Focus on quality, not just quantity - Peng, Changhui (Nature, 2011)

From static biogeographical model to dynamic global vegetation model: a global perspective on modelling vegetation dynamics - Peng, Changhui (Ecological Modelling, 2000)

Growth and yield models for uneven-aged stands: past, present and future - Peng, Changhui (Forest Ecology and Management, 2000)

Understanding the role of forest simulation models in sustainable forest management - Peng, Changhui (Environmental Impact Assessment Review, 2000)

Toward dynamic global vegetation models for simulating vegetation–climate interactions and feedbacks: recent developments, limitations, and future challenges - Quillet, Anne; Peng, Changhui; Garneau, Michelle (Environmental Reviews, 2010)
There is a lack in representation of biosphere–atmosphere interactions in current climate models. To fill this gap, one may introduce vegetation dynamics in surface transfer schemes or couple global climate models (GCMs) with vegetation dynamics models. As these vegetation dynamics models were not designed to be included in GCMs, how are the latest generation dynamic global vegetation models (DGVMs) suitable for use in global climate studies? This paper reviews the latest developments in DGVM modelling as well as the development of DGVM–GCM coupling in the framework of global climate studies. Limitations of DGVM and coupling are shown and the challenges of these methods are highlighted. During the last decade, DGVMs underwent major changes in the representation of physical and biogeochemical mechanisms such as photosynthesis and respiration processes as well as in the representation of regional properties of vegetation. However, several limitations such as carbon and nitrogen cycles, competition, land-use and land-use changes, and disturbances have been identified. In addition, recent advances in model coupling techniques allow the simulation of the vegetation–atmosphere interactions in GCMs with the help of DGVMs. Though DGVMs represent a good alternative to investigate vegetation–atmosphere interactions at a large scale, some weaknesses in evaluation methodology and model design need to be further investigated to improve the results.

Relationships between stand growth and structural diversity in spruce-dominated forests in New Brunswick, Canada - Lei, Xiangdong; Wang, Weifeng; Peng, Changhui (Canadian Journal of Forest Research, 2009)
Relationships between stand growth and structural diversity were examined in spruce-dominated forests in New Brunswick, Canada. Net growth, survivor growth, mortality, and recruitment represented stand growth, and tree species, size, and height diversity indices were used to describe structural diversity. Mixed-effects second-order polynomial regressions were employed for statistical analysis. Results showed stand structural diversity had a significant positive effect on net growth and survivor growth by volume but not on mortality and recruitment. Among the tested diversity indices, the integrated diversity of tree species and height contributed most to stand net growth and survivor growth. Structural diversity showed increasing trends throughout the developmental stages from young, immature, mature, and overmature forest stands. This relationship between stand growth and structural diversity may be due to stands featuring high structural diversity that enhances niche complementarities of resource use because trees exist within different horizontal and vertical layers, and strong competition resulted from size differences among trees. It is recommended to include effects of species and structural diversity in forest growth modeling initiatives. Moreover, uneven-aged stand management in conjunction with selective or partial cutting to maintain high structural diversity is also recommended to maintain biodiversity and rapid growth in spruce-dominated forests.

Global patterns of particulate organic carbon export from land to the ocean - Li, Mingxu; Peng, Changhui; He, Nianpeng (Ecohydrology, 2022)
Abstract Global rivers and streams are important carbon transport pathways from land to the ocean. However, few studies have quantified terrigenous carbon dynamics in river ecosystems and its variations due to climate change and anthropogenic perturbations. Therefore, our study analysed fluvial particulate organic carbon (POC) and developed a processed‐based model (TRIPLEX‐HYDRA) to simulate the production, transport and removal (i.e., deposition, degradation and dam retention) processes of fluvial POC along the land–ocean aquatic continuum (LOAC). Based on our results, approximately 0.29 Pg of POC is exported from land to the ocean through rivers each year. More specifically, we found that rivers at low latitudes (30°S–30°N, 0.18 Pg yr −1 ) and high northern latitudes (60°N–90°N, 0.05 Pg yr −1 ) had higher POC fluxes compared to rivers in other regions. This high POC flux is related to strong erosion rates and high soil organic carbon storage. Additionally, our model simulation revealed that total POC flux from global river has not significantly changed from 1983 to 2015 but displays markedly decreased or increased trend at regional scale. These regional variations in POC export are affected by climate warming and dam construction. Moreover, approximately 0.46 Pg of POC is deposited or trapped by dams along the LOAC system, which plays a vital role in the global river carbon budget. Although some limitations and uncertainties remain, this study establishes a theoretical and methodological basis for quantifying riverine POC dynamics in the LOAC system.

Individual-tree basal area growth models for jack pine and black spruce in northern Ontario - Zhang, Lianjun; Peng, Changhui; Dang, Qinglai (The Forestry Chronicle, 2004)
Individual-tree models of five-year basal area growth were developed for jack pine (Pinus banksiana Lamb.) and black spruce (Picea mariana (Mill.) BSP) in northern Ontario. Tree growth data were collected from long-term permanent plots of pure and mixed stands of the two species. The models were fitted using mixed model methods due to correlated remeasurements of tree growth over time. Since the data covered a wide range of stand ages, stand conditions and tree sizes, serious heterogeneous variances existed in the data. Therefore, the coefficients of the final models were obtained using weighted regression techniques. The models for the two species were evaluated across 4-cm diameter classes using independent data. The results indicated (1) the models of jack pine and black spruce produced similar prediction errors and biases for intermediate-sized trees (1228 cm in tree diameter), (2) both models yielded relatively large errors and biases for larger trees (> 28 cm) than those for smaller trees, and (3) the jack pine model produced much larger errors and biases for small-sized trees (< 12 cm) than did the black spruce model. Key words: mixed models, repeated measures, model validation

Land use induced changes of organic carbon storage in soils of China - Wu, Haibin; Guo, Zhengtang; Peng, Changhui (Global Change Biology, 2003)
Abstract Using the data compiled from China's second national soil survey and an improved method of soil carbon bulk density, we have estimated the changes of soil organic carbon due to land use, and compared the spatial distribution and storage of soil organic carbon (SOC) in cultivated soils and noncultivated soils in China. The results reveal that ∼ 57% of the cultivated soil subgroups ( ∼ 31% of the total soil surface) have experienced a significant carbon loss, ranging from 40% to 10% relative to their noncultivated counterparts. The most significant carbon loss is observed for the non‐irrigated soils (dry farmland) within a semiarid/semihumid belt from northeastern to southwestern China, with the maximum loss occurring in northeast China. On the contrary, SOC has increased in the paddy and irrigated soils in northwest China. No significant change is observed for forest soils in southern China, grassland and desert soils in northwest China, as well as irrigated soils in eastern China. The SOC storage and density under noncultivated conditions in China are estimated to ∼ 77.4 Pg (10 15 g) and ∼ 8.8 kg C m −2 , respectively, compared to a SOC storage of ∼ 70.3 Pg and an average SOC density of ∼ 8.0 kg C m −2 under the present‐day conditions. This suggests a loss of ∼ 7.1 Pg SOC and a decrease of ∼ 0.8 kg C m −2 SOC density due to increasing human activities, in which the loss in organic horizons has contributed to ∼ 77%. This total loss of SOC in China induced by land use represents ∼ 9.5% of the world's SOC decrease. This amount is equivalent to ∼ 3.5 ppmv of the atmospheric CO 2 increase. Since ∼ 78% of the currently cultivated soils in China have been degraded to a low/medium productivities and are responsible for most of the SOC loss, an improved land management, such as the development of irrigated and paddy land uses, would have a considerable potential in restoring the SOC storage. Assuming a restoration of ∼ 50% of the lost SOC during the next 20–50 years, the soils in China would absorb ∼ 3.5 Pg of carbon from the atmosphere.

Distribution and storage of soil organic carbon in China - Wu, Haibin; Guo, Zhengtang; Peng, Changhui (Global Biogeochemical Cycles, 2003)
Surface soils hold the largest terrestrial organic carbon pool, although estimates of the world's soil organic carbon storage remain controversial, largely due to spatial data gaps or insufficient data density. In this study, spatial distribution and storage of soil organic carbon in China are estimated using the published data from 34,411 soil profiles investigated during China's second national soil survey. Results show that organic carbon density in soils varies from 0.73 to 70.79 kg C/m 2 with the majority ranging between 4.00 and 11.00 kg C/m 2 . Carbon density decreases from east to west. A general southward increase is obvious for western China, while carbon density decreases from north to south in eastern China. Highest values are observed in forest soils in northeast China and in subalpine soils in the southeastern part of the Tibetan Plateau. The average density of ∼8.01 kg C/m 2 in China is lower than the world's mean organic carbon density in soil (∼10.60 kg C/m 2 ), mainly due to the extended arid and semi‐arid regions. Total organic carbon storage in soils in China is estimated to be ∼70.31 Pg C, representing ∼4.7% of the world storage. Carbon storage in the surface organic horizons which is most sensitive to interactions with the atmosphere and environmental change is ∼32.54 Pg C.

Developing and Validating Nonlinear Height–Diameter Models for Major Tree Species of Ontario's Boreal Forests - Peng, Changhui; Zhang, Lianjun; Liu, Jinxun (Northern Journal of Applied Forestry, 2001)
Abstract Six commonly used nonlinear growth functions were fitted to individual tree height-diameter data of nine major tree species in Ontario's boreal forests. A total of 22,571 trees was collected from new permanent sample plots across the northeast and northwest of Ontario.The available data for each species were split into two sets: the majority (90%) was used to estimate model parameters, and the remaining data (10%) were reserved to validate the models. The performance of the models was compared and evaluated by model, R2, mean difference, and mean absolute difference. The results showed that these six sigmoidal models were able to capture the height–diameter relationships and fit the data equally well, but produced different asymptote estimates. Sigmoidal models such as Chapman–Richards, Weibull, and Schnute functions provided the most satisfactory height predictions. The effect of model performance on tree volume estimation was also investigated. Tree volumes of different species were computed by Honer's volume equations using a range of diameters and the predicted tree total height from the six models. For trees with diameter less than 55 cm, the six height-diameter models produced very similar results for all species, while more differentiation among the models was observed for large-sized trees (e.g., diameters > 80 cm). North. J. Appl. For. 18:87–94.

Effects of street plants on atmospheric particulate dispersion in urban streets: A review - Wang, Xiaoshuang; Zhou, Zhixiang; Xiang, Yang; Peng, Chucai; Peng, Changhui (Environmental Reviews, 2024)
Numerous empirical studies have demonstrated that street trees not only reduce dust pollution and absorb particulate matter (PM) but also improve microclimates, providing both ecological functions and aesthetic value. However, recent research has revealed that street tree canopy cover can impede the dispersion of atmospheric PM within street canyons, leading to the accumulation of street pollutants. Although many studies have investigated the impact of street trees on air pollutant dispersion within street canyons, the extent of their influence remains unclear and uncertain. Pollutant accumulation corresponds to the specific characteristics of individual street canyons, coupled with meteorological factors and pollution source strength. Notably, the characteristics of street tree canopy cover also exert a significant influence. There is still a quantitative research gap on street tree cover impacts with respect to pollution and dust reduction control measures within street spaces. To improve urban traffic environments, policymakers have mainly focused on scientifically based street vegetation deployment initiatives in building ecological garden cities and improving the living environment. To address uncertainties regarding the influence of street trees on the dispersion of atmospheric PM in urban streets, this study reviews dispersion mechanisms and key atmospheric PM factors in urban streets, summarizes the research approaches used to conceptualize atmospheric PM dispersion in urban street canyons, and examines urban plant efficiency in reducing atmospheric PM. Furthermore, we also address current challenges and future directions in this field to provide a more comprehensive understanding of atmospheric PM dispersion in urban streets and the role that street trees play in mitigating air pollution.

Stimulation of terrestrial ecosystem carbon storage by nitrogen addition: a meta-analysis - Yue, Kai; Peng, Yan; Peng, Changhui; Yang, Wanqin; Peng, Xin; Wu, Fuzhong (Scientific Reports, 2016)
Abstract Elevated nitrogen (N) deposition alters the terrestrial carbon (C) cycle, which is likely to feed back to further climate change. However, how the overall terrestrial ecosystem C pools and fluxes respond to N addition remains unclear. By synthesizing data from multiple terrestrial ecosystems, we quantified the response of C pools and fluxes to experimental N addition using a comprehensive meta-analysis method. Our results showed that N addition significantly stimulated soil total C storage by 5.82% ([2.47%, 9.27%], 95% CI, the same below) and increased the C contents of the above- and below-ground parts of plants by 25.65% [11.07%, 42.12%] and 15.93% [6.80%, 25.85%], respectively. Furthermore, N addition significantly increased aboveground net primary production by 52.38% [40.58%, 65.19%] and litterfall by 14.67% [9.24%, 20.38%] at a global scale. However, the C influx from the plant litter to the soil through litter decomposition and the efflux from the soil due to microbial respiration and soil respiration showed insignificant responses to N addition. Overall, our meta-analysis suggested that N addition will increase soil C storage and plant C in both above- and below-ground parts, indicating that terrestrial ecosystems might act to strengthen as a C sink under increasing N deposition.

Formulating and parameterizing the allocation of net primary productivity for modeling overmature stands in boreal forest ecosystems - Zhou, Xiaolu; Peng, Changhui; Dang, Qing-Lai (Ecological Modelling, 2006)

Methane Emissions from Paddy Rice Fields: Strategies towards Achieving A Win-Win Sustainability Scenario between Rice Production and Methane Emission Reduction - Epule, Epule Terence; Peng, Changhui; Mafany, Ndiva Mongoh (Journal of Sustainable Development, 2011)

Responses of autumn vegetation phenology to climate change and urbanization at northern middle and high latitudes - Du, Hui; Wang, Mei; Liu, Yuxin; Guo, Mengjiao; Peng, Changhui; Li, Peng (International Journal of Applied Earth Observation and Geoinformation, 2022)

Individual height–diameter models for young black spruce ( Picea mariana ) and jack pine ( Pinus banksiana ) plantations in New Brunswick, Canada - Lei, Xiangdong; Peng, Changhui; Wang, Haiyan; Zhou, Xiaolu (The Forestry Chronicle, 2009)
Historically, height–diameter models have mainly been developed for mature trees; consequently, few height–diameter models have been calibrated for young forest stands. In order to develop equations predicting the height of trees with small diameters, 46 individual height–diameter models were fitted and tested in young black spruce (Picea mariana) and jack pine (Pinus banksiana) plantations between the ages of 4 to 8 years, measured from 182 plots in New Brunswick, Canada. The models were divided into 2 groups: a diameter group and a second group applying both diameter and additional stand- or tree-level variables (composite models). There was little difference in predicting tree height among the former models (Group I) while the latter models (Group II) generally provided better prediction. Based on goodness of fit (R 2 and MSE), prediction ability (the bias and its associated prediction and tolerance intervals in absolute and relative terms), and ease of application, 2 Group II models were recommended for predicting individual tree heights within young black spruce and jack pine forest stands. Mean stand height was required for application of these models. The resultant tolerance intervals indicated that most errors (95%) associated with height predictions would be within the following limits (a 95% confidence level): [-0.54 m, 0.54 m] or [-14.7%, 15.9%] for black spruce and [-0.77 m, 0.77 m] or [-17.1%, 18.6%] for jack pine. The recommended models are statistically reliable for growth and yield applications, regeneration assessment and management planning. Key words: composite model, linear model, model calibration, model validation, prediction interval, tolerance interval

Simulating age-related changes in carbon storage and allocation in a Chinese fir plantation growing in southern China using the 3-PG model - Zhao, Meifang; Xiang, Wenhua; Peng, Changhui; Tian, Dalun (Forest Ecology and Management, 2009)

New coupled model used inversely for reconstructing past terrestrial carbon storage from pollen data: validation of model using modern data - Wu, Haibin; Guiot, Joël; Peng, Changhui; Guo, Zhengtang (Global Change Biology, 2009)
Abstract The knowledge of potential impacts of climate change on terrestrial vegetation is crucial to understand long‐term global carbon cycle development. Discrepancy in data has long existed between past carbon storage reconstructions since the Last Glacial Maximum by way of pollen, carbon isotopes, and general circulation model (GCM) analysis. This may be due to the fact that these methods do not synthetically take into account significant differences in climate distribution between modern and past conditions, as well as the effects of atmospheric CO 2 concentrations on vegetation. In this study, a new method to estimate past biospheric carbon stocks is reported, utilizing a new integrated ecosystem model (PCM) built on a physiological process vegetation model (BIOME4) coupled with a process‐based biospheric carbon model (DEMETER). The PCM was constrained to fit pollen data to obtain realistic estimates. It was estimated that the probability distribution of climatic parameters, as simulated by BIOME4 in an inverse process, was compatible with pollen data while DEMETER successfully simulated carbon storage values with corresponding outputs of BIOME4. The carbon model was validated with present‐day observations of vegetation biomes and soil carbon, and the inversion scheme was tested against 1491 surface pollen spectra sample sites procured in Africa and Eurasia. Results show that this method can successfully simulate biomes and related climates at most selected pollen sites, providing a coefficient of determination ( R ) of 0.83–0.97 between the observed and reconstructed climates, while also showing a consensus with an R ‐value of 0.90–0.96 between the simulated biome average terrestrial carbon variables and the available observations. The results demonstrate the reliability and feasibility of the climate reconstruction method and its potential efficiency in reconstructing past terrestrial carbon storage.

Distribution of soil inorganic carbon storage and its changes due to agricultural land use activity in China - Wu, Haibin; Guo, Zhengtang; Gao, Qiong; Peng, Changhui (Agriculture, Ecosystems & Environment, 2009)

Marginal effects of silvicultural treatments on soil nutrients following harvest in a Chinese fir plantation - Xiang, Wenhua; Chai, Hongxia; Tian, Dalun; Peng, Changhui (Soil Science and Plant Nutrition, 2009)

Satellite-based estimation of biomass carbon stocks for northeast China's forests between 1982 and 1999 - Tan, Kun; Piao, Shilong; Peng, Changhui; Fang, Jingyun (Forest Ecology and Management, 2007)

Meta-analysis and its application in global change research - Lei, XiangDong; Peng, ChangHui; Tian, DaLun; Sun, JianFeng (Chinese Science Bulletin, 2007)

Relationships between species richness of vascular plants and terrestrial vertebrates in China: analyses based on data of nature reserves - Zhao, Shuqing; Fang, Jingyun; Peng, Changhui; Tang, Zhiyao (Diversity and Distributions, 2006)
ABSTRACT The relationship between plant diversity and animal diversity on a broadscale and its mechanisms are uncertain. In this study, we explored this relationship and its possible mechanisms using data from 186 nature reserves across China on species richness of vascular plants and terrestrial vertebrates, and climatic and topographical variables. We found significant positive correlations between species richness in almost all taxa of vascular plants and terrestrial vertebrates. Multiple regression analyses indicated that plant richness was a significant predictor of richness patterns for terrestrial vertebrates (except birds), suggesting that a causal association may exist between plant diversity and vertebrate diversity in China. The mechanisms for the relationships between species richness of plants and animals are probably dependent on vertebrate groups. For mammals (endothermic vertebrates), this relationship probably represents the integrated effects of plants on animals through trophic links (i.e. providing foods) and non‐trophic interactions (i.e. supplying habitats), whereas for amphibians and reptiles (ectothermic vertebrates), this may be a result of the non‐trophic links, such as the effects of plants on the resources that amphibians and reptiles require.

The relationships between terrestrial vertebrate species richness in China’s nature reserves and environmental variables - Zhao, Shuqing; Fang, Jingyun; Peng, Changhui; Tang, Zhiyao (Canadian Journal of Zoology, 2006)
Explaining species richness patterns over broad geographic scales is a central issue of biogeography and macroecology. In this study, we took spatial autocorrelation into account and used terrestrial vertebrate species richness data from 211 nature reserves, together with climatic and topographical variables and reserve area, to explain terrestrial vertebrate species richness patterns in China and to test two climatically based hypotheses for animals. Our results demonstrated that species richness patterns of different terrestrial vertebrate taxa were predicted by the environmental variables used, in a decreasing order, as reptiles (56.5%), followed by amphibians (51.8%), mammals (42%), and birds (19%). The endothermic vertebrates (mammals and birds) were closely correlated with net primary productivity (NPP), which supports the productivity hypothesis, whereas the ectothermic vertebrates (amphibians and reptiles) were strongly associated with both water and energy variables but weakly with NPP, which supports the physiologically based ambient climate hypothesis. The differences in the dependence of endothermic and ectothermic vertebrates on productivity or ambient climate may be due in part to their different thermoregulatory mechanisms. Consistent with earlier studies, mammals were strongly and positively related to geomorphologic heterogeneity, measured by elevation range, implying that the protection of mountains may be especially important in conserving mammalian diversity.

Methane Emissions from Unique Wetlands in China: Case Studies, Meta Analyses and Modelling - Chen, Huai; Wu, Ning; Peng, Changhui; Wang, Yanfen (DE GRUYTER, 2015)

Combination of nitrogen deposition and ultraviolet-B radiation decreased litter decomposition in subtropical China - Song, Xinzhang; Zhang, Huiling; Jiang, Hong; Peng, Changhui (Plant and Soil, 2014)

Integrating major agricultural practices into the TRIPLEX-GHG model v2.0 for simulating global cropland nitrous oxide emissions: Development, sensitivity analysis and site evaluation - Song, Hanxiong; Peng, Changhui; Zhang, Kerou; Zhu, Qiuan (Science of The Total Environment, 2022)

Comparative analyses of different biogenic CO2 emission accounting systems in life cycle assessment - Liu, Weiguo; Zhu, Qiuan; Zhou, Xiaolu; Peng, Changhui (Science of The Total Environment, 2019)

Development and evaluation of ecoregion-based jack pine height-diameter models for Ontario - Zhang, Lianjun; Peng, Changhui; Huang, Shongming; Zhou, Xiaolu (The Forestry Chronicle, 2002)
The Chapman-Richards growth function is used to model jack pine (Pinus banksiana Lamb.) tree height-diameter relationships at provincial, regional, and ecoregional levels. The results suggest that the tree height-diameter relationships of jack pine are significantly different among the geographic regions of Ontario, depending on local climatic, soil, and ecological conditions. In light of this study, the provincial and regional height-diameter models are not appropriate for predicting tree heights at the ecoregional level. Further, applying a specific ecoregional model to other ecoregions will also result in significant biases for predicting local tree heights. The ecoregion-based height-diameter models developed in this study may provide more accurate information on tree growth and development to forest resource managers and planners. Key words: Chapman-Richards growth function, permanent sample plot, non-linear extra sum of square method, forest management

The Importance of Energy Theory in Shaping Elevational Species Richness Patterns in Plants - Jiang, Zihan; Liu, Qiuyu; Xu, Wei; Peng, Changhui (Biology, 2022)
Many hypotheses have been proposed to explain elevational species richness patterns; however, evaluating their importance remains a challenge, as mountains that are nested within different biogeographic regions have different environmental attributes. Here, we conducted a comparative study for trees, shrubs, herbs, and ferns along the same elevational gradient for 22 mountains worldwide, examining the performance of hypotheses of energy, tolerance, climatic variability, and spatial area to explain the elevational species richness patterns for each plant group. Results show that for trees and shrubs, energy-related factors exhibit greater explanatory power than other factors, whereas the factors that are associated with climatic variability performed better in explaining the elevational species richness patterns of herbs and ferns. For colder mountains, energy-related factors emerged as the main drivers of woody species diversity, whereas in hotter and wetter ecosystems, temperature and precipitation were the most important predictors of species richness along elevational gradients. For herbs and ferns, the variation in species richness was less than that of woody species. These findings provide important evidence concerning the generality of the energy theory for explaining the elevational species richness pattern of plants, highlighting that the underlying mechanisms may change among different growth form groups and regions within which mountains are nested.

Rainfall and Deforestation Dilemma for Cereal Production in the Sudano-Sahel of Cameroon - Epule, Terence Epule; Peng, Changhui; Lepage, Laurent; Chen, Zhi (Journal of Agricultural Science, 2012)

Forest Loss Triggers in Cameroon: A Quantitative Assessment Using Multiple Linear Regression Approach - Epule, Epule Terence; Peng, Changhui; Lepage, Laurent; Chen, Zhi (Journal of Geography and Geology, 2011)

Controls of soil and aggregate‐associated organic carbon variations following natural vegetation restoration on the L oess P lateau in C hina - Deng, Lei; Kim, Dong‐Gill; Peng, Changhui; Shangguan, Zhouping (Land Degradation & Development, 2018)
Abstract Natural vegetation restoration can enhance soil organic carbon (SOC) sequestration, but the mechanisms and control factors underlying SOC sequestration are still unknown. The objectives of the study are to quantify the temporal variation of soil and aggregate‐associated organic carbon (OC) and identify factors controlling the variation following natural vegetation restoration after farmland abandonment. We collected soils from sites having 5, 30, 60, 100, and 160 years of a natural vegetation restoration chronosequence after farmland abandonment in the Loess Plateau, China. The results showed that natural vegetation restoration increased macroaggregates (0.25–2 mm; 46.6% to 73.9%), SOC (2.27 to 9.81 g kg −1 ), and aggregate OC (7.33 to 36.98 g kg −1 ) in the top 20‐cm soil compared with abandoned farmland, and the increases mainly occurred in the early stage (<60 years). The increase of SOC was contributed by OC accumulated in macroaggregates (0.25–2 mm) rather than microaggregates (≤0.25 mm). Moreover, SOC sequestration in the topsoil (0–10 cm) was mainly determined by fine root biomass (FR), labile organic carbon (LOC), and microbial biomass carbon (MBC). And in the subsoil (10–20 cm), SOC sequestration was mainly determined by the proportion of macroaggregates. The results suggest that natural vegetation restoration increased SOC and aggregate OC, and FR, MBC, LOC, and the physical protection of aggregates played important roles in regulating SOC and aggregate OC.

Enabling Conditions for Successful Greening of Public Spaces: The Case of Touroua, Cameroon Based on Perceptions - Epule, Epule Terence; Peng, Changhui; Lepage, Laurent; Chen, Zhi (Small-scale Forestry, 2014)

The causes, effects and challenges of Sahelian droughts: a critical review - Epule, Epule Terence; Peng, Changhui; Lepage, Laurent; Chen, Zhi (Regional Environmental Change, 2014)

Policy options towards deforestation reduction in Cameroon: An analysis based on a systematic approach - Epule, Epule Terence; Peng, Changhui; Lepage, Laurent; Chen, Zhi (Land Use Policy, 2014)

Effects of harvesting regimes on carbon and nitrogen dynamics of boreal forests in central Canada: a process model simulation - Peng, Changhui; Jiang, Hong; Apps, Michael J.; Zhang, Yanli (Ecological Modelling, 2002)

Comparing standardised precipitation and barley yield across Quebec - Epule, Terence Epule; Poirier, Vincent; Lafontaine, Simon; Peng, Changhui (Environmental Science and Pollution Research, 2024)

Divergent contributions of spring and autumn photosynthetic phenology to seasonal carbon uptake of subtropical vegetation in China - Peng, Ying; Li, Peng; Zhou, Xiaolu; Luo, Yunpeng; Zhang, Cicheng; Wang, Longjun; Li, Tong; Peng, Changhui (Journal of Geographical Sciences, 2024)

Variation in runoff with age of Chinese fir plantations in Central South China - Tian, Dalun; Yan, Wende; Chen, Xiaoyong; Deng, Xiangwen; Peng, Yuanying; Kang, Wenxing; Peng, Changhui (Hydrological Processes, 2008)
Abstract To determine the influence of forest structures on runoff characteristics, the hydrological effects of Chinese fir plantations were studied by analysing runoff patterns at different growth and development stages (stand age classes I to V) from 1984 to 2004 at the Huitong Ecosystem Research Station, Central South University of Forestry and Technology, Hunan Province, Central South China. Results for two small experimental Chinese fir watersheds showed different peak values for surface runoff amount and coefficients at different ages, with lowest values in age classes I and V and highest values in age classes II and III. However, both underground and total runoff coefficients decreased with increasing age class. Total runoff coefficient was about twice as high in age class I (30·8%) as that in age class V (15·8%). Higher underground and total runoff coefficients were found in young forests. This was mainly attributed to soil disturbance due to human management practices such as site ploughing. Results indicate that Chinese fir plantations play a significant role in regulating water distribution in the watershed. Useful information is provided on the effects of forest management practices on hydrological processes in forest plantations. Copyright © 2008 John Wiley & Sons, Ltd.

Divergent response of vegetation phenology to extreme temperatures and precipitation of different intensities on the Tibetan Plateau - Sun, Mai; Li, Peng; Ren, Peixin; Tang, Jiayi; Zhang, Cicheng; Zhou, Xiaolu; Peng, Changhui (Science China Earth Sciences, 2023)

Degradation of lignin and cellulose during foliar litter decomposition in an alpine forest river - Yue, Kai; Peng, Changhui; Yang, Wanqin; Peng, Yan; Zhang, Chuan; Huang, Chunping; Wu, Fuzhong (Ecosphere, 2016)
Abstract Lignin and cellulose are thought to be critical factors that affect the rate of litter decomposition; however, few data are available on their degradation dynamics during litter decomposition in lotic ecosystems, such as forest rivers, where litter can decompose much more rapidly than in terrestrial ecosystems. We studied the degradation of lignin and cellulose in the foliar litter of four dominant riparian species (willow: Salix paraplesia ; azalea: Rhododendron lapponicum ; cypress: Sabina saltuaria ; and larch: Larix mastersiana ) in an alpine forest river. Over an entire year's incubation, litter lignin and cellulose degraded by 14.7–100% and 57.7–100% of their initial masses, respectively, depending on litter species. Strong degradations of lignin and cellulose occurred in the prefreezing period (i.e., the first 41 d) during litter decomposition, and the degradation rate was the highest among all the decomposition periods regardless of litter species. Litter species, decomposition period, and environmental factors such as temperature and nutrient availability showed significant influences on lignin and cellulose degradation rates. Compared with previously reported data regarding the dynamics of lignin and cellulose during litter decomposition in terrestrial ecosystems, our results suggest that lignin and cellulose can be degraded much more rapidly in lotic ecosystems, indicating that the traditionally used two‐phased model for the dynamics of lignin in decomposing litter may not be suitable in lotic ecosystems.

Satellite monitoring reveals short-term cumulative and time-lag effect of drought and heat on autumn photosynthetic phenology in subtropical vegetation - Ren, Peixin; Li, Peng; Tang, Jiayi; Li, Tong; Liu, Zelin; Zhou, Xiaolu; Peng, Changhui (Environmental Research, 2023)

Divergent responses of autumn vegetation phenology to climate extremes over northern middle and high latitudes - Wang, Mei; Li, Peng; Peng, Changhui; Xiao, Jingfeng; Zhou, Xiaolu; Luo, Yunpeng; Zhang, Cicheng (Global Ecology and Biogeography, 2022)
Abstract Aim Compared with gradual climate change, extreme climatic events have more direct and dramatic impacts on vegetation growth. However, the influence of climate extremes on important phenological periods, such as the end of the growing season (EOS), remains unclear. Here, we investigate the temporal trends of EOS across different biomes and quantify the response of EOS to multiple climate extreme indices (CEIs). Location Northern middle and high latitudes. Time period 2000–2020. Major taxa studied Plants. Methods Three phenology extraction methods were used to compute EOS from satellite, FLUXNET and Pan European Phenology Project PEP725 phenological datasets. Different stress states of cold, hot, dry and wet extremes were represented by 12 CEIs. Partial correlation and ridge regression analysis were used to quantify the response of EOS to climate extremes across latitudinal and biome scales. Results Our study showed a delayed EOS in boreal biomes, but a significantly advanced EOS in temperate biomes. The advanced EOS induced by cold stress was observed for c . 80% of the vegetated pixels. The warm‐related CEIs delayed the EOS in high latitudes, and the delayed effect weakened or even reversed with decreasing latitude. In contrast, EOS exhibited opposite response patterns to dry days and wet‐related CEIs. Overall, EOS exhibited higher sensitivity to extreme temperature in boreal biomes than in temperate biomes. Specifically, continuous drought and high heat stress induced an earlier EOS in some temperate forest biomes, whereas moderate heat stress delayed the EOS in most study biomes. In contrast, EOS was not sensitive to extreme drought in water‐restricted biomes. Main conclusions EOS exhibited divergent responses to various climate extremes with different intensities and frequencies. Moreover, the response of EOS to extreme climate stress was dependent on the biome and latitude. These findings emphasize the importance of incorporating the divergent extreme climate effects into vegetation phenological models and Earth system models.

A Review of General Methods for Quantifying and Estimating Urban Trees and Biomass - Yang, Mingxia; Zhou, Xiaolu; Liu, Zelin; Li, Peng; Tang, Jiayi; Xie, Binggeng; Peng, Changhui (Forests, 2022)
Understanding the biomass, characteristics, and carbon sequestration of urban forests is crucial for maintaining and improving the quality of life and ensuring sustainable urban planning. Approaches to urban forest management have been incorporated into interdisciplinary, multifunctional, and technical efforts. In this review, we evaluate recent developments in urban forest research methods, compare the accuracy and efficiency of different methods, and identify emerging themes in urban forest assessment. This review focuses on urban forest biomass estimation and individual tree feature detection, showing that the rapid development of remote sensing technology and applications in recent years has greatly benefited the study of forest dynamics. Included in the review are light detection and ranging-based techniques for estimating urban forest biomass, deep learning algorithms that can extract tree crowns and identify tree species, methods for measuring large canopies using unmanned aerial vehicles to estimate forest structure, and approaches for capturing street tree information using street view images. Conventional methods based on field measurements are highly beneficial for accurately recording species-specific characteristics. There is an urgent need to combine multi-scale and spatiotemporal methods to improve urban forest detection at different scales.

Recent advances in carbon footprint studies of urban ecosystems: overview, application, and future challenges - Chen, Kexin; Yang, Mingxia; Zhou, Xiaolu; Liu, Zelin; Li, Peng; Tang, Jiayi; Peng, Changhui (Environmental Reviews, 2022)
Urban ecosystems are complex systems with anthropogenic features that generate considerable CO 2 emissions, which contributes to global climate change. Quantitative estimates of the carbon footprint of urban ecosystems are crucial for developing low-carbon development policies to mitigate climate change. Herein, we reviewed more than 195 urban carbon footprint and carbon footprint related studies, collated the recent progress in carbon footprint calculation methods and research applications of the urban ecosystem carbon footprint, analyzed the research applications of the carbon footprint of different cities, and focused on the need to study the urban ecosystem carbon footprint from a holistic perspective. Specifically, we aimed to: (i) compare the strengths and weaknesses of five existing carbon footprint calculation methods [life cycle assessment, input–output analysis, hybrid life cycle assessment, carbon footprint calculator, and Intergovernmental Panel on Climate Change (IPCC)]; (ii) analyze the status of current research on the carbon footprint of different urban subregions based on different features; and (iii) highlight new methods and areas of research on the carbon footprint of future urban ecosystems. Not all carbon footprint accounting methods are applicable to the carbon footprint determination of urban ecosystems; although the IPCC method is more widely used than the others, the hybrid life cycle assessment method is more accurate. With the emergence of new science and technology, quantitative methods to calculate the carbon footprint of urban ecosystems have evolved, becoming more accurate. Further development of new technologies, such as big data and artificial intelligence, to assess the carbon footprint of urban ecosystems is anticipated to help address the emerging challenges in urban ecosystem research effectively to achieve carbon neutrality and urban sustainability under global change.

Response of Vegetation Photosynthetic Phenology to Urbanization in Dongting Lake Basin, China - Li, Peng; Sun, Mai; Liu, Yuxin; Ren, Peixin; Peng, Changhui; Zhou, Xiaolu; Tang, Jiayi (Remote Sensing, 2021)
Urbanization can induce environmental changes such as the urban heat island effect, which in turn influence the terrestrial ecosystem. However, the effect of urbanization on the phenology of subtropical vegetation remains relatively unexplored. This study analyzed the changing trend of vegetation photosynthetic phenology in Dongting Lake basin, China, and its response to urbanization using nighttime light and chlorophyll fluorescence datasets. Our results indicated the start of the growing season (SOS) of vegetation in the study area was significantly advanced by 0.70 days per year, whereas the end of the growing season (EOS) was delayed by 0.24 days per year during 2000–2017. We found that urbanization promoted the SOS advance and EOS delay. With increasing urbanization intensity, the sensitivity of SOS to urbanization firstly increased then decreased, while the sensitivity of EOS to urbanization decreased with urbanization intensity. The climate sensitivity of vegetation phenology varied with urbanization intensity; urbanization induced an earlier SOS by increasing preseason minimum temperatures and a later EOS by increasing preseason precipitation. These findings improve our understanding of the vegetation phenology response to urbanization in subtropical regions and highlight the need to integrate human activities into future vegetation phenology models.

Analysis and Prediction of Expansion of Central Cities Based on Nighttime Light Data in Hunan Province, China - Liu, Yuxin; He, Tian; Wang, Yi; Peng, Changhui; Du, Hui; Yuan, Shuai; Li, Peng (Sustainability, 2021)
Quantifying the characteristics of urban expansion as well as influencing factors is essential for the simulation and prediction of urban expansion. In this study, we extracted the built-up regions of 14 central cities in the Hunan province using the DMSP-OLS night light remote sensing datasets from 1992 to 2018, and evaluated the spatial and temporal characteristics of the built-up regions in terms of the area, expansion speed, and main expansion direction. The backpropagation (BP) neural network and autoregressive integrated moving average (ARIMA) model were used to predict the area of the built-up regions from 2019 to 2026. The model predictions were based on the GDP, ratio of the secondary industry output to the GDP, ratio of the tertiary industry output to the GDP, year-end urban population, and urban road area. The results demonstrated that the built-up area and expansion speed of the central cities in the eastern part of the Hunan province were significantly higher than those in the western part. The main expansion directions of the 14 central cities were east and south. The urban road area, year-end urban population, and GDP were the main driving factors of the expansion. The urban expansion model based on the BP neural network provided a high prediction accuracy (R = 0.966). It was estimated that the total area of urban built-up regions in the Hunan province will reach 2463.80 km2 by 2026. These findings provide a new perspective for predicting urban areas rapidly and simply, and it also provides a useful reference for studying the spatial expansion characteristics of central cities and formulating a sustainable urban development strategy during the 14th Five-Year Plan of China.

Modelling the impacts of climate and land use changes on soil water erosion: Model applications, limitations and future challenges - Guo, Yanrong; Peng, Changhui; Zhu, Qiuan; Wang, Meng; Wang, Han; Peng, Shushi; He, Honglin (Journal of Environmental Management, 2019)

Effects of three global change drivers on terrestrial C:N:P stoichiometry: a global synthesis - Yue, Kai; Fornara, Dario A.; Yang, Wanqin; Peng, Yan; Li, Zhijie; Wu, Fuzhong; Peng, Changhui (Global Change Biology, 2017)
Abstract Over the last few decades, there has been an increasing number of controlled‐manipulative experiments to investigate how plants and soils might respond to global change. These experiments typically examined the effects of each of three global change drivers [i.e., nitrogen (N) deposition, warming, and elevated CO 2 ] on primary productivity and on the biogeochemistry of carbon (C), N, and phosphorus (P) across different terrestrial ecosystems. Here, we capitalize on this large amount of information by performing a comprehensive meta‐analysis (>2000 case studies worldwide) to address how C:N:P stoichiometry of plants, soils, and soil microbial biomass might respond to individual vs. combined effects of the three global change drivers. Our results show that (i) individual effects of N addition and elevated CO 2 on C:N:P stoichiometry are stronger than warming, (ii) combined effects of pairs of global change drivers (e.g., N addition + elevated CO 2 , warming + elevated CO 2 ) on C:N:P stoichiometry were generally weaker than the individual effects of each of these drivers, (iii) additive interactions (i.e., when combined effects are equal to or not significantly different from the sum of individual effects) were more common than synergistic or antagonistic interactions, (iv) C:N:P stoichiometry of soil and soil microbial biomass shows high homeostasis under global change manipulations, and (v) C:N:P responses to global change are strongly affected by ecosystem type, local climate, and experimental conditions. Our study is one of the first to compare individual vs. combined effects of the three global change drivers on terrestrial C:N:P ratios using a large set of data. To further improve our understanding of how ecosystems might respond to future global change, long‐term ecosystem‐scale studies testing multifactor effects on plants and soils are urgently required across different world regions.

Assessing the role of parameter interactions in the sensitivity analysis of a model of peatland dynamics - Quillet, Anne; Frolking, Steve; Garneau, Michelle; Talbot, Julie; Peng, Changhui (Ecological Modelling, 2013)

Methane Fluxes from Alpine Wetlands of Zoige Plateau in Relation to Water Regime and Vegetation under Two Scales - Chen, Huai; Wu, Ning; Wang, Yanfen; Gao, Yongheng; Peng, Changhui (Water, Air, & Soil Pollution, 2011)

Well Water Quality and Public Health Implications: the Case of Four Neighbourhoods of the City of Douala Cameroon - Epule, Terence Epule; Peng, Changhui; Mirielle Wase, Moto; Mafany, Ndiva Mongoh (Global Journal of Health Science, 2011)

Quantification of provincial-level carbon emissions from energy consumption in China - Geng, Yuhuan; Tian, Mingzhong; Zhu, Qiuan; Zhang, Jianjun; Peng, Changhui (Renewable and Sustainable Energy Reviews, 2011)

Soil respiration dynamics in Cinnamomum camphora forest and a nearby Liquidambar formosana forest in Subtropical China - Tian, DaLun; Wang, GuangJun; Yan, WenDe; Xiang, WenHua; Peng, ChangHui (Chinese Science Bulletin, 2010)

Ecosystem service value assessment for constructed wetlands: A case study in Hangzhou, China - Yang, Wu; Chang, Jie; Xu, Bin; Peng, Changhui; Ge, Ying (Ecological Economics, 2008)

Micrometeorological measurements of nitrous oxide exchange above a cropland - Li, Jun; Tong, Xiaojuan; Yu, Qiang; Dong, Yunshe; Peng, Changhui (Atmospheric Environment, 2008)

Dominant factors controlling glacial and interglacial variations in the treeline elevation in tropical Africa - Wu, Haibin; Guiot, Joël; Brewer, Simon; Guo, Zhengtang; Peng, Changhui (Proceedings of the National Academy of Sciences, 2007)
The knowledge of tropical palaeoclimates is crucial for understanding global climate change, because it is a test bench for general circulation models that are ultimately used to predict future global warming. A longstanding issue concerning the last glacial maximum in the tropics is the discrepancy between the decrease in sea-surface temperatures reconstructed from marine proxies and the high-elevation decrease in land temperatures estimated from indicators of treeline elevation. In this study, an improved inverse vegetation modeling approach is used to quantitatively reconstruct palaeoclimate and to estimate the effects of different factors (temperature, precipitation, and atmospheric CO 2 concentration) on changes in treeline elevation based on a set of pollen data covering an altitudinal range from 100 to 3,140 m above sea level in Africa. We show that lowering of the African treeline during the last glacial maximum was primarily triggered by regional drying, especially at upper elevations, and was amplified by decreases in atmospheric CO 2 concentration and perhaps temperature. This contrasts with scenarios for the Holocene and future climates, in which the increase in treeline elevation will be dominated by temperature. Our results suggest that previous temperature changes inferred from tropical treeline shifts may have been overestimated for low-CO 2 glacial periods, because the limiting factors that control changes in treeline elevation differ between glacial and interglacial periods.

Patterns of fish species richness in China's lakes - Zhao, Shuqing; Fang, Jingyun; Peng, Changhui; Tang, Zhiyao; Piao, Shilong (Global Ecology and Biogeography, 2006)
ABSTRACT Aim To document the patterns of fish species richness and their possible causes in China's lakes at regional and national scales. Location Lakes across China. Methods We compiled data of fish species richness, limnological characteristics and climatic variables for 109 lakes across five regions of China: East region, Northeast region, Southwest region, North‐Northwest region, and the Tibetan Plateau. Correlation analyses, regression models and a general linear model were used to explore the patterns of fish species richness. Results At the national scale, lake altitude, energy availability (potential evapotranspiration, PET) and lake area explained 79.6% of the total variation of the lake fish species richness. The determinants of the fish richness pattern varied among physiographic regions. Lake area was the strongest predictor of fish species richness in the East and Southwest lakes, accounting for 22.2% and 82.9% of the variation, respectively. Annual PET explained 68.7% of the variation of fish richness in the Northeast lakes. Maximum depth, mineralization degree, and lake area explained 45.5% of the fish variation in the lakes of the North‐Northwest region. On the Tibetan Plateau, lake altitude was the first predictor variable, interpreting 32.2% of the variation. Main conclusions Lake altitude was the most important factor explaining the variation of fish species richness across China's lakes, and accounted for 74.5% of the variation. This may stem in part from the fact that the lakes investigated in our study span the largest altitudinal range anywhere in the world. The effects of the lake altitude on fish species richness can be separated into direct and indirect aspects due to its collinearity with PET. We also found that the fish diversity and its determinants were scale‐dependent. Fish species richness was probably energy‐determined in the cold region, while it was best predicted by the lake area in the relatively geologically old region. The independent variables we used only explained a small fraction of the variations in the lake fish species richness in East China and the Tibetan Plateau, which may be due to the effects of human activity and historical events, respectively.

The response of the net primary production of Moso bamboo forest to the On and Off-year management: A case study in Anji County, Zhejiang, China - Chen, Shulin; Jiang, Hong; Cai, Zhijian; Zhou, Xiaolu; Peng, Changhui (Forest Ecology and Management, 2018)

Soil-atmosphere exchange of carbon dioxide, methane and nitrous oxide in temperate forests along an elevation gradient in the Qinling Mountains, China - Pang, Junzhu; Peng, Changhui; Wang, Xiaoke; Zhang, Hongxing; Zhang, Shuoxin (Plant and Soil, 2023)

Can forest carbon sequestration offset industrial CO2 emissions? A case study of Hubei Province, China - Cheng, Jing; Huang, Chunbo; Gan, Xintao; Peng, Changhui; Deng, Lei (Journal of Cleaner Production, 2023)

Stoichiometric and nutrient resorption characteristics of dominant tree species in subtropical Chinese forests - Zeng, Yelin; Fang, Xi; Xiang, Wenhua; Deng, Xiangwen; Peng, Changhui (Ecology and Evolution, 2017)
Abstract This study investigated seasonal patterns in stoichiometric ratios, nutrient resorption characteristics, and nutrient use strategies of dominant tree species at three successional stages in subtropical China, which have not been fully understood. Fresh leaf and leaf litterfall samples were collected in growing and nongrowing seasons for determining the concentrations of carbon (C), nitrogen (N), and phosphorus (P). Then, stoichiometric ratios (i.e., C:N, C:P, N:P, and C:N:P) and resorption parameters were calculated. Our results found that there was no consistent variation in leaf C:N and C:P ratios among different species. However, leaf N:P ratios in late‐successional species became significantly higher, indicating that P limitation increases during successional development. Due to the P limitation in this study area, P resorption efficiency and proficiency were higher than corresponding N resorption parameters. Dominant tree species at early‐successional stage adopted “conservative consumption” nutrient use strategy, whereas the species at late‐successional stage inclined to adopt “resource spending” strategy.

Observed high and persistent carbon uptake by Moso bamboo forests and its response to environmental drivers - Song, Xinzhang; Chen, Xiaofeng; Zhou, Guomo; Jiang, Hong; Peng, Changhui (Agricultural and Forest Meteorology, 2017)

From plant functional types to plant functional traits: A new paradigm in modelling global vegetation dynamics - Yang, Yanzheng; Zhu, Qiuan; Peng, Changhui; Wang, Han; Chen, Huai (Progress in Physical Geography: Earth and Environment, 2015)
Dynamic global vegetation models (DGVMs) typically track the material and energy cycles in ecosystems with finite plant functional types (PFTs). Increasingly, the community ecology and modelling studies recognize that current PFT scheme is not sufficient for simulating ecological processes. Recent advances in the study of plant functional traits (FTs) in community ecology provide a novel and feasible approach for the improvement of PFT-based DGVMs. This paper reviews the development of current DGVMs over recent decades. After characterizing the advantages and disadvantages of the PFT-based scheme, it summarizes trait-based theories and discusses the possibility of incorporating FTs into DGVMs. More importantly, this paper summarizes three strategies for constructing next-generation DGVMs with FTs. Finally, the method’s limitations, current challenges and future research directions for FT theory are discussed for FT theory. We strongly recommend the inclusion of several FTs, namely specific leaf area (SLA), leaf nitrogen content (LNC), carbon isotope composition of leaves (Leaf δ 13 C), the ratio between leaf-internal and ambient mole fractions of CO 2 (Leaf C i /C a ), seed mass and plant height. These are identified as the most important in constructing DGVMs based on FTs, which are also recognized as important ecological strategies for plants. The integration of FTs into dynamic vegetation models is a critical step towards improving the results of DGVM simulations; communication and cooperation among ecologists and modellers is equally important for the development of the next generation of DGVMs.

Insect‐induced tree mortality of boreal forests in eastern Canada under a changing climate - Zhang, Xiongqing; Lei, Yuancai; Ma, Zhihai; Kneeshaw, Dan; Peng, Changhui (Ecology and Evolution, 2014)
Abstract Forest insects are major disturbances that induce tree mortality in eastern coniferous (or fir‐spruce) forests in eastern North America. The spruce budworm ( SBW ) ( Choristoneura fumiferana [Clemens]) is the most devastating insect causing tree mortality. However, the relative importance of insect‐caused mortality versus tree mortality caused by other agents and how this relationship will change with climate change is not known. Based on permanent sample plots across eastern Canada, we combined a logistic model with a negative model to estimate tree mortality. The results showed that tree mortality increased mainly due to forest insects. The mean difference in annual tree mortality between plots disturbed by insects and those without insect disturbance was 0.0680 per year ( P < 0.0001, T ‐test), and the carbon sink loss was about 2.87t C ha −1 year −1 larger than in natural forests. We also found that annual tree mortality increased significantly with the annual climate moisture index ( CMI ) and decreased significantly with annual minimum temperature ( T min ), annual mean temperature ( T mean ) and the number of degree days below 0°C ( DD 0), which was inconsistent with previous studies (Adams et al. ; van Mantgem et al. ; Allen et al. ). Furthermore, the results for the trends in the magnitude of forest insect outbreaks were consistent with those of climate factors for annual tree mortality. Our results demonstrate that forest insects are the dominant cause of the tree mortality in eastern Canada but that tree mortality induced by insect outbreaks will decrease in eastern Canada under warming climate.

Chinese Grain for Green Program led to highly increased soil organic carbon levels: A meta-analysis - Song, Xinzhang; Peng, Changhui; Zhou, Guomo; Jiang, Hong; Wang, Weifeng (Scientific Reports, 2014)

Effects of vegetation restoration on soil nutrients, plant diversity, and its spatiotemporal heterogeneity in a desert–oasis ecotone - Wu, Chunyan; Deng, Lei; Huang, Chunbo; Chen, Yongfu; Peng, Changhui (Land Degradation & Development, 2021)
Abstract Vegetation restoration has been proposed as an effective measure for rehabilitating degraded land and slowing desertification in arid regions. However, the spatial variation in soil quality and plant diversity following vegetation restoration remains unclear. This study was designed to explore soil nutrient dynamics and how soil nutrients affect plant diversity and spatial heterogeneity after shrub restoration. We assessed the effect of Haloxylon ammodendron (C.A.Mey.) Bunge (which has been planted over 30 years) on the soil nutrients and plant diversity in a desert–oasis ecotone in Minqin County, Gansu, China, using geostatistics, beta diversity and rarefaction analyses, and Hill number extrapolation. Soil nutrients, including soil organic matter, total nitrogen, and alkali nitrogen, increased significantly after H. ammodendron planting. Species richness gradually increased from 1–5 years to 10–20 years after H. ammodendron was planted but then decreased at 20–30 years. The largest differences in plant composition were observed at 15 and 20 years. Plant diversity increased in the whole 30 years after shrub planting, increasing in the first 25 years and then decreasing at 26–30 year stage. The maximum coefficient of determination for the spatial heterogeneity model fit was 0.84 (25 years). The spatial heterogeneity in vegetation decreased with increasing soil available K content at 1–10 years. Our results suggest that planting shrubs can improve soil conditions and plant species diversity in desert–oasis ecotones and soil nutrients have a strong influence on plant diversity patterns and spatial heterogeneity following vegetation restoration.

Nitrogen addition decreases methane uptake caused by methanotroph and methanogen imbalances in a Moso bamboo forest - Li, Quan; Peng, Changhui; Zhang, Junbo; Li, Yongfu; Song, Xinzhang (Scientific Reports, 2021)
Abstract Forest soils play an important role in controlling global warming by reducing atmospheric methane (CH 4 ) concentrations. However, little attention has been paid to how nitrogen (N) deposition may alter microorganism communities that are related to the CH 4 cycle or CH 4 oxidation in subtropical forest soils. We investigated the effects of N addition (0, 30, 60, or 90 kg N ha −1 yr −1 ) on soil CH 4 flux and methanotroph and methanogen abundance, diversity, and community structure in a Moso bamboo ( Phyllostachys edulis ) forest in subtropical China. N addition significantly increased methanogen abundance but reduced both methanotroph and methanogen diversity. Methanotroph and methanogen community structures under the N deposition treatments were significantly different from those of the control. In N deposition treatments, the relative abundance of Methanoculleus was significantly lower than that in the control. Soil pH was the key factor regulating the changes in methanotroph and methanogen diversity and community structure. The CH 4 emission rate increased with N addition and was negatively correlated with both methanotroph and methanogen diversity but positively correlated with methanogen abundance. Overall, our results suggested that N deposition can suppress CH 4 uptake by altering methanotroph and methanogen abundance, diversity, and community structure in subtropical Moso bamboo forest soils.

The Characteristics and Seasonal Variation of Methane Fluxes From an Alpine Wetland in the Qinghai Lake watershed, China - Wu, Fangtao; Cao, Shengkui; Cao, Guangchao; Chen, Kelong; Peng, Changhui (Wetlands, 2021)

Evaluating soil nutrients of Dacrydium pectinatum in China using machine learning techniques - Wu, Chunyan; Chen, Yongfu; Hong, Xiaojiang; Liu, Zelin; Peng, Changhui (Forest Ecosystems, 2020)
Abstract Background The accurate estimation of soil nutrient content is particularly important in view of its impact on plant growth and forest regeneration. In order to investigate soil nutrient content and quality for the natural regeneration of Dacrydium pectinatum communities in China, designing advanced and accurate estimation methods is necessary. Methods This study uses machine learning techniques created a series of comprehensive and novel models from which to evaluate soil nutrient content. Soil nutrient evaluation methods were built by using six support vector machines and four artificial neural networks. Results The generalized regression neural network model was the best artificial neural network evaluation model with the smallest root mean square error (5.1), mean error (− 0.85), and mean square prediction error (29). The accuracy rate of the combined k -nearest neighbors ( k -NN) local support vector machines model (i.e. k -nearest neighbors -support vector machine (KNNSVM)) for soil nutrient evaluation was high, comparing to the other five partial support vector machines models investigated. The area under curve value of generalized regression neural network (0.6572) was the highest, and the cross-validation result showed that the generalized regression neural network reached 92.5%. Conclusions Both the KNNSVM and generalized regression neural network models can be effectively used to evaluate soil nutrient content and quality grades in conjunction with appropriate model variables. Developing a new feasible evaluation method to assess soil nutrient quality for Dacrydium pectinatum , results from this study can be used as a reference for the adaptive management of rare and endangered tree species. This study, however, found some uncertainties in data acquisition and model simulations, which will be investigated in upcoming studies.

Assessment of biomass utilization potential of Caragana korshinskii and its effect on carbon sequestration on the Northern Shaanxi Loess Plateau, China - Liu, Weiguo; Yu, Zhen; Zhu, Qiuan; Zhou, Xiaolu; Peng, Changhui (Land Degradation & Development, 2020)
Abstract Biomass has been promoted as a promising energy resource to mitigate global climate change. To evaluate the contribution of biomass utilization to climate change mitigation under the “Grain for Green” program in Northern Shaanxi, China, a soil carbon dynamic model and a life cycle assessment model were integrated to examine the benefits of using Caragana korshinskii Kom. as an energy crop. We found that the annual dry biomass output is maintained at 0.7 Tg during the simulation period (2020–2097). Due to the compensatory effect of biomass regrowth, the global warming potential of biomass‐derived CO 2 emissions is approximately 0.045; therefore, the total annual biogenic CO 2 emission is 57,211 ± 6,168 Mg CO 2 eq. The total annual life cycle CO 2 emissions approach 867,072 Mg CO 2 eq yr −1 . Under the scenario of no biomass removal, final carbon storage ranges from 15.7 to 19.3 TgC, and the highest carbon sequestration rate is 0.47 TgC yr −1 . In comparison with the no biomass removal scenario, the carbon sequestration rate (close to 0 MgC yr −1 ) in the biomass utilization scenario indicates a carbon loss; however, a portion of the carbon loss (31.39–62.09%) can be offset by carbon emission reductions from the substitution of fossil fuels.

The Vertical Differences in the Change Rates and Controlling Factors of Soil Organic Carbon and Total Nitrogen along Vegetation Restoration in a Subtropical Area of China - Cao, Zhiwei; Fang, Xi; Xiang, Wenhua; Lei, Pifeng; Peng, Changhui (Sustainability, 2020)
The study was to investigate the change patterns of soil organic carbon (SOC), total nitrogen (TN), and soil C/N (C/N) in each soil sublayer along vegetation restoration in subtropical China. We collected soil samples in four typical plant communities along a restoration chronosequence. The soil physicochemical properties, fine root, and litter biomass were measured. Our results showed the proportion of SOC stocks (Cs) and TN stocks (Ns) in 20–30 and 30–40 cm soil layers increased, whereas that in 0–10 and 10–20 cm soil layers decreased. Different but well-constrained C/N was found among four restoration stages in each soil sublayer. The effect of soil factors was greater on the deep soil than the surface soil, while the effect of vegetation factors was just the opposite. Our study indicated that vegetation restoration promoted the uniform distribution of SOC and TN on the soil profile. The C/N was relatively stable along vegetation restoration in each soil layer. The accumulation of SOC and TN in the surface soil layer was controlled more by vegetation factors, while that in the lower layer was controlled by both vegetation factors and soil factors.

Warming‐induced global soil carbon loss attenuated by downward carbon movement - Luo, Zhongkui; Luo, Yiqi; Wang, Guocheng; Xia, Jianyang; Peng, Changhui (Global Change Biology, 2020)
Abstract The fate of soil organic carbon (SOC) under warming is poorly understood, particularly across large extents and in the whole‐soil profile. Using a data‐model integration approach applied across the globe, we find that downward movement of SOC along the soil profile reduces SOC loss under warming. We predict that global SOC stocks (down to 2 m) will decline by 4% (~80 Pg) on average when SOC reaches the steady state under 2°C warming, assuming no changes in net primary productivity (NPP). To compensate such decline (i.e. maintain current SOC stocks), a 3% increase of NPP is required. Without the downward SOC movement, global SOC declines by 15%, while a 20% increase in NPP is needed to compensate that loss. This vital role of downward SOC movement in controlling whole‐soil profile SOC dynamics in response to warming is due to the protection afforded to downward‐moving SOC by depth, indicated by much longer residence times of SOC in deeper layers. Additionally, we find that this protection could not be counteracted by promoted decomposition due to the priming of downward‐moving new SOC from upper layers on native old SOC in deeper layers. This study provides the first estimation of whole‐soil SOC changes under warming and additional NPP required to compensate such changes across the globe, and reveals the vital role of downward movement of SOC in reducing SOC loss under global warming.

Modeling and estimating aboveground biomass of Dacrydium pierrei in China using machine learning with climate change - Wu, Chunyan; Chen, Yongfu; Peng, Changhui; Li, Zhaochen; Hong, Xiaojiang (Journal of Environmental Management, 2019)

How is biodiversity changing in response to ecological restoration in terrestrial ecosystems? A meta-analysis in China - Huang, Chunbo; Zhou, Zhixiang; Peng, Changhui; Teng, Mingjun; Wang, Pengcheng (Science of The Total Environment, 2019)

Factors Affecting the Spatial and Temporal Variations in Soil Erodibility of China - Zhu, Guangyu; Tang, Zhuangsheng; Shangguan, Zhouping; Peng, Changhui; Deng, Lei (Journal of Geophysical Research: Earth Surface, 2019)
Abstract Soil erosion occurs extensively across China, leading to severe degradation of the land and ecosystem services. However, the spatial and temporal variations in soil erodibility ( k ) and the distribution of soil erosion across land use types and slopes remain unclear. We synthesized the results from 325 sites published in 152 literatures to analyze the factors affecting the k , such as land use type, climate, topography, soil, and vegetation restoration age. The results showed that areas with slopes >25° had a larger k factor ( k = 0.1047) than did those with slope <6° ( k = 0.0637) or 6–25° ( k = 0.0832). The k from 2006 to 2011 ( k = 0.0725) was higher than that from 1999 to 2005 ( k = 0.058) and that from 2012 to 2016 ( k = 0.0631). The k value initially increased with vegetation restoration age and then gradually decreased. Land use also had an impact on the k factor, with the k factor of cropland ( k = 0.0697) being higher than that of grassland ( k = 0.0663) but lower than that of forest ( k = 0.0967). Across China, North Shaanxi, Heilongjiang, and South Guizhou, which are located in the Loess Plateau in Northwest China, the Black Soil region of Northeast China, and the Karst areas in Southwest China, respectively, were the three most severely eroded regions due to hydraulic erosion, frost‐thaw erosion, and high‐intensity erosion, respectively. Overall, the most important factors affecting the k were soil characteristics, followed by topography and climate. Among them, soil nitrogen and precipitation were the two most critical factors influencing the k . , Key Points Grassland had lower soil erodibility than had cropland and forestland North Shaanxi, Heilongjiang, and South Guizhou were the three most severely eroded regions Precipitation and soil N play critical roles in controlling soil erosion

Stand carbon density drivers and changes under future climate scenarios across global forests - Guo, Yanrong; Peng, Changhui; Trancoso, Ralph; Zhu, Qiuan; Zhou, Xiaolu (Forest Ecology and Management, 2019)

Developing and Evaluating Tree Height-Diameter Models at Three Geographic Scales for Black Spruce in Ontario - Peng, Changhui; Zhang, Lianjun; Zhou, Xiaolu; Dang, Qinglai; Huang, Shongming (Northern Journal of Applied Forestry, 2004)
Abstract A total of 11,612 black spruce trees were measured from permanent sample plots across the boreal and central regions of Ontario and were used to fit the well-known Chapman-Richards growth model at provincial, regional, and ecoregional scales. The results suggest that the height-diameter relationships of black spruce vary with different geographic regions and scales. There were significant variations in height-diameter relationships for black spruce between boreal and central regions as well as among some of the seven ecoregions. The ecoregion-based height-diameter models presented here will provide more accurate predictions for tree height and, consequently, tree volume than these models developed at both provincial and regional scales. Furthermore, the heterogeneity of tree species should be considered in developing and applying ecoregion-based height-diameter models for predicting local tree height.

A component object model strategy for reusing ecosystem models - Liu, Jinxun; Peng, Changhui; Dang, Qinglai; Apps, Mike; Jiang, Hong (Computers and Electronics in Agriculture, 2002)

Changes in Forest Biomass Carbon Storage in China Between 1949 and 1998 - Fang, Jingyun; Chen, Anping; Peng, Changhui; Zhao, Shuqing; Ci, Longjun (Science, 2001)
The location and mechanisms responsible for the carbon sink in northern mid-latitude lands are uncertain. Here, we used an improved estimation method of forest biomass and a 50-year national forest resource inventory in China to estimate changes in the storage of living biomass between 1949 and 1998. Our results suggest that Chinese forests released about 0.68 petagram of carbon between 1949 and 1980, for an annual emission rate of 0.022 petagram of carbon. Carbon storage increased significantly after the late 1970s from 4.38 to 4.75 petagram of carbon by 1998, for a mean accumulation rate of 0.021 petagram of carbon per year, mainly due to forest expansion and regrowth. Since the mid-1970s, planted forests (afforestation and reforestation) have sequestered 0.45 petagram of carbon, and their average carbon density increased from 15.3 to 31.1 megagrams per hectare, while natural forests have lost an additional 0.14 petagram of carbon, suggesting that carbon sequestration through forest management practices addressed in the Kyoto Protocol could help offset industrial carbon dioxide emissions.

Interannual Variability in Net Primary Production and Precipitation - Fang, Jingyun; Piao, Shilong; Tang, Zhiyao; Peng, Changhui; Ji, Wei (Science, 2001)

Developing carbon-based ecological indicators to monitor sustainability of Ontario’s forests - Peng, Changhui; Liu, Jinxun; Dang, Qinglai; Zhou, Xiaolu; Apps, Mike (Ecological Indicators, 2002)

Application of machine learning methods for paleoclimatic reconstructions from leaf traits - Wei, Gang; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Yang, Bin (International Journal of Climatology, 2021)
Abstract Digital leaf physiognomy (DLP) is considered as one of the most promising methods for estimating past climate. However, current models built using the DLP data set still lack precision, especially for mean annual precipitation (MAP). To improve predictive power, we developed five machine learning (ML) models for mean annual temperature (MAT) and MAP respectively, and then tested the precision of these models and some of their averaging compared with that obtained from other models. The precision of all models was assessed using a repeated stratified 10‐fold cross‐validation. For MAT, three combinations of models ( R 2 = .77) presented moderate improvements in precision over the multiple linear regression (MLR) model ( R 2 = .68). For log e (MAP), the averaging of the support vector machine (SVM) and boosting models improved the R 2 from .19 to .63 compared with that of the MLR model. For MAP, the R 2 of this model combination was 0.49, which was much better than that of the artificial neural network (ANN) model ( R 2 = .21). Even the bagging model, which had the lowest R 2 (.37) for log e (MAP), demonstrated better precision ( R 2 = .27) for MAP. Our palaeoclimate estimates for nine fossil floras were also more accurate, because they were in better agreement with independent paleoclimate evidence. Our study confirms that our ML models and their averaging can improve paleoclimatic reconstructions, providing a better understanding of the relationship between climate and leaf physiognomy.

Contribution of the Order Ericales to Improving Paleoclimate Reconstructions - Wei, Gang; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Liu, Weiguo (Sustainability, 2022)
Paleobotanists have long built leaf climate models based on site mean of leaf physiognomic characteristics of woody dicotyledons species (WDS) for estimating past climate. To explore the potential of the order Ericales in estimating paleoclimate, we developed two linear models for each climatic factor. One is based on WDS, and the other is based on both WDS and leaf physiognomic characters of the order Ericales (WDS-E). We found that, compared with WDS models, WDS-E models improved greatly in mean annual precipitation (MAP), growing season precipitation (GSP) and mean annual range in temperature (MART). When the minimum species number of the order Ericales is three per site, the WDS-E models improved the r2 from 0.64 to 0.78 for MART, from 0.23 to 0.61 for ln(MAP), and from 0.37 to 0.64 for ln(GSP) compared with the WDS models. For mean annual temperature (MAT), the WDS-E model (r2 = 0.86) also exhibited a moderate improvement in precision over the WDS model (r2 = 0.82). This study demonstrates that other patterns, such as those of the order Ericales, can contribute additional information towards building more precise paleoclimate models.

The effects of environmental factors and plant diversity on forest carbon sequestration vary between eastern and western regions of China - Chen, Kexin; Li, Tong; Yang, Mingxia; Zhou, Xiaolu; Peng, Changhui (Journal of Cleaner Production, 2024)

Integrating models with data in ecology and palaeoecology: advances towards a model-data fusion approach: Model-data fusion in ecology - Peng, Changhui; Guiot, Joel; Wu, Haibin; Jiang, Hong; Luo, Yiqi (Ecology Letters, 2011)

Soil CH4 and CO2 dynamics and nitrogen transformations with incubation in mountain forest and meadow ecosystems - Zhang, Junjun; Peng, Changhui; Xue, Wei; Yang, Zhenan; Yang, Bin; Li, Peng; Zhu, Qiuan; Wang, Meng (CATENA, 2018)

Grazing alters vegetation phenology by regulating regional environmental factors on the Tibetan Plateau - Wang, Longjun; Li, Peng; Li, Tong; Zhou, Xiaolu; Liu, Zelin; Zou, Ziying; Zhu, Qiuan; Peng, Changhui (Agriculture, Ecosystems & Environment, 2023)

Application of climate change scenarios in the simulation of forest ecosystems: an overview - Liu, Haoyun; Li, Peng; Peng, Changhui; Liu, Cong; Zhou, Xiaolu; Deng, Zhengmiao; Zhang, Cicheng; Liu, Zelin (Environmental Reviews, 2023)
Climate change scenarios established by the Intergovernmental Panel on Climate Change have developed a significant tool for analyzing, modeling, and predicting future climate change impacts in different research fields after more than 30 years of development and refinement. In the wake of future climate change, the changes in forest structure and functions have become a frontier and focal area of global change research. This study mainly reviews and synthesizes climate change scenarios and their applications in forest ecosystem research over the past decade. These applications include changes in (1) forest structure and spatial vegetation distribution, (2) ecosystem structure, (3) ecosystem services, and (4) ecosystem stability. Although climate change scenarios are useful for predicting future climate change impacts on forest ecosystems, the accuracy of model simulations needs to be further improved. Based on existing studies, climate change scenarios are used in future simulation applications to construct a biomonitoring network platform integrating observations and predictions for better conservation of species diversity.

Foliar litter decomposition in an alpine forest meta-ecosystem on the eastern Tibetan Plateau - Yue, Kai; Yang, Wanqin; Peng, Changhui; Peng, Yan; Zhang, Chuan; Huang, Chunping; Tan, Yu; Wu, Fuzhong (Science of The Total Environment, 2016)

Combined control of multiple extreme climate stressors on autumn vegetation phenology on the Tibetan Plateau under past and future climate change - Li, Peng; Liu, Zelin; Zhou, Xiaolu; Xie, Binggeng; Li, Zhongwu; Luo, Yunpeng; Zhu, Qiuan; Peng, Changhui (Agricultural and Forest Meteorology, 2021)

Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China - Ren, Peixin; Liu, Zelin; Zhou, Xiaolu; Peng, Changhui; Xiao, Jingfeng; Wang, Songhan; Li, Xing; Li, Peng (Forest Ecosystems, 2021)
Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGS sif and EGS evi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

Change in Autumn Vegetation Phenology and the Climate Controls From 1982 to 2012 on the Qinghai–Tibet Plateau - Li, Peng; Zhu, Qiuan; Peng, Changhui; Zhang, Jing; Wang, Meng; Zhang, Junjun; Ding, Juhua; Zhou, Xiaolu (Frontiers in Plant Science, 2020)

Variation in Soil Methane Fluxes and Comparison between Two Forests in China - Wei, Hua; Peng, Changhui; Liu, Shirong; Liu, Xiaojing; Li, Peng; Song, Hanxiong; Yuan, Minshu; Wang, Meng (Forests, 2018)
Methane (CH4) is a vital greenhouse gas with a 28-fold higher global warming potential than carbon dioxide when considering a molar basis for the time horizon of 100 years. Here, we investigated the variation of soil CH4 fluxes, soil physiochemical properties, and CH4-related bacteria community composition of two forests in China. We measured CH4 fluxes using static chambers and analyzed soil bacterial communities using next-generation high-throughput sequencing in a temperate broad-leaved deciduous forest at Baotianman Nature Reserve (TBDF-BTM) and a tropical rainforest at Jianfengling National Natural Reserve (TRF-JFL). Our results showed that the soils from both sites were CH4 sinks. Significant variation in soil CH4 fluxes was found at TBDF-BTM exclusively, while no seasonal variation in the CH4 uptake was observed at TRF-JFL. The CH4 fluxes at TBDF-BTM were substantially higher than those at TRF-JFL during all seasons. One genus of methanotrophs and three genera of methylotrophs were detected at both sites, though they had no direct relationship with soil CH4 fluxes. Water-filled pore space and soil total carbon content are the main factors controlling the soil CH4 fluxes at TBDF-BTM. At TRF-JFL, the soil CH4 fluxes showed no significant correlations with any of the soil properties. This study improves our understanding of soil CH4 fluxes and their influencing factors in forests in different climatic zones and provides a reference for future investigation of forest soil CH4 fluxes, the forest ecosystem carbon cycle, and the forest CH4 model.

Positive Relationship between Aboveground Carbon Stocks and Structural Diversity in Spruce-Dominated Forest Stands in New Brunswick, Canada - Wang, Weifeng; Lei, Xiangdong; Ma, Zhihai; Kneeshaw, Daniel D.; Peng, Changhui (Forest Science, 2011)
Abstract Maintaining both the structure and functionality of forest ecosystems is a primary goal of forest management. In this study, relationships between structural diversity and aboveground stand carbon (C) stocks were examined in spruce-dominated forests in New Brunswick, Canada. Tree species, size, and height diversity indices as well as a combination of these diversity indices were used to correlate aboveground C stocks. Multiple linear regressions were subsequently used to quantify the relationships between these indices and aboveground C stocks, and partial correlation analysis was also adopted to remove the effects of other explanatory variables. Results show that stand structural diversity has a significant positive effect on aboveground C stocks even though the relationship is weak overall. Positive relationships observed between the diversity indices and aboveground C stocks support the hypothesis that increased structural diversity enhances aboveground C storage capacity. This occurs because complex forest structures allow for greater light infiltration and promote a more efficient resource use by trees, leading to an increase in biomass and C production. Mixed tolerant species composition and uneven-aged stand management in conjunction with selection or partial cutting to maintain high structural diversity is therefore recommended to preserve biodiversity and C stocks in spruce-dominated forests.

A Simulation of Temporal and Spatial Variations in Carbon at Landscape Level: A Case Study for Lake Abitibi Model Forest in Ontario, Canada - Zhou, Xiaolu; Peng, Changhui; Dang, Qing-Lai; Chen, Jiaxin; Parton, Sue (Mitigation and Adaptation Strategies for Global Change, 2007)

Identifying maize yield and precipitation gaps in Uganda - Epule, Terence Epule; Dhiba, Driss; Etongo, Daniel; Peng, Changhui; Lepage, Laurent (SN Applied Sciences, 2021)
Abstract In sub-Saharan Africa (SSA), precipitation is an important driver of agricultural production. In Uganda, maize production is essentially rain-fed. However, due to changes in climate, projected maize yield targets have not often been met as actual observed maize yields are often below simulated/projected yields. This outcome has often been attributed to parallel gaps in precipitation. This study aims at identifying maize yield and precipitation gaps in Uganda for the period 1998–2017. Time series historical actual observed maize yield data (hg/ha/year) for the period 1998–2017 were collected from FAOSTAT. Actual observed maize growing season precipitation data were also collected from the climate portal of World Bank Group for the period 1998–2017. The simulated or projected maize yield data and the simulated or projected growing season precipitation data were simulated using a simple linear regression approach. The actual maize yield and actual growing season precipitation data were now compared with the simulated maize yield data and simulated growing season precipitation to establish the yield gaps. The results show that three key periods of maize yield gaps were observed (period one: 1998, period two: 2004–2007 and period three: 2015–2017) with parallel precipitation gaps. However, in the entire series (1998–2017), the years 2008–2009 had no yield gaps yet, precipitation gaps were observed. This implies that precipitation is not the only driver of maize yields in Uganda. In fact, this is supported by a low correlation between precipitation gaps and maize yield gaps of about 6.3%. For a better understanding of cropping systems in SSA, other potential drivers of maize yield gaps in Uganda such as soils, farm inputs, crop pests and diseases, high yielding varieties, literacy, and poverty levels should be considered.

A critical analysis of the carbon neutrality assumption in life cycle assessment of forest bioenergy systems - Liu, Weiguo; Yu, Zhen; Xie, Xinfeng; Von Gadow, Klaus; Peng, Changhui (Environmental Reviews, 2018)
This study presents a critical analysis regarding the assumption of carbon neutrality in life cycle assessment (LCA) models that assess climate change impacts of bioenergy usage. We identified a complex of problems in the carbon neutrality assumption, especially regarding bioenergy derived from forest residues. In this study, we summarized several issues related to carbon neutral assumptions, with particular emphasis on possible carbon accounting errors at the product level. We analyzed errors in estimating emissions in the supply chain, direct and indirect emissions due to forest residue extraction, biogenic CO 2 emission from biomass combustion for energy, and other effects related to forest residue extraction. Various modeling approaches are discussed in detail. We concluded that there is a need to correct accounting errors when estimating climate change impacts and proposed possible remedies. To accurately assess climate change impacts of bioenergy use, greater efforts are required to improve forest carbon cycle modeling, especially to identify and correct pitfalls associated with LCA accounting, forest residue extraction effects on forest fire risk and biodiversity. Uncertainties in accounting carbon emissions in LCA are also highlighted, and associated risks are discussed.

Predicting forest growth and yield in northeastern Ontario using the process-based model of TRIPLEX1.0 - Zhou, Xiaolu; Peng, Changhui; Dang, Qing-Lai; Chen, Jiaxin; Parton, Sue (Canadian Journal of Forest Research, 2005)
Process-based carbon dynamic models are rarely validated against traditional forest growth and yield data and are difficult to use as a practical tool for forest management. To bridge the gap between empirical and process-based models, a simulation using a hybrid model of TRIPLEX1.0 was performed for the forest growth and yield of the boreal forest ecosystem in the Lake Abitibi Model Forest in northeastern Ontario. The model was tested using field measurements, forest inventory data, and the normal yield table. The model simulations of tree height and diameter at breast height (DBH) showed a good agreement with measurements for black spruce (Picea mariana (Mill.) BSP), jack pine (Pinus banksiana Lamb.), and trembling aspen (Populus tremuloides Michx.). The coefficients of determination (R 2 ) between simulated values and permanent sample plot measurements were 0.92 for height and 0.95 for DBH. At the landscape scale, model predictions were compared with forest inventory data and the normal yield table. The R 2 ranged from 0.73 to 0.89 for tree height and from 0.72 to 0.85 for DBH. The simulated basal area is consistent with the normal yield table. The R 2 for basal area ranged from 0.82 to 0.96 for black spruce, jack pine, and trembling aspen for each site class. This study demonstrated the feasibility of testing the performance of the process-based carbon dynamic model using traditional forest growth and yield data and the ability of the TRIPLEX1.0 model for predicting growth and yield variables. The current work also introduces a means to test model accuracy and its prediction of forest stand variables to provide a complement to empirical growth and yield models for forest management practices, as well as for investigating climate change impacts on forest growth and yield in regions without sufficient established permanent sample plots and remote areas without suitable field measurements.

Modelling the influence of harvesting on Chinese boreal forest carbon dynamics - Jiang, Hong; Apps, Michael J; Peng, Changhui; Zhang, Yanli; Liu, Jinxun (Forest Ecology and Management, 2002)

TRIPLEX: a generic hybrid model for predicting forest growth and carbon and nitrogen dynamics - Peng, Changhui; Liu, Jinxun; Dang, Qinglai; Apps, Michael J; Jiang, Hong (Ecological Modelling, 2002)

Drought-induced tree mortality: ecological consequences, causes, and modeling - Wang, Weifeng; Peng, Changhui; Kneeshaw, Daniel D.; Larocque, Guy R.; Luo, Zhibin (Environmental Reviews, 2012)
Drought-induced tree mortality, which rapidly alters forest ecosystem composition, structure, and function, as well as the feedbacks between the biosphere and climate, has occurred worldwide over the past few decades, and is expected to increase pervasively as climate change progresses. The objectives of this review are to (1) highlight the likely ecological consequences of drought-induced tree mortality, (2) synthesize the hypotheses related to drought-induced tree mortality, (3) discuss the implications of current knowledge for modeling tree mortality processes under climate change, and (4) highlight future research needs. First, we emphasize the likely ecological consequences of tree mortality from ecosystem to biome to continental scales. We then document and criticize multiple non-exclusive tree mortality hypotheses (e.g., carbon starvation — carbon supply is less than carbon demand; and hydraulic failure — desiccation from failed water transport) from a more comprehensive ecological perspective. Next, we extend a forest decline concept model, Manion’s framework, by considering new emerging environmental conditions, for a more thorough understanding of the effects of climate change on forest decline. We find that an increase in drought frequency and (or) climate-change-type droughts may trigger increased background tree mortality rates and severe forest dieback events, accelerating species turnover and ecological regime shifts. The contribution of CO 2 fertilization, rising temperature within the optimal growth range, and increased nitrogen deposition may defer or reduce this trend in tree mortality, but such contributions will vary between locations, species, and tree sizes. Multiple hypotheses proposed for drought-induced tree mortality are discussed, but coupling carbon and water cycles could help resolve the debate. The absence of a physiological understanding of tree mortality mechanisms limits the predictive ability of current models from stand-level process-based models to dynamic global vegetation models. We thus suggest that long-term observations, experiments, and models should be tightly interwoven during the research process to better forecast future climate changes and evaluate their impacts on forests.

African climate change policy performance index - Epule, Terence Epule; Chehbouni, Abdelghani; Dhiba, Driss; Moto, Mirielle Wase; Peng, Changhui (Environmental and Sustainability Indicators, 2021)

The long-term impact of urbanization on nitrogen patterns and dynamics in Shanghai, China - Gu, Baojing; Dong, Xiaoli; Peng, Changhui; Luo, Weidong; Chang, Jie; Ge, Ying (Environmental Pollution, 2012)

Application of artificial neural networks in global climate change and ecological research: An overview - Liu, ZeLin; Peng, ChangHui; Xiang, WenHua; Tian, DaLun; Deng, XiangWen; Zhao, MeiFang (Chinese Science Bulletin, 2010)

Growth and structure development of semi-natural larch-spruce-fir (Larix olgensis–Picea jezoensis–Abies nephrolepis) forests in northeast China: 12-year results after thinning - Lei, Xiangdong; Lu, Yuanchang; Peng, Changhui; Zhang, Xiaopeng; Chang, Jie; Hong, Lingxia (Forest Ecology and Management, 2007)

Land use change in Asia and the ecological consequences - Zhao, Shuqing; Peng, Changhui; Jiang, Hong; Tian, Dalun; Lei, Xiangdong; Zhou, Xiaolu (Ecological Research, 2006)
Abstract Viewed within a historical context, Asia has experienced dramatic land transformations, and currently more than 50% of Asian land area is under agriculture. The consequences of this transformation are manifold. Southeast Asia has the highest deforestation rate of any major tropical region. Many of the world's large rivers and lakes in Asia have been heavily degraded. About 11 of 19 world megacities with more than 10 million inhabitants are in Asia. These land use activities have resulted in substantial negative ecological consequences, including increased anthropogenic CO 2 emissions, deteriorated air and water quality, alteration of regional climate, an increase of disease and a loss of biodiversity. Although land use occurs at the local level, it has the potential to cause ecological impact across local, regional and global scales. Reducing the negative environmental impacts of land use change while maintaining economic viability and social acceptability is an major challenge for most developing countries in Asia.

Large-scale detection of vegetation dynamics and their potential drivers using MODIS images and BFAST: A case study in Quebec, Canada - Fang, Xiuqin; Zhu, Qiuan; Ren, Liliang; Chen, Huai; Wang, Kai; Peng, Changhui (Remote Sensing of Environment, 2018)

Biochar amendment decreases soil microbial biomass and increases bacterial diversity in Moso bamboo ( Phyllostachys edulis ) plantations under simulated nitrogen deposition - Li, Quan; Lei, Zhaofeng; Song, Xinzhang; Zhang, Zhiting; Ying, Yeqing; Peng, Changhui (Environmental Research Letters, 2018)

Eco-CCUS: A cost-effective pathway towards carbon neutrality in China - Li, Mingxu; He, Nianpeng; Xu, Li; Peng, Changhui; Chen, Huai; Yu, Guirui (Renewable and Sustainable Energy Reviews, 2023)

Effects of nitrogen deposition and management practices on leaf litterfall and N and P return in a Moso bamboo forest - Zhang, Junbo; Lv, Jianhua; Li, Quan; Ying, Yeqing; Peng, Changhui; Song, Xinzhang (Biogeochemistry, 2017)

Quantification of methane emissions from municipal solid waste landfills in China during the past decade - Du, Mingxi; Peng, Changhui; Wang, Xiaoge; Chen, Huai; Wang, Meng; Zhu, Qiuan (Renewable and Sustainable Energy Reviews, 2017)

Dynamic allocation and transfer of non-structural carbohydrates, a possible mechanism for the explosive growth of Moso bamboo (Phyllostachys heterocycla) - Song, Xinzhang; Peng, Changhui; Zhou, Guomo; Gu, Honghao; Li, Quan; Zhang, Chao (Scientific Reports, 2016)
Abstract Moso bamboo can rapidly complete its growth in both height and diameter within only 35–40 days after shoot emergence. However, the underlying mechanism for this “explosive growth” remains poorly understood. We investigated the dynamics of non-structural carbohydrates (NSCs) in shoots and attached mature bamboos over a 20-month period. The results showed that Moso bamboos rapidly completed their height and diameter growth within 38 days. At the same time, attached mature bamboos transferred almost all the NSCs of their leaves, branches and especially trunks and rhizomes to the “explosively growing” shoots via underground rhizomes for the structural growth and metabolism of shoots. Approximately 4 months after shoot emergence, this transfer stopped when the leaves of the young bamboos could independently provide enough photoassimilates to meet the carbon demands of the young bamboos. During this period, the NSC content of the leaves, branches, trunks and rhizomes of mature bamboos declined by 1.5, 23, 28 and 5 fold, respectively. The trunk contributed the most NSCs to the shoots. Our findings provide new insight and a possible rational mechanism explaining the “explosive growth” of Moso bamboo and shed new light on understanding the role of NSCs in the rapid growth of Moso bamboo.

Integrating global socio-economic influences into a regional land use change model for China - Xu, Xia; Gao, Qiong; Peng, Changhui; Cui, Xuefeng; Liu, Yinghui; Jiang, Li (Frontiers of Earth Science, 2014)

Admixture of alder (Alnus formosana) litter can improve the decomposition of eucalyptus (Eucalyptus grandis) litter - Wu, Fuzhong; Peng, Changhui; Yang, Wanqin; Zhang, Jian; Han, Yu; Mao, Tao (Soil Biology and Biochemistry, 2014)

Climate Change Contribution to Forest Growth in Eastern China over Past Two Decades - Jin, Jiaxin; Jiang, Hong; Peng, Changhui; Zhang, Xiuying; Wang, Ying; Wang, Jinyin (Terrestrial, Atmospheric and Oceanic Sciences, 2014)

Interactive effects of elevated UV-B radiation and N deposition on decomposition of Moso bamboo litter - Song, Xinzhang; Jiang, Hong; Zhang, Zhiting; Zhou, Guomo; Zhang, Shuikui; Peng, Changhui (Soil Biology and Biochemistry, 2014)

Soil N forms and gross transformation rates in Chinese subtropical forests dominated by different tree species - Zeng, Yelin; Xiang, Wenhua; Deng, Xiangwen; Fang, Xi; Liu, Cong; Peng, Changhui (Plant and Soil, 2014)

An assessment of the predictors of the dynamics in arable production per capita index, arable production and permanent cropland and forest area based on structural equation models - Epule, Epule Terence; Bryant, Christopher Robin; Akkari, Cherine; Sarr, Mamadou Adama; Peng, Changhui (SpringerPlus, 2014)

Direct and Indirect Effects of UV-B Exposure on Litter Decomposition: A Meta-Analysis - Song, Xinzhang; Peng, Changhui; Jiang, Hong; Zhu, Qiuan; Wang, Weifeng (PLoS ONE, 2013)

Nitrogen addition increases CO2, CH4, and N2O concentrations of topsoils and subsoils in a subtropical Moso bamboo forest - Lv, Jianhua; Li, Quan; Zhang, Junbo; Li, Yongfu; Peng, Changhui; Song, Xinzhang (CATENA, 2022)

Climate Change Will Reduce the Carbon Use Efficiency of Terrestrial Ecosystems on the Qinghai-Tibet Plateau: An Analysis Based on Multiple Models - Wang, Yue; Hu, Jinming; Yang, Yanzheng; Li, Ruonan; Peng, Changhui; Zheng, Hua (Forests, 2020)
The carbon use efficiency (CUE) of ecosystems, expressed as the ratio of net primary production (NPP) and gross primary production (GPP), is extremely sensitive to climate change and has a great effect on the carbon cycles of terrestrial ecosystems. Climate change leads to changes in vegetation, resulting in different CUE values, especially on the Qinghai-Tibet Plateau, one of the most climate-sensitive regions in the world. However, the change trend and the intrinsic mechanism of climate effects on CUE in the future climate change scenario are not clear in this region. Based on the scheme of the coupled model intercomparison project (CMIP6), we analyze the simulation results of the five models of the scenario model intercomparison project (ScenarioMIP) under three different typical future climate scenarios, including SSP1-2.6, SSP3-7.0 and SSP5-8.5, on the Qinghai-Tibet Plateau in 2015–2100 with methods of model-averaging to average the long-term forecast of the five several well-known forecast models for three alternative climate scenarios with three radiative forcing levels to discuss the CUE changes and a structural equations modeling (SEM) approach to examine how the trends in GPP, NPP, and CUE related to different climate factors. The results show that (1) GPP and NPP demonstrated an upward trend in a long time series of 86 years, and the upward trend became increasingly substantial with the increase in radiation forcing; (2) the ecosystem CUE of the Qinghai-Tibet Plateau will decrease in the long time series in the future, and it shows a substantial decreasing trend with the increase in radiation forcing; and (3) the dominant climate factor affecting CUE is temperature of the factors included in these models, which affects CUE mainly through GPP and NPP to produce indirect effects. Temperature has a higher comprehensive effect on CUE than precipitation and CO2, which are negative effects on CUE on an annual scale. Our finding that the CUE decreases in the future suggests that we must pay more attention to the vegetation and CUE changes, which will produce great effects on the regional carbon dynamics and balance.

Nitrogen -addition accelerates phosphorus cycling and changes phosphorus use strategy in a subtropical Moso bamboo forest - Li, Quan; Lv, Jianhua; Peng, Changhui; Xiang, Wenhua; Xiao, Wenfa; Song, Xinzhang (Environmental Research Letters, 2021)
Abstract Ecosystem-level effects of increasing atmospheric nitrogen (N) deposition on the phosphorus (P) cycle and P use strategy are poorly understood. Here, we conducted a seven year N-addition experiment to comprehensively evaluate the effects of N deposition on P limitation, cycling, and use strategy in a subtropical Moso bamboo forest. N addition significantly increased foliar litterfall by 4.7%–21.7% and subsequent P return to the soil by 49.0%–70.1%. It also increased soil acidity, acid phosphatase activity, and soil microbial biomass P, which substantially contributed to a significantly increased soil P availability and largely alleviated the P limitation. This resulted in a significant decrease in the foliar P-resorption efficiency and the abundance and colonization of arbuscular mycorrhizal fungi. Our results indicate that N deposition can reduce plant internal cycling while enhancing ecosystem-scale cycling of P in Moso bamboo forests. This suggests a shift in P use from a ‘conservative consumption’ strategy to a ‘resource spending’ strategy. Our findings shed new light on N deposition effects on P cycle processes and P use strategy at the ecosystem scale under increasing atmospheric N deposition.

Quantitative assessment of the importance of bio-physical drivers of land cover change based on a random forest method - Meng, Yanrong; Yang, Mingxia; Liu, Shan; Mou, Yuling; Peng, Changhui; Zhou, Xiaolu (Ecological Informatics, 2021)

Gross Ecosystem Productivity Dominates the Control of Ecosystem Methane Flux in Rice Paddies - Li, Hong; Zhao, Min; Peng, Changhui; Guo, Haiqiang; Wang, Qing; Zhao, Bin (Land, 2021)
Although rice paddy fields are one of the world’s largest anthropogenic sources of methane CH4, the budget of ecosystem CH4 and its’ controls in rice paddies remain unclear. Here, we analyze seasonal dynamics of direct ecosystem-scale measurements of CH4 flux in a rice-wheat rotation agroecosystem over 3 consecutive years. Results showed that the averaged CO2 uptakes and CH4 emissions in rice seasons were 2.2 and 20.9 folds of the wheat seasons, respectively. In sum, the wheat-rice rotation agroecosystem acted as a large net C sink (averaged 460.79 g C m−2) and a GHG (averaged 174.38 g CO2eq m−2) source except for a GHG sink in one year (2016) with a very high rice seeding density. While the linear correlation between daily CH4 fluxes and gross ecosystem productivity (GEP) was not significant for the whole rice season, daily CH4 fluxes were significantly correlated to daily GEP both before (R2: 0.52–0.83) and after the mid-season drainage (R2: 0.71–0.79). Furthermore, the F partial test showed that GEP was much greater than that of any other variable including soil temperature for the rice season in each year. Meanwhile, the parameters of the best-fit functions between daily CH4 fluxes and GEP shifted between rice growth stages. This study highlights that GEP is a good predictor of daily CH4 fluxes in rice paddies.

The impact of intensive management on net ecosystem productivity and net primary productivity of a Lei bamboo forest - Zhang, Minxia; Chen, Shulin; Jiang, Hong; Peng, Changhui; Zhang, Jinmeng; Zhou, Guomo (Ecological Modelling, 2020)

Modeling the effects of precipitation and temperature patterns on agricultural drought in China from 1949 to 2015 - Yang, Mingxia; Mou, Yuling; Meng, Yanrong; Liu, Shan; Peng, Changhui; Zhou, Xiaolu (Science of The Total Environment, 2020)

A new integrated framework to estimate the climate change impacts of biomass utilization for biofuel in life cycle assessment - Liu, Weiguo; Xu, Junming; Xie, Xinfeng; Yan, Yan; Zhou, Xiaolu; Peng, Changhui (Journal of Cleaner Production, 2020)

Effect of Urbanization on Ecosystem Service Values in the Beijing-Tianjin-Hebei Urban Agglomeration of China from 2000 to 2014 - Liu, Shan; Yang, Mingxia; Mou, Yuling; Meng, Yanrong; Zhou, Xiaolu; Peng, Changhui (Sustainability, 2020)
Rapid urbanization has led to the continuous deterioration of the surrounding natural ecosystem. It is important to identify the key urbanization factors that affect ecosystem services and analyze the potential effects of these factors on the ecosystem. We selected the Beijing, Tianjin, and Hebei (BTH) urban agglomeration to investigate these effects, and designed three indicators to map the urbanization level: Population density, gross domestic product (GDP) density, and the construction land proportion. Four indicators were chosen to quantify ecosystem services: Food production, carbon sequestration and oxygen production, water conservation, and soil conservation. To handle the nonlinear interactions, we used a random forest (RF) method to assess the effect of urbanization on ecosystem services in the BTH area from 2000 to 2014. Our study demonstrated that population density and economic growth were the internal driving forces affecting ecosystem services. We observed changing trends in the effect of urbanization: The effect of population density on ecosystem services increased, the effect of the proportion of construction land was consistent with population density, and the effect of GDP density on ecosystem services decreased. Our results suggest that controlling the population and GDP would significantly influence the sustainable development in large urban areas.

Land use/cover change in the Three Gorges Reservoir area, China: Reconciling the land use conflicts between development and protection - Huang, Chunbo; Huang, Xin; Peng, Changhui; Zhou, Zhixiang; Teng, Mingjun; Wang, Pengcheng (CATENA, 2019)

Re-estimating the changes and ranges of forest biomass carbon in China during the past 40 years - Zhou, Xiaolu; Lei, Xiangdong; Liu, Caixia; Huang, Huabing; Zhou, Carl; Peng, Changhui (Forest Ecosystems, 2019)
Abstract Background In recent decades the future of global forests has been a matter of increasing concern, particularly in relation to the threat of forest ecosystem responses under potential climate change. To the future predictions of these responses, the current forest biomass carbon storage (FCS) should first be clarified as much as possible, especially at national scales. However, few studies have introduced how to verify an FCS estimate by delimiting the reasonable ranges. This paper addresses an estimation of national FCS and its verification using two-step process to narrow the uncertainty. Our study focuses on a methodology for reducing the uncertainty resulted by converting from growing stock volume to above- and below-ground biomass (AB biomass), so as to eliminate the significant bias in national scale estimations. Methods We recommend splitting the estimation into two parts, one part for stem and the other part for AB biomass to preclude possible significant bias. Our method estimates the stem biomass from volume and wood density (WD), and converts the AB biomass from stem biomass by using allometric relationships. Results Based on the presented two-step process, the estimation of China’s FCS is performed as an example to explicate how to infer the ranges of national FCS. The experimental results demonstrate a national FCS estimation within the reasonable ranges (relative errors: + 4.46% and − 4.44%), e.g., 5.6–6.1 PgC for China’s forest ecosystem at the beginning of the 2010s. These ranges are less than 0.52 PgC for confirming each FCS estimate of different periods during the last 40 years. In addition, our results suggest the upper-limits by specifying a highly impractical value of WD (0.7 t∙m − 3 ) on the national scale. As a control reference, this value decides what estimate is impossible to achieve for the FCS estimates. Conclusions Presented methodological analysis highlights the possibility to determine a range that the true value could be located in. The two-step process will help to verify national FCS and also to reduce uncertainty in related studies. While the true value of national FCS is immeasurable, our work should motivate future studies that explore new estimations to approach the true value by narrowing the uncertainty in FCS estimations on national and global scales.

Positive responses of belowground C dynamics to nitrogen enrichment in China - Deng, Lei; Peng, Changhui; Zhu, Guangyu; Chen, Lei; Liu, Yulin; Shangguan, Zhouping (Science of The Total Environment, 2018)

Historic carbon budgets of Ontario’s forest ecosystems - Liu, Jinxun; Peng, Changhui; Apps, Mike; Dang, Qinglai; Banfield, Edwin; Kurz, Werner (Forest Ecology and Management, 2002)

Temporal and Spatial Variation of Wetland CH4 Emissions from the Qinghai–Tibet Plateau under Future Climate Change Scenarios - Zhang, Xian; Wang, Jieyi; Zhang, Jiang; Chen, Huai; Peng, Changhui; Zhu, Qiuan (Atmosphere, 2022)
Wetlands are an important natural source of methane (CH4), so it is important to quantify how their emissions may vary under future climate change conditions. The Qinghai–Tibet Plateau contains more than a third of China’s wetlands. Here, we simulated temporal and spatial variation in CH4 emissions from natural wetlands on the Qinghai–Tibet Plateau from 2008 to 2100 under Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. Based on the simulation results of the TRIPLEX-GHG model forced with data from 24 CMIP5 models of global climate, we predict that, assuming no change in wetland distribution on the Plateau, CH4 emissions from natural wetlands will increase by 35%, 98% and 267%, respectively, under RCP 2.6, 4.5 and 8.5. The predicted increase in atmospheric CO2 concentration will contribute 10–28% to the increased CH4 emissions from wetlands on the Plateau by 2100. Emissions are predicted to be majorly in the range of 0 to 30.5 g C m−2·a−1 across the Plateau and higher from wetlands in the southern region of the Plateau than from wetlands in central or northern regions. Under RCP8.5, the methane emissions of natural wetlands on the Qinghai–Tibet Plateau increased much more significantly than that under RCP2.6 and RCP4.5.

Contribution of Incorporating the Phosphorus Cycle into TRIPLEX-CNP to Improve the Quantification of Land Carbon Cycle - Ding, Juhua; Zhu, Qiuan; Li, Hanwei; Zhou, Xiaolu; Liu, Weiguo; Peng, Changhui (Land, 2022)
Phosphorus (P) is a key and a limiting nutrient in ecosystems and plays an important role in many physiological and biochemical processes, affecting both terrestrial ecosystem productivity and soil carbon storage. However, only a few global land surface models have incorporated P cycle and used to investigate the interactions of C-N-P and its limitation on terrestrial ecosystems. The overall objective of this study was to integrate the P cycle and its interaction with carbon (C) and nitrogen (N) into new processes model of TRIPLEX-CNP. In this study, key processes of the P cycle, including P pool sizes and fluxes in plant, litter, and soil were integrated into a new model framework, TRIPLEX-CNP. We also added dynamic P:C ratios for different ecosystems. Based on sensitivity analysis results, we identified the phosphorus resorption coefficient of leaf (rpleaf) as the most influential parameter to gross primary productivity (GPP) and biomass, and determined optimal coefficients for different plant functional types (PFTs). TRIPLEX-CNP was calibrated with 49 sites and validated against 116 sites across eight biomes globally. The results suggested that TRIPLEX-CNP performed well on simulating the global GPP and soil organic carbon (SOC) with respective R2 values of 0.85 and 0.78 (both p < 0.01) between simulated and observed values. The R2 of simulation and observation of total biomass are 0.67 (p < 0.01) by TRIPLEX-CNP. The overall model performance had been improved in global GPP, total biomass and SOC after adding the P cycle comparing with the earlier version. Our work represents the promising step toward new coupled ecosystem process models for improving the quantifications of land carbon cycle and reducing uncertainty.

Soil methane emissions from plain poplar (Populus spp.) plantations with contrasting soil textures - Ma, Xuehong; Feng, Huili; Guo, Jiahuan; Peng, Changhui; Kneeshaw, Daniel; Wang, Weifeng (Scientific Reports, 2024)
Abstract The forest soil methane (CH 4 ) flux exhibits high spatiotemporal variability. Understanding these variations and their driving factors is crucial for accurately assessing the forest CH 4 budget. In this study, we monitored the diurnal and seasonal variations in soil CH 4 fluxes in two poplar ( Populus spp.) plantations (Sihong and Dongtai) with different soil textures using the static chamber-based method. The results showed that the annual average soil CH 4 flux in the Sihong and Dongtai poplar plantations was 4.27 ± 1.37 kg CH 4 -C ha –1 yr –1 and 1.92 ± 1.07 kg CH 4 -C ha –1 yr –1 , respectively. Both plantations exhibited net CH 4 emissions during the growing season, with only weak CH 4 absorption (–0.01 to –0.007 mg m –2 h –1 ) during the non-growing season. Notably, there was a significant difference in soil CH 4 flux between the clay loam of the Sihong poplar plantation and the sandy loam of the Dongtai poplar plantation. From August to December 2019 and from July to August and November 2020, the soil CH 4 flux in the Sihong poplar plantation was significantly higher than in the Dongtai poplar plantation. Moreover, the soil CH 4 flux significantly increased with rising soil temperature and soil water content. Diurnally, the soil CH 4 flux followed a unimodal variation pattern at different growing stages of poplars, with peaks occurring at noon and in the afternoon. However, the soil CH 4 flux did not exhibit a consistent seasonal pattern across different years, likely due to substantial variations in precipitation and soil water content. Overall, our study emphasizes the need for a comprehensive understanding of the spatiotemporal variations in forest soil CH 4 flux with different soil textures. This understanding is vital for developing reasonable forest management strategies and reducing uncertainties in the global CH 4 budget.

Impacts of environmental and socioeconomic factors on gross ecosystem product of the Three Gorges reservoir area, China - Cheng, Jing; Liu, Shuangshuang; Huang, Chunbo; Wang, Lunche; Liu, Zelin; Peng, Changhui (Land Degradation & Development, 2024)
Abstract Environmental and socioeconomic drivers would alter landscapes, bringing various effects with different directions and magnitudes. Demonstrating these driving effects is key to relieving the conflicts between territorial vegetation restoration and regional economic growth. However, the relationship between ecological protection and economic development due to landscape dynamics has not been systematically demonstrated as environment is difficult to quantify by the monetary value. In this article, we explored the changes in gross ecosystem product (GEP) in the Three Gorges (TG) reservoir area and constructed a conceptual framework to explicate its driving mechanism. Our results suggested that topographic, soil, and climatic factors positively impact on GEP through their important effects on vegetation structure, distribution, and succession. Additionally, reforestation policies promote the conversion of farmland and grassland to forestland in the TG reservoir region, which was the main contributor to enhancing GEP. Conversely, socioeconomic factors negatively impact GEP, of which effects were mainly manifested by changes in the proportion of ecological land. Therefore, it is essential to maintain a suitable land use proportion in this region to optimize GEP, and we proposed a landscape restoration program to enhance four ecosystem productions. This article provides a reference for land resource allocation for environmental protection and sustainable development in ecologically fragile areas.

Estimates and Predictions of Methane Emissions from Wastewater in China from 2000 to 2020 - Du, Mingxi; Zhu, Qiuan; Wang, Xiaoge; Li, Peng; Yang, Bin; Chen, Huai; Wang, Meng; Zhou, Xiaolu; Peng, Changhui (Earth's Future, 2018)
Methane accounts for 20% of the global warming caused by greenhouse gases, and wastewater is a major anthropogenic source of methane. Based on the Intergovernmental Panel on Climate Change greenhouse gas inventory guidelines and current research findings, we calculated the amount of methane emissions from 2000 to 2014 that originated from wastewater from different provinces in China. Methane emissions from wastewater increased from 1349.01 to 3430.03 Gg from 2000 to 2014, and the mean annual increase was 167.69 Gg. The methane emissions from industrial wastewater treated by wastewater treatment plants ( E It ) accounted for the highest proportion of emissions. We also estimated the future trend of industrial wastewater methane emissions using the artificial neural network model. A comparison of the emissions for the years 2020, 2010, and 2000 showed an increasing trend in methane emissions in China and a spatial transition of industrial wastewater emissions from eastern and southern regions to central and southwestern regions and from coastal regions to inland regions. These changes were caused by changes in economics, demographics, and relevant policies. , Key Points Methane emission from wastewater from 2000 to 2014 was calculated to increase from 1349.01 Gg to 3430.03 Gg. Methane emission from wastewater from 2015 to 2020 was estimated to increase from 3875.30 Gg to 5212.75 Gg. A spatial transition of methane emission from wastewater was found and discussed in the present study.

Research progress, challenges, and prospects of PM2.5 concentration estimation using satellite data - Zhu, Shoutao; Tang, Jiayi; Zhou, Xiaolu; Li, Peng; Liu, Zelin; Zhang, Cicheng; Zou, Ziying; Li, Tong; Peng, Changhui (Environmental Reviews, 2023)
Satellite data are vital for understanding the large-scale spatial distribution of particulate matter (PM 2.5 ) due to their low cost, wide coverage, and all-weather capability. Estimation of PM 2.5 using satellite aerosol optical depth (AOD) products is a popular method. In this paper, we review the PM 2.5 estimation process based on satellite AOD data in terms of data sources (i.e., inversion algorithms, data sets, and interpolation methods), estimation models (i.e., statistical regression, chemical transport models, machine learning, and combinatorial analysis), and modeling validation (i.e., four types of cross-validation (CV) methods). We found that the accuracy of time-based CV is lower than others. We found significant differences in modeling accuracy between different seasons ( p < 0.01) and different spatial resolutions ( p < 0.01). We explain these phenomena in this article. Finally, we summarize the research process, present challenges, and future directions in this field. We opine that low-cost mobile devices combined with transfer learning or hybrid modeling offer research opportunities in areas with limited PM 2.5 monitoring stations and historical PM 2.5 estimation. These methods can be a good choice for air pollution estimation in developing countries. The purpose of this study is to provide a basic framework for future researchers to conduct relevant research, enabling them to understand current research progress and future research directions.

Spatial patterns of leaf δ13 C and its relationship with plant functional groups and environmental factors in China: Factors Dominate Plant Traits - Li, Mingxu; Peng, Changhui; Wang, Meng; Yang, Yanzheng; Zhang, Kerou; Li, Peng; Yang, Yan; Ni, Jian; Zhu, Qiuan (Journal of Geophysical Research: Biogeosciences, 2017)

Detecting and mapping tree crowns based on convolutional neural network and Google Earth images - Yang, Mingxia; Mou, Yuling; Liu, Shan; Meng, Yanrong; Liu, Zelin; Li, Peng; Xiang, Wenhua; Zhou, Xiaolu; Peng, Changhui (International Journal of Applied Earth Observation and Geoinformation, 2022)

Headwater stream ecosystem: an important source of greenhouse gases to the atmosphere - Li, Mingxu; Peng, Changhui; Zhang, Kerou; Xu, Li; Wang, Jianming; Yang, Yan; Li, Peng; Liu, Zelin; He, Nianpeng (Water Research, 2021)

Simulating carbon exchange in Canadian Boreal forests - Zhou, Xiaolu; Peng, Changhui; Dang, Qing-Lai; Sun, Jianfeng; Wu, Haibin; Hua, Dong (Ecological Modelling, 2008)

Application of machine-learning methods in forest ecology: recent progress and future challenges - Liu, Zelin; Peng, Changhui; Work, Timothy; Candau, Jean-Noel; DesRochers, Annie; Kneeshaw, Daniel (Environmental Reviews, 2018)
Machine learning, an important branch of artificial intelligence, is increasingly being applied in sciences such as forest ecology. Here, we review and discuss three commonly used methods of machine learning (ML) including decision-tree learning, artificial neural network, and support vector machine and their applications in four different aspects of forest ecology over the last decade. These applications include: (i) species distribution models, (ii) carbon cycles, (iii) hazard assessment and prediction, and (iv) other applications in forest management. Although ML approaches are useful for classification, modeling, and prediction in forest ecology research, further expansion of ML technologies is limited by the lack of suitable data and the relatively “higher threshold” of applications. However, the combined use of multiple algorithms and improved communication and cooperation between ecological researchers and ML developers still present major challenges and tasks for the betterment of future ecological research. We suggest that future applications of ML in ecology will become an increasingly attractive tool for ecologists in the face of “big data” and that ecologists will gain access to more types of data such as sound and video in the near future, possibly opening new avenues of research in forest ecology.

Drought‐induced increase in tree mortality and corresponding decrease in the carbon sink capacity of Canada's boreal forests from 1970 to 2020 - Liu, Qiuyu; Peng, Changhui; Schneider, Robert; Cyr, Dominic; McDowell, Nate G.; Kneeshaw, Daniel (Global Change Biology, 2023)
Abstract Canada's boreal forests, which occupy approximately 30% of boreal forests worldwide, play an important role in the global carbon budget. However, there is little quantitative information available regarding the spatiotemporal changes in the drought‐induced tree mortality of Canada's boreal forests overall and their associated impacts on biomass carbon dynamics. Here, we develop spatiotemporally explicit estimates of drought‐induced tree mortality and corresponding biomass carbon sink capacity changes in Canada's boreal forests from 1970 to 2020. We show that the average annual tree mortality rate is approximately 2.7%. Approximately 43% of Canada's boreal forests have experienced significantly increasing tree mortality trends (71% of which are located in the western region of the country), and these trends have accelerated since 2002. This increase in tree mortality has resulted in significant biomass carbon losses at an approximate rate of 1.51 ± 0.29 MgC ha −1 year −1 (95% confidence interval) with an approximate total loss of 0.46 ± 0.09 PgC year −1 (95% confidence interval). Under the drought condition increases predicted for this century, the capacity of Canada's boreal forests to act as a carbon sink will be further reduced, potentially leading to a significant positive climate feedback effect.

Past and future carbon sequestration benefits of China’s grain for green program - Deng, Lei; Liu, Shuguang; Kim, Dong Gill; Peng, Changhui; Sweeney, Sandra; Shangguan, Zhouping (Global Environmental Change, 2017)

Nitrogen metabolism of two contrasting poplar species during acclimation to limiting nitrogen availability - Luo, Jie; Li, Hong; Liu, Tongxian; Polle, Andrea; Peng, Changhui; Luo, Zhi-Bin (Journal of Experimental Botany, 2013)

Notice of Retraction: Short-Term Response of Koelreuteria paniculata Seedlings to Simulated Soils Polluted by Manganese Mining Wasteland in Central South China - Zhao, Kun; Huang, Zhihong; Ma, Yu'e; Xiang, Wenhua; Peng, Changhui; Deng, Xiangwen (2011 5th International Conference on Bioinformatics and Biomedical Engineering, 2011)

Model prediction of biome‐specific global soil respiration from 1960 to 2012 - Zhao, Zhengyong; Peng, Changhui; Yang, Qi; Meng, Fan‐Rui; Song, Xinzhang; Chen, Shutao; Epule, Terence Epule; Li, Peng; Zhu, Qiuan (Earth's Future, 2017)
Abstract Biome‐specific soil respiration (Rs) has important yet different roles in both the carbon cycle and climate change from regional to global scales. To date, no comparable studies related to global biome‐specific Rs have been conducted applying comprehensive global Rs databases. The goal of this study was to develop artificial neural network ( ANN ) models capable of spatially estimating global Rs and to evaluate the effects of interannual climate variations on 10 major biomes. We used 1976 annual Rs field records extracted from global Rs literature to train and test the ANN models. We determined that the best ANN model for predicting biome‐specific global annual Rs was the one that applied mean annual temperature ( MAT ), mean annual precipitation ( MAP ), and biome type as inputs ( r 2 = 0.60). The ANN models reported an average global Rs of 93.3 ± 6.1 Pg C yr −1 from 1960 to 2012 and an increasing trend in average global annual Rs of 0.04 Pg C yr −1 . Estimated annual Rs increased with increases in MAT and MAP in cropland, boreal forest, grassland, shrubland, and wetland biomes. Additionally, estimated annual Rs decreased with increases in MAT and increased with increases in MAP in desert and tundra biomes, and only significantly decreased with increases in MAT ( r 2 = 0.87) in the savannah biome. The developed biome‐specific global Rs database for global land and soil carbon models will aid in understanding the mechanisms underlying variations in soil carbon dynamics and in quantifying uncertainty in the global soil carbon cycle. , Key Points Predict biome‐specific global soil respiration from 1960 to 2012 using an artificial neural network model Prediction determined an average global soil respiration of 93.3 ± 6.1 Pg C yr −1 and an increasing trend of 0.04 Pg C yr −1 The 10 biome‐specific soil respiration estimates made it possible to trace different responses to global climate change in each biome

Quantification and uncertainty of global upland soil methane sinks: Processes, controls, model limitations, and improvements - Song, Hanxiong; Peng, Changhui; Zhu, Qiuan; Chen, Zhi; Blanchet, Jean-Pierre; Liu, Qiuyu; Li, Tong; Li, Peng; Liu, Zelin (Earth-Science Reviews, 2024)

Quantifying the effects of climate change and harvesting on carbon dynamics of boreal aspen and jack pine forests using the TRIPLEX-Management model - Wang, Weifeng; Peng, Changhui; Kneeshaw, Daniel D.; Larocque, Guy R.; Song, Xinzhang; Zhou, Xiaolu (Forest Ecology and Management, 2012)

Development of a New TRIPLEX-Insect Model for Simulating the Effect of Spruce Budworm on Forest Carbon Dynamics - Liu, Zelin; Peng, Changhui; De Grandpré, Louis; Candau, Jean-Noël; Zhou, Xiaolu; Kneeshaw, Daniel (Forests, 2018)
The spruce budworm (SBW) defoliates and kills conifer trees, consequently affecting carbon (C) exchanges between the land and atmosphere. Here, we developed a new TRIPLEX-Insect sub-model to quantify the impacts of insect outbreaks on forest C fluxes. We modeled annual defoliation (AD), cumulative defoliation (CD), and tree mortality. The model was validated against observed and published data at the stand level in the North Shore region of Québec and Cape Breton Island in Nova Scotia, Canada. The results suggest that TRIPLEX-Insect performs very well in capturing tree mortality following SBW outbreaks and slightly underestimates current annual volume increment (CAI). In both mature and immature forests, the simulation model suggests a larger reduction in gross primary productivity (GPP) than in autotrophic respiration (Ra) at the same defoliation level when tree mortality was low. After an SBW outbreak, the growth release of surviving trees contributes to the recovery of annual net ecosystem productivity (NEP) based on forest age if mortality is not excessive. Overall, the TRIPLEX-Insect model is capable of simulating C dynamics of balsam fir following SBW disturbances and can be used as an efficient tool in forest insect management.

Developing allometric equations to estimate forest biomass for tree species categories based on phylogenetic relationships - Yang, Mingxia; Zhou, Xiaolu; Peng, Changhui; Li, Tong; Chen, Kexin; Liu, Zelin; Li, Peng; Zhang, Cicheng; Tang, Jiayi; Zou, Ziying (Forest Ecosystems, 2023)

Global response of terrestrial gross primary productivity to climate extremes - Yuan, Minshu; Zhu, Qiuan; Zhang, Jiang; Liu, Jinxun; Chen, Huai; Peng, Changhui; Li, Peng; Li, Mingxu; Wang, Meng; Zhao, Pengxiang (Science of The Total Environment, 2021)

Effects of increasing aerosol optical depth on the gross primary productivity in China during 2000–2014 - Zhang, Jing; Ding, Juhua; Zhang, Jiang; Yuan, Minshu; Li, Peng; Xiao, Zhongyong; Peng, Changhui; Chen, Huai; Wang, Meng; Zhu, Qiuan (Ecological Indicators, 2020)

Individual and combined effects of multiple global change drivers on terrestrial phosphorus pools: A meta-analysis - Yue, Kai; Yang, Wanqin; Peng, Yan; Peng, Changhui; Tan, Bo; Xu, Zhenfeng; Zhang, Li; Ni, Xiangyin; Zhou, Wei; Wu, Fuzhong (Science of The Total Environment, 2018)

Assessing the spatio-temporal variation and uncertainty patterns of historical and future projected water resources in China - Zhu, Qiuan; Jiang, Hong; Peng, Changhui; Liu, Jinxun; Fang, Xiuqin; Chen, Huai; Liu, Shirong (Journal of Water and Climate Change, 2013)
The spatial and temporal variation and uncertainty of precipitation and runoff in China were compared and evaluated between historical and future periods under different climate change scenarios. The precipitation pattern is derived from observed and future projected precipitation data for historical and future periods, respectively. The runoff is derived from simulation results in historical and future periods using a dynamic global vegetation model (DGVM) forced with historical observed and global climate models (GCMs) future projected climate data, respectively. One GCM (CGCM3.1) under two emission scenarios (SRES A2 and SRES B1) was used for the future period simulations. The results indicated high uncertainties and variations in climate change effects on hydrological processes in China: precipitation and runoff showed a significant increasing trend in the future period but a decreasing trend in the historical period at the national level; the temporal variation and uncertainty of projected precipitation and runoff in the future period were predicted to be higher than those in the historical period; the levels of precipitation and runoff in the future period were higher than those in the historical period. The change in trends of precipitation and runoff are highly affected by different climate change scenarios. GCM structure and emission scenarios should be the major sources of uncertainty.

Simulations of runoff and evapotranspiration in Chinese fir plantation ecosystems using artificial neural networks - Liu, Zelin; Peng, Changhui; Xiang, Wenhua; Deng, Xiangwen; Tian, DaLun; Zhao, Meifang; Yu, Guirui (Ecological Modelling, 2012)

Weak indirect effects inherent to nitrogen biogeochemical cycling within anthropogenic ecosystems: A network environ analysis - Min, Yong; Jin, Xiaogang; Chang, Jie; Peng, Changhui; Gu, Baojing; Ge, Ying; Zhong, Yang (Ecological Modelling, 2011)

Nitrous oxide fluxes from the littoral zone of a lake on the Qinghai-Tibetan Plateau - Chen, Huai; Wang, Meng; Wu, Ning; Wang, Yanfen; Zhu, Dan; Gao, Yongheng; Peng, Changhui (Environmental Monitoring and Assessment, 2011)

Altitudinal changes in carbon storage of temperate forests on Mt Changbai, Northeast China - Zhu, Biao; Wang, Xiangping; Fang, Jingyun; Piao, Shilong; Shen, Haihua; Zhao, Shuqing; Peng, Changhui (Journal of Plant Research, 2010)

Quantifying the response of forest carbon balance to future climate change in Northeastern China: Model validation and prediction - Peng, Changhui; Zhou, Xiaolu; Zhao, Shuqing; Wang, Xiangping; Zhu, Biao; Piao, Shilong; Fang, Jingyun (Global and Planetary Change, 2009)

Anthropogenic modification of the nitrogen cycling within the Greater Hangzhou Area system, China - Gu, Baojing; Chang, Jie; Ge, Ying; Ge, Hanliang; Yuan, Chi; Peng, Changhui; Jiang, Hong (Ecological Applications, 2009)
Based on the mass balance approach, a detailed quantification of nitrogen (N) cycling was constructed for an urban–rural complex system, named the Greater Hangzhou Area (GHA) system, for this paper. The GHA is located in the humid climatic region on the southeastern coast of China, one of the earliest regions in the Yangtze Delta to experience economic development. Total N input into the GHA was calculated at 274.66 Gg/yr (1 Gg = 10 9 g), and total output was calculated at 227.33 Gg/yr, while N accumulation was assessed at 47.33 Gg/yr (17.2% of the total N input). Human activity resulted in 73% of N input by means of synthetic fertilizers, human food, animal feed, imported N containing chemicals, fossil fuel combustion, and other items. More than 69.3% of N was released into the atmosphere, and riverine N export accounted for 22.2% of total N output. N input and output to and from the GHA in 1980 were estimated at 119.53 Gg/yr and 98.30 Gg/yr, respectively, with an increase of 130% and 131%, respectively, during a 24‐year period (from 1980 to 2004). The N input increase was influenced by synthetic fertilizers (138%), animal feed (225%), N‐containing chemicals (371%), riverine input (311%), and N deposition (441%). Compared to the N balance seen in the arid Central Arizona–Phoenix (CAP) system in the United States, the proportion of N transferred to water bodies in the humid GHA system was found to be 36 times higher than the CAP system. Anthropogenic activity, as it typically does, enhanced the flux of N biogeochemistry in the GHA; however, a lack of an N remover (N pollutant treatment facilities) causes excess reactive N (N r ; such as NH 3 , N 2 O, NO x ), polluting water bodies and the atmosphere within the GHA. Therefore many challenges remain ahead in order to achieve sustainable development in the rapidly developing GHA system.

Building a "Green" Railway in China - Peng, Changhui; Ouyang, Hua; Gao, Qiong; Jiang, Yuan; Zhang, Feng; Li, Jun; Yu, Qiang (Science, 2007)

Biochar mitigates dissolved organic carbon loss but does not affect dissolved organic nitrogen leaching loss caused by nitrogen deposition in Moso bamboo plantations - Lei, Zhaofeng; Li, Quan; Song, Xinzhang; Wang, Weifeng; Zhang, Zhiting; Peng, Changhui; Tian, Linlin (Global Ecology and Conservation, 2018)

Quantifying patterns, sources and uncertainty of nitrous oxide emissions from global grazing lands: Nitrogen forms are the determinant factors for estimation and mitigation - Song, Hanxiong; Peng, Changhui; Zhang, Kerou; Li, Tong; Yang, Mingxia; Liu, Qiuyu; Zhu, Qiuan (Global and Planetary Change, 2023)

Predicting potential climate change impacts of bioenergy from perennial grasses in 2050 - Liu, Weiguo; Wang, Kui; Hao, Hongke; Yan, Yan; Zhang, Han; Zhang, Huanling; Peng, Changhui (Resources, Conservation and Recycling, 2023)

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX‐GHG - Wang, Kefeng; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Wang, Meng; Zhang, Kerou; Wang, Gangsheng (Journal of Advances in Modeling Earth Systems, 2017)
Abstract Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process‐based model TRIPLEX‐GHG was developed by coupling it with the new MEND (Microbial‐ENzyme‐mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX‐MICROBE) shows considerable improvement over the previous version (TRIPLEX‐GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195 Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well‐regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated by Xu et al. (2014). We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC), and mineral‐associated organic carbon (MOC). However, our work represents the first step toward a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles. , Key Points Traditional soil carbon models are lacking in their representation of key microbial processes that control the soil carbon response to global climate change A Ecosystem model (TRIPLEX‐MICROBE) offers considerable improvement over a previous version (TRIPLEX‐GHG) in simulating soil organic carbon Our work is the first step toward a new generation of ecosystem process models that integrate key microbial processes into soil carbon cycles

Significant effects of biodiversity on forest biomass during the succession of subtropical forest in south China - Ouyang, Shuai; Xiang, Wenhua; Wang, Xiangping; Zeng, Yelin; Lei, Pifeng; Deng, Xiangwen; Peng, Changhui (Forest Ecology and Management, 2016)

Integrating a model with remote sensing observations by a data assimilation approach to improve the model simulation accuracy of carbon flux and evapotranspiration at two flux sites - Zhang, TingLong; Sun, Rui; Peng, ChangHui; Zhou, GuoYi; Wang, ChunLing; Zhu, QiuAn; Yang, YanZheng (Science China Earth Sciences, 2016)

Effects of Topographic and Soil Factors on Woody Species Assembly in a Chinese Subtropical Evergreen Broadleaved Forest - Zhao, Lijuan; Xiang, Wenhua; Li, Jiaxiang; Lei, Pifeng; Deng, Xiangwen; Fang, Xi; Peng, Changhui (Forests, 2015)
Evergreen broadleaved forests in subtropical China contain a complicated structure of diverse species. The impact of topographic and soil factors on the assembly of woody species in the forest has been poorly understood. We used Ripley’s K(t) function to analyze the spatial patterns and associations of dominant species and residual analysis (RDA) to quantify the contribution of topography and soil to species assembly. The 1 ha plot investigated had 4797 stems with a diameter at breast height (dbh) larger than 1 cm that belong to 73 species, 55 genera, and 38 families. All stems of the entire forest and four late successional species exhibited a reversed J shape for dbh distribution, while two early successional species showed a unimodal shape. Aggregation was the major spatial pattern for entire forests and dominant species across vertical layers. Spatial associations between inter- and intra-species were mostly independent. Topographic and soil factors explained 28.1% of species assembly. The forest was close to late succession and showed the characteristics of diverse woody species, high regeneration capacity, and aggregated spatial patterns. Topographic and soil factors affected species assembly, but together they could only explain a small part of total variance.

A novel pathway of direct methane production and emission by eukaryotes including plants, animals and fungi: An overview - Liu, Jiangong; Chen, Huai; Zhu, Qiuan; Shen, Yan; Wang, Xue; Wang, Meng; Peng, Changhui (Atmospheric Environment, 2015)

MODELING INDIVIDUAL TREE MORTALITY RATES USING MARGINAL AND RANDOM EFFECTS REGRESSION MODELS - Ma, Zhihai; Peng, Changhui; Li, Weizhong; Zhu, Qiuan; Wang, Weifeng; Song, Xinzhang; Liu, Jianwei (Natural Resource Modeling, 2013)
A bstract Developing models to predict tree mortality using data from long‐term repeated measurement data sets can be difficult and challenging due to the nature of mortality as well as the effects of dependence on observations. Marginal (population‐averaged) generalized estimating equations (GEE) and random effects (subject‐specific) models offer two possible ways to overcome these effects. For this study, standard logistic, marginal logistic based on the GEE approach, and random logistic regression models were fitted and compared. In addition, four model evaluation statistics were calculated by means of K ‐fold cross‐valuation. They include the mean prediction error, the mean absolute prediction error, the variance of prediction error, and the mean square error. Results from this study suggest that the random effects model produced the smallest evaluation statistics among the three models. Although marginal logistic regression accommodated for correlations between observations, it did not provide noticeable improvements of model performance compared to the standard logistic regression model that assumed impendence. This study indicates that the random effects model was able to increase the overall accuracy of mortality modeling. Moreover, it was able to ascertain correlation derived from the hierarchal data structure as well as serial correlation generated through repeated measurements.

Soil temperature, microbial biomass and enzyme activity are the critical factors affecting soil respiration in different soil layers in Ziwuling Mountains, China - Qu, Ruosong; Liu, Guanzhen; Yue, Ming; Wang, Gangsheng; Peng, Changhui; Wang, Kefeng; Gao, Xiaoping (Frontiers in Microbiology, 2023)
Soil microorganisms are critical biological indicators for evaluating soil health and play a vital role in carbon (C)-climate feedback. In recent years, the accuracy of models in terms of predicting soil C pools has been improved by considering the involvement of microbes in the decomposition process in ecosystem models, but the parameter values of these models have been assumed by researchers without combining observed data with the models and without calibrating the microbial decomposition models. Here, we conducted an observational experiment from April 2021 to July 2022 in the Ziwuling Mountains, Loess Plateau, China, to explore the main influencing factors of soil respiration (R S ) and determine which parameters can be incorporated into microbial decomposition models. The results showed that the R S rate is significantly correlated with soil temperature (T S ) and moisture (M S ), indicating that T S increases soil C loss. We attributed the non-significant correlation between R S and soil microbial biomass carbon (MBC) to variations in microbial use efficiency, which mitigated ecosystem C loss by reducing the ability of microorganisms to decompose organic resources at high temperatures. The structural equation modeling (SEM) results demonstrated that T S , microbial biomass, and enzyme activity are crucial factors affecting soil microbial activity. Our study revealed the relations between T S , microbial biomass, enzyme activity, and R S , which had important scientific implications for constructing microbial decomposition models that predict soil microbial activity under climate change in the future. To better understand the relationship between soil dynamics and C emissions, it will be necessary to incorporate climate data as well as R S and microbial parameters into microbial decomposition models, which will be important for soil conservation and reducing soil C loss in the Loess Plateau.

Evaluating and quantifying the effect of various spruce budworm intervention strategies on forest carbon dynamics in Atlantic Canada - Liu, Zelin; Peng, Changhui; MacLean, David A.; De Grandpré, Louis; Candau, Jean-Noël; Kneeshaw, Daniel (Forest Ecosystems, 2022)

The effects of elevated CO2, elevated O3, elevated temperature, and drought on plant leaf gas exchanges: a global meta-analysis of experimental studies - Zhang, Jinmeng; Deng, Lei; Jiang, Hong; Peng, Changhui; Huang, Chunbo; Zhang, Minxia; Zhang, Xiuying (Environmental Science and Pollution Research, 2021)

The Effects of Drought and Re-Watering on Non-Structural Carbohydrates of Pinus tabulaeformis Seedlings - Guo, Xinyi; Peng, Changhui; Li, Tong; Huang, Jingjing; Song, Hanxiong; Zhu, Qiuan; Wang, Meng (Biology, 2021)
Intense and frequent drought events strongly affect plant survival. Non-structural carbohydrates (NSCs) are important “buffers” to maintain plant functions under drought conditions. We conducted a drought manipulation experiment using three-year-old Pinus tabulaeformis Carr. seedlings. The seedlings were first treated under different drought intensities (i.e., no irrigation, severe, and moderate) for 50 days, and then they were re-watered for 25 days to explore the dynamics of NSCs in the leaves, twigs, stems, and roots. The results showed that the no irrigation and severe drought treatments significantly reduced photosynthetic rate by 93.9% and 32.6% for 30 days, respectively, leading to the depletion of the starch storage for hydraulic repair, osmotic adjustment, and plant metabolism. The seedlings under moderate drought condition also exhibited starch storage consumption in leaves and twigs. After re-watering, the reduced photosynthetic rate recovered to the control level within five days in the severe drought group but showed no sign of recovery in the no irrigation group. The seedlings under the severe and moderate drought conditions tended to invest newly fixed C to starch storage and hydraulic repair instead of growth due to the “drought legacy effect”. Our findings suggest the depletion and recovery of starch storage are important strategies for P. tabulaeformis seedlings, and they may play key roles in plant resistance and resilience under environmental stress.

TRIPLEX-Mortality model for simulating drought-induced tree mortality in boreal forests: Model development and evaluation - Liu, Qiuyu; Peng, Changhui; Schneider, Robert; Cyr, Dominic; Liu, Zelin; Zhou, Xiaolu; Kneeshaw, Daniel (Ecological Modelling, 2021)

Woody plants reduce the sensitivity of soil extracellular enzyme activity to nutrient enrichment in wetlands: A meta-analysis - Li, Tong; Peng, Changhui; Bu, Zhaojun; Zhu, Qiuan; Song, Hanxiong; Guo, Xinyi; Wang, Meng (Soil Biology and Biochemistry, 2021)

Decoupling the Complementarity Effect and the Selection Effect on the Overyielding of Fine Root Production Along a Tree Species Richness Gradient in Subtropical Forests - Liu, Cong; Xiang, Wenhua; Xie, Binggeng; Ouyang, Shuai; Zeng, Yelin; Lei, Pifeng; Peng, Changhui (Ecosystems, 2021)

Effects of Nitrogen Additions on Soil Respiration in an Asian Tropical Montane Rainforest - Wu, Fangtao; Peng, Changhui; Liu, Weiguo; Liu, Zhihao; Wang, Hui; Chen, Dexiang; Li, Yide (Forests, 2021)
Understanding the impacts of nitrogen (N) addition on soil respiration (RS) and its temperature sensitivity (Q10) in tropical forests is very important for the global carbon cycle in a changing environment. Here, we investigated how RS respond to N addition in a tropical montane rainforest in Southern China. Four levels of N treatments (0, 25, 50, and 100 kg N ha−1 a−1 as control (CK), low N (N25), moderate N (N50), and high N (N100), respectively) were established in September 2010. Based on a static chamber-gas chromatography method, RS was measured from January 2015 to December 2018. RS exhibited significant seasonal variability, with low RS rates appeared in the dry season and high rates appeared in the wet season regardless of treatment. RS was significantly related to the measured soil temperature and moisture. Our results showed that soil RS increased after N additions, the mean annual RS was 7% higher in N25 plots, 8% higher in N50 plots, and 11% higher in N100 plots than that in the CK plots. However, the overall impacts of N additions on RS were statistically insignificant. For the entire study period, the CK, N25, N50, and N100 treatments yielded Q10 values of 2.27, 3.45, 4.11, and 2.94, respectively. N addition increased the temperature sensitivity (Q10) of RS. Our results suggest that increasing atmospheric N deposition may have a large impact on the stimulation of soil CO2 emissions from tropical rainforests in China.

Long-term forest succession improves plant diversity and soil quality but not significantly increase soil microbial diversity: Evidence from the Loess Plateau - Liu, Yulin; Zhu, Guangyu; Hai, Xuying; Li, Jiwei; Shangguan, Zhouping; Peng, Changhui; Deng, Lei (Ecological Engineering, 2020)

Global estimation of the climate change impact of logging residue utilization for biofuels - Liu, Weiguo; Hou, Yue; Liu, Wenyan; Yang, Mingxia; Yan, Yan; Peng, Changhui; Yu, Zhen (Forest Ecology and Management, 2020)

The significant contribution of lake depth in regulating global lake diffusive methane emissions - Li, Mingxu; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Yang, Gang; Song, Xinzhang; Zhang, Kerou (Water Research, 2020)

Effects of Land Cover Changes on Net Primary Productivity in the Terrestrial Ecosystems of China from 2001 to 2012 - Li, Hanwei; Ding, Juhua; Zhang, Jiang; Yang, Zhenan; Yang, Bin; Zhu, Qiuan; Peng, Changhui (Land, 2020)
The 2001–2012 MODIS MCD12Q1 land cover data and MOD17A3 NPP data were used to calculate changes in land cover in China and annual changes in net primary productivity (NPP) during a 12-year period and to quantitatively analyze the effects of land cover change on the NPP of China’s terrestrial ecosystems. The results revealed that during the study period, no changes in land cover type occurred in 7447.31 thousand km2 of China, while the area of vegetation cover increased by 160.97 thousand km2 in the rest of the country. Forest cover increased to 20.91%, which was mainly due to the conversion of large areas of savanna (345.19 thousand km2) and cropland (178.96 thousand km2) to forest. During the 12-year study period, the annual mean NPP of China was 2.70 PgC and increased by 0.25 PgC, from 2.50 to 2.75 PgC. Of this change, 0.21 PgC occurred in areas where there was no land cover change, while 0.04 PgC occurred in areas where there was land cover change. The contributions of forest and cropland to NPP exhibited increasing trends, while the contributions of shrubland and grassland to NPP decreased. Among these land cover types, the contributions of forest and cropland to the national NPP were the greatest, accounting for 40.97% and 27.95%, respectively, of the annual total NPP. There was no significant correlation between changes in forest area and changes in total annual NPP (R2 < 0.1), while the correlation coefficient for changes in cropland area and total annual NPP was 0.48. Additionally, the area of cropland converted to other land cover types was negatively correlated with the changes in NPP, and the loss of cropland caused a reduction in the national NPP.

Separating Regressions for Model Fitting to Reduce the Uncertainty in Forest Volume-Biomass Relationship - Liu, Caixia; Zhou, Xiaolu; Lei, Xiangdong; Huang, Huabing; Zhou, Carl; Peng, Changhui; Wang, Xiaoyi (Forests, 2019)
The method of forest biomass estimation based on a relationship between the volume and biomass has been applied conventionally for estimating stand above- and below-ground biomass (SABB, t ha−1) from mean growing stock volume (m3 ha−1). However, few studies have reported on the diagnosis of the volume-SABB equations fitted using field data. This paper addresses how to (i) check parameters of the volume-SABB equations, and (ii) reduce the bias while building these equations. In our analysis, all equations were applied based on the measurements of plots (biomass or volume per hectare) rather than individual trees. The volume-SABB equation is re-expressed by two Parametric Equations (PEs) for separating regressions. Stem biomass is an intermediate variable (parametric variable) in the PEs, of which one is established by regressing the relationship between stem biomass and volume, and the other is created by regressing the allometric relationship of stem biomass and SABB. A graphical analysis of the PEs proposes a concept of “restricted zone,” which helps to diagnose parameters of the volume-SABB equations in regression analyses of field data. The sampling simulations were performed using pseudo data (artificially generated in order to test a model) for the model test. Both analyses of the regression and simulation demonstrate that the wood density impacts the parameters more than the allometric relationship does. This paper presents an applicable method for testing the field data using reasonable wood densities, restricting the error in field data processing based on limited field plots, and achieving a better understanding of the uncertainty in building those equations.

Modeling Global Riverine DOC Flux Dynamics From 1951 to 2015 - Li, Mingxu; Peng, Changhui; Zhou, Xiaolu; Yang, Yanzheng; Guo, Yanrong; Shi, Guohua; Zhu, Qiuan (Journal of Advances in Modeling Earth Systems, 2019)
Abstract Climate change has a profound impact on the global carbon cycle, including effects on riverine carbon pools, which connect terrestrial, oceanic, and atmospheric carbon pools. Until now, terrestrial ecosystem models have rarely incorporated riverine carbon components into global carbon budgets. Here we developed a new process‐based model, TRIPLEX‐HYDRA (TRIPLEX‐hydrological routing algorithm), that considers the production, consumption, and transport processes of nonanthropogenic dissolved organic carbon (DOC) from soil to river ecosystems. After the parameter calibration, model results explained more than 50% of temporal variations in all but three rivers. Validation results suggested that DOC yield simulated by TRIPLEX‐HYDRA has a good fit ( R 2 = 0.61, n = 71, p < 0.001) with global river observations. And then, we applied this model for global rivers. We found that mean DOC yield of global river approximately 1.08 g C/m 2 year, where most high DOC yield appeared in the rivers from high northern or tropic regions. Furthermore, our results suggested that global riverine DOC flux appeared a significant decrease trend (average rate: 0.38 Pg C/year) from 1951 to 2015, although the variation patterns of DOC fluxes in global rivers are diverse. A decreasing trend in riverine DOC flux appeared in the middle and high northern latitude regions (30–90°N), which could be attributable to an increased flow path and DOC degradation during the transport process. Furthermore, increasing trend of DOC fluxes is found in rivers from tropical regions (30°S–30°N), which might be related to an increase in terrestrial organic carbon input. Many other rivers (e.g., Mississippi, Yangtze, and Lena rivers) experienced no significant changes under a changing environment. , Key Points Terrestrial ecosystem models rarely incorporate riverine DOC components into the global carbon cycle The TRIPLEX‐HYDRA model simulates the spatiotemporal variation in the DOC fluxes in global rivers The global riverine DOC flux simulated by the TRIPLEX‐HYDRA model has significantly decreased from 1951 to 2015

The 7-Decade Degradation of a Large Freshwater Lake in Central Yangtze River, China - Zhao, Shuqing; Fang, Jingyun; Miao, Shili; Gu, Ben; Tao, Shu; Peng, Changhui; Tang, Zhiyao (Environmental Science & Technology, 2005)

Potential future changes in soil carbon dynamics in the Ziwuling Forest, China under different climate change scenarios - Qu, Ruosong; Chen, Shiyi; Wang, Kefeng; Liu, Qiuyu; Yang, Bin; Yue, Ming; Peng, Changhui (Science of The Total Environment, 2024)

Impacts of landscape dynamics on terrestrial ecosystem health in the Three Gorges Reservoir Area, China - Huang, Chunbo; Cheng, Jing; Liu, Shuangshuang; Wan, Yunshan; Zhou, Jie; Liu, Zelin; Peng, Changhui (Journal of Cleaner Production, 2024)

Differential Responses of Soil Microbial and Carbon‐Nitrogen Processes to Future Environmental Changes Across Soil Depths and Environmental Factors - Wang, Kefeng; Wang, Gangsheng; Qu, Ruosong; Huang, Wenjuan; Zhou, Guoyi; Yue, Ming; Peng, Changhui (Earth's Future, 2024)
Abstract Accurately predicting carbon‐climate feedbacks relies on understanding the environmental factors regulating soil organic carbon (SOC) storage and dynamics. Here, we employed a microbial ecological model (MEND), driven by downscaled output data from six Earth system models under two Shared Socio‐economic Pathways (SSP1‐2.6 and SSP5‐8.5) scenarios, to simulate long‐term soil biogeochemical processes. We aim to analyze the responses of soil microbial and carbon‐nitrogen (C‐N) processes to changes in environmental factors, including litter input (L), soil moisture (W) and temperature (T), and soil pH, in a broadleaf forest (BF) and a pine forest (PF). For the entire soil layer in both forests, we found that, compared to the baseline period of 2009–2020, the mean SOC during 2081–2100 increased by 40.9%–90.6% under the L or T change scenarios, versus 5.2%–31.0% under the W change scenario. However, soil moisture emerged as a key regulator of SOC, MBC and inorganic N dynamics in the topsoil of BF and PF. For example, W change led to SOC gain of 5.5%–37.2%, compared to the SOC loss of 15.5%–18.0% under L or T scenario. Additionally, a further reduction in soil pH by 0.2 units in the BF, representing the acid rain effect, significantly resulted in an additional SOC gain by 14.2%–21.3%, compared to the LTW (simultaneous changes in the three factors) scenario. These results indicate that the results derived solely from topsoil may not be extrapolated to the entire soil profile. Overall, this study significantly advances our comprehension of how different environmental factors impact the dynamics of SOC and the implications they have for climate change. , Plain Language Summary Accurately predicting carbon‐climate feedbacks relies on understanding the environmental factors regulating soil organic carbon (SOC) storage and dynamics. We aim to analyze the responses of soil microbial and carbon‐nitrogen (C‐N) processes to changes in environmental factors, including litter input (L), soil moisture (W) and temperature (T), and soil pH, in a broadleaf forest (BF) and a pine forest (PF). We found that soil moisture change would be beneficial for SOC accumulation and serves as a key regulator of MBC and inorganic N in topsoil, whereas the change in litterfall or soil temperature are favorable for SOC accumulation in the entire soil profile. Additionally, a further reduction in soil pH by 0.2 units, representing the acid rain effect, significantly resulted in an additional SOC gain by 14.2%–21.3%, compared to the scenario with simultaneous changes in L, W, and T. These results indicate that findings solely from topsoil may not be extrapolated to the entire soil profile. Overall, this study significantly advances our comprehension of how different environmental factors impact the dynamics of SOC and the implications they have for climate change. , Key Points Soil C responses to climate change are depth dependent, therefore, results from just the topsoil may not apply to the entire soil profile Soil moisture change benefits topsoil SOC accumulation, whereas litterfall and soil temperature changes favor SOC accumulation in the entire soil profile We need to pay more attention to the effects of soil moisture and pH rather than temperature and litter‐input on soil biogeochemical processes

Globally limited individual and combined effects of multiple global change factors on allometric biomass partitioning - Peng, Yan; Fornara, Dario A.; Yue, Kai; Peng, Xin; Peng, Changhui; Wu, Qiqian; Ni, Xiangyin; Liao, Shu; Yang, Yusheng; Wu, Fuzhong; Peñuelas, Josep (Global Ecology and Biogeography, 2022)
Abstract Aim Plant biomass allocation reflects the distribution of photosynthates among different organs in response to changing environmental conditions. Global change influences plant growth across terrestrial ecosystems, but impacts of individual and combined multiple global change factors (GCFs) on plant biomass allocation at the global scale are unclear. Location Global. Time period Contemporary. Major taxa studied Plants in terrestrial ecosystems. Methods We conducted a meta‐analysis of data comprising 4,180 pairwise observations to assess individual and combined effects of nitrogen addition (N), warming (W), elevated CO 2 (C), irrigation (I), and drought (D) on plant biomass allocation based on the ‘ratio‐based optimal partitioning’ and ‘isometric allocation’ hypotheses. Results We found that (a) ratio‐based plant biomass fractions of different organs were only minimally affected by individual and combined effects of the studied GCFs; (b) combined effects of two‐factor pairs of GCFs on plant biomass allocation were commonly additive, rather than synergistic or antagonistic; (c) moderator variables influenced, but seldom changed the direction of individual and combined effects of GCFs on plant biomass allocation; and (d) neither individual nor combined effects of the studied GCFs altered allometric relationships among different organs, indicating that patterns of plant biomass allocation under the environmental stress conditions exerted by the multiple GCFs were better explained by the isometric allocation rather than the ratio‐based optimal partitioning hypothesis. Main conclusions Our results show consistent patterns of allometric plant biomass partitioning under effects of multiple GCFs and provide evidence of an isometric plant biomass allocation trajectory in response to global change perturbations. These findings improve our understanding and prediction of terrestrial vegetation responses to future global change scenarios.

The role of industrial nitrogen in the global nitrogen biogeochemical cycle - Gu, Baojing; Chang, Jie; Min, Yong; Ge, Ying; Zhu, Qiuan; Galloway, James N.; Peng, Changhui (Scientific Reports, 2013)

Elevated UV-B radiation increased the decomposition of Cinnamomum camphora and Cyclobalanopsis glauca leaf litter in subtropical China - Song, Xinzhang Z.; Zhang, Huiling L.; Chang, Scott X.; Jiang, Hong; Peng, Changhui H.; Yu, Shuquan Q. (Journal of Soils and Sediments, 2012)

Development of TRIPLEX-Management model for simulating the response of forest growth to pre-commercial thinning - Wang, Weifeng; Peng, Changhui; Zhang, S.Y.; Zhou, Xiaolu; Larocque, Guy R.; Kneeshaw, Daniel D.; Lei, Xiangdong (Ecological Modelling, 2011)

Constructed wetlands in China: recent developments and future challenges - Liu, Dong; Ge, Ying; Chang, Jie; Peng, Changhui; Gu, Binhe; Chan, Gilbert Ys; Wu, Xiaofu (Frontiers in Ecology and the Environment, 2009)
Constructed wetlands (CWs) are an emerging, environmentally friendly engineering system employed in China. They require lower investment and operation costs while providing higher treatment efficiency and more ecosystem services than conventional wastewater treatment methods. Introduced to China in 1987, CW systems used for wastewater treatment have rapidly increased in number, particularly since the late 1990s. This review summarizes the state‐of‐the‐art application of CW systems for water pollution treatment by reviewing the basics of the technology and its historical development and performance efficiency. Current progress, limitations, future concerns, and the challenges of CW technologies are also discussed. Also highlighted is the need for sufficient and appropriate data to assist in the further development of CW systems and the implementation of integrated “bottom‐up” and “top‐down” approaches by both the public in general and government bodies in particular.

Allocation Mechanisms of Non-Structural Carbohydrates of Robinia pseudoacacia L. Seedlings in Response to Drought and Waterlogging - Yang, Bin; Peng, Changhui; Harrison, Sandy P.; Wei, Hua; Wang, Han; Zhu, Qiuan; Wang, Meng (Forests, 2018)
Climate change is likely to lead to an increased frequency of droughts and floods, both of which are implicated in large-scale carbon allocation and tree mortality worldwide. Non-structural carbohydrates (NSCs) play an important role in tree survival under stress, but how NSC allocation changes in response to drought or waterlogging is still unclear. We measured soluble sugars (SS) and starch in leaves, twigs, stems and roots of Robinia pseudoacacia L. seedlings that had been subjected to a gradient in soil water availability from extreme drought to waterlogged conditions for a period of 30 days. Starch concentrations decreased and SS concentrations increased in tissues of R. pseudoacacia seedlings, such that the ratio of SS to starch showed a progressive increase under both drought and waterlogging stress. The strength of the response is asymmetric, with the largest increase occurring under extreme drought. While the increase in SS concentration in response to extreme drought is the largest in roots, the increase in the ratio of SS to starch is the largest in leaves. Individual components of SS showed different responses to drought and waterlogging across tissues: glucose concentrations increased significantly with drought in all tissues but showed little response to waterlogging in twigs and stems; sucrose and fructose concentrations showed marked increases in leaves and roots in response to drought but a greater response to drought and waterlogging in stems and twigs. These changes are broadly compatible with the roles of individual SS under conditions of water stress. While it is important to consider the role of NSC in buffering trees against mortality under stress, modelling this behaviour is unlikely to be successful unless it accounts for different responses within organs and the type of stress involved.

Photosynthetic responses to altitude: an explanation based on optimality principles - Wang, Han; Prentice, I. Colin; Davis, Tyler W.; Keenan, Trevor F.; Wright, Ian J.; Peng, Changhui (New Phytologist, 2017)

Application of the ecosystem model and Markov Chain Monte Carlo for parameter estimation and productivity prediction - Li, Weizhong; Peng, Changhui; Zhou, Xiaolu; Sun, Jianfeng; Zhu, Qiuan; Wu, Haibin; St-Onge, Benoit (Ecosphere, 2015)
It is increasingly being recognized that global ecological research requires novel methods and strategies in which to combine process‐based ecological models and data in cohesive, systematic ways. In process‐based model applications, inherent spatial and temporal heterogeneities found within terrestrial ecosystems may lead to the uncertainties of model predictions. To reduce simulation uncertainties due to inaccurate model parameters, the Markov Chain Monte Carlo (MCMC) method was applied in this study to improve the estimations of four key parameters used in the process‐based ecosystem model of TRIPLEX‐FLUX. These four key parameters include a maximum photosynthetic carboxylation rate of 25°C (Vmax), an electron transport (Jmax) light‐saturated rate within the photosynthetic carbon reduction cycle of leaves, a coefficient of stomatal conductance (m), and a reference respiration rate of 10°C (R10). Seven forest flux tower sites located across North America were used to investigate and facilitate understanding of the daily variation in model parameters for three deciduous forests, three evergreen temperate forests, and one evergreen boreal forest. Eddy covariance CO 2 exchange measurements were assimilated to optimize the parameters in the year 2006. After parameter optimization and adjustment took place, net ecosystem production prediction significantly improved (by approximately 25%) compared to the CO 2 flux measurements taken at the seven forest ecosystem sites. Results suggest that greater seasonal variability occurs in broadleaf forests in respect to the selected parameters than in needleleaf forests. This study also demonstrated that the model‐data fusion approach by incorporating MCMC method is able to better estimate parameters and improve simulation accuracy for different ecosystems located across North America.

Soil GHG fluxes are altered by N deposition: New data indicate lower N stimulation of the N2 O flux and greater stimulation of the calculated C pools - Deng, Lei; Huang, Chunbo; Kim, Dong‐Gill; Shangguan, Zhouping; Wang, Kaibo; Song, Xinzhang; Peng, Changhui (Global Change Biology, 2020)
Abstract The effects of nitrogen (N) deposition on soil organic carbon (C) and greenhouse gas (GHG) emissions in terrestrial ecosystems are the main drivers affecting GHG budgets under global climate change. Although many studies have been conducted on this topic, we still have little understanding of how N deposition affects soil C pools and GHG budgets at the global scale. We synthesized a comprehensive dataset of 275 sites from multiple terrestrial ecosystems around the world and quantified the responses of the global soil C pool and GHG fluxes induced by N enrichment. The results showed that the soil organic C concentration and the soil CO 2 , CH 4 and N 2 O emissions increased by an average of 3.7%, 0.3%, 24.3% and 91.3% under N enrichment, respectively, and that the soil CH 4 uptake decreased by 6.0%. Furthermore, the percentage increase in N 2 O emissions (91.3%) was two times lower than that (215%) reported by Liu and Greaver ( Ecology Letters , 2009, 12:1103–1117). There was also greater stimulation of soil C pools (15.70 kg C ha −1 year −1 per kg N ha −1 year −1 ) than previously reported under N deposition globally. The global N deposition results showed that croplands were the largest GHG sources (calculated as CO 2 equivalents), followed by wetlands. However, forests and grasslands were two important GHG sinks. Globally, N deposition increased the terrestrial soil C sink by 6.34 Pg CO 2 /year. It also increased net soil GHG emissions by 10.20 Pg CO 2 ‐Geq (CO 2 equivalents)/year. Therefore, N deposition not only increased the size of the soil C pool but also increased global GHG emissions, as calculated by the global warming potential approach.

Aerial spraying of bacterial insecticides to control spruce budworm defoliation leads to reduced carbon losses - Liu, Zelin; Peng, Changhui; De Grandpré, Louis; Candau, Jean‐Noël; Work, Timothy; Zhou, Xiaolu; Kneeshaw, Daniel (Ecosphere, 2020)
Abstract Spruce budworm (SBW) outbreaks are a major natural disturbance in boreal forests of eastern North America. During large‐scale infestations, aerial spraying of bacterial insecticides is used to suppress local high‐density SBW populations. While the primary goal of spraying is the protection of wood volume for later harvest, it should also maintain carbon stored in trees. This study provides the first quantitative analysis of the efficacy of aerial spraying against SBW on carbon dynamics in balsam fir, spruce, and mixed fir–spruce forests. In this study, we used the TRIPLEX‐Insect model to simulate carbon dynamics with and without spray applications in 14 sites of the boreal forest located in various regions of Québec. We found that the efficacy of aerial spraying on reducing annual defoliation was greater in the early stage (<5 yr since the outbreak began) of the outbreak than in later (5–10 yr since the outbreak began) stage. Our results showed that more net ecosystem productivity is maintained in balsam fir (the most vulnerable species) than in either spruce or mixed fir–spruce forests following spraying. Also, average losses in aboveground biomass due to the SBW following spraying occurred more slowly than without spraying in balsam fir forests. Our findings suggest that aerial spraying could be used to maintain carbon in conifer forests during SBW disturbances, but that the efficacy of spray programs is affected by host species and stage of the SBW outbreak.

Differences of soil CO2 flux in two contrasting subalpine ecosystems on the eastern edge of the Qinghai-Tibetan Plateau: A four-year study - Duan, Min; Li, Andi; Wu, Yanhong; Zhao, Zuoping; Peng, Changhui; DeLuca, Thomas H.; Sun, Shouqin (Atmospheric Environment, 2019)

Structural and functional differentiation of the microbial community in the surface and subsurface peat of two minerotrophic fens in China - Wang, Meng; Tian, Jianqing; Bu, Zhaojun; Lamit, Louis J.; Chen, Huai; Zhu, Qiuan; Peng, Changhui (Plant and Soil, 2019)

Simulation and Analysis of the Effect of a Spruce Budworm Outbreak on Carbon Dynamics in Boreal Forests of Quebec - Liu, Zelin; Peng, Changhui; De Grandpré, Louis; Candau, Jean-Noël; Work, Timothy; Huang, Chunbo; Kneeshaw, Daniel (Ecosystems, 2019)

Dynamic carbon allocation trade‐off: A robust approach to model tree biomass allometry - Yang, Mingxia; Zhou, Xiaolu; Liu, Zelin; Li, Peng; Liu, Caixia; Huang, Huabing; Tang, Jiayi; Zhang, Cicheng; Zou, Ziying; Xie, Binggeng; Peng, Changhui (Methods in Ecology and Evolution, 2024)
Abstract Forest above‐ground biomass (AGB) is often estimated by converting the observed tree size using allometric scaling between the dry weight and size of an organism. However, the variations in biomass allocation and scaling between tree crowns and stems due to survival competition during a tree's lifecycle remain unclear. This knowledge gap can improve the understanding of modelling tree biomass allometry because traditional allometries ignore the dynamics of allocation. Herein, we characterised allometric scaling using the dynamic ratio ( r ) of the stem biomass (SB) to AGB and a dynamic exponent. The allometric models were biologically parameterised by the r values for initial, intermediate and final ages rather than only a regression result. The scaling was tested using field measurements of 421 species and 2213 different‐sized trees in pantropical regions worldwide. We found that the scaling fluctuated with tree size, and this fluctuation was driven by the trade‐off relationship of biomass allocation between the tree crown and stem depending on the dynamic crown trait. The allometric scaling between SB and AGB varied from 0.8 to 1.0 for a tree during its entire lifecycle. The fluctuations presented a general law for the allometric scaling of the pantropical tree biomass and size. Our model quantified the trade‐off and explained 94.1% of the allometric relationship between the SB and AGB (93.8% of which between D 2 H and AGB) for pantropical forests, which resulted in a better fit than that of the traditional model. Considering the effects of the trade‐off on modelling, the actual biomass of large trees could be substantially greater than conventional estimates. These results highlight the importance of coupling growth mechanisms in modelling allometry and provide a theoretical foundation for better describing and predicting forest carbon accumulation.

Effects of Increased Nitrogen Deposition and Rotation Length on Long-Term Productivity of Cunninghamia lanceolata Plantation in Southern China - Zhao, Meifang; Xiang, Wenhua; Tian, Dalun; Deng, Xiangwen; Huang, Zhihong; Zhou, Xiaolu; Peng, Changhui (PLoS ONE, 2013)

Effects of future climate change, CO2 enrichment, and vegetation structure variation on hydrological processes in China - Zhu, Qiuan; Jiang, Hong; Peng, Changhui; Liu, Jinxun; Fang, Xiuqin; Wei, Xiaohua; Liu, Shirong; Zhou, Guomo (Global and Planetary Change, 2012)

General allometric equations and biomass allocation of Pinus massoniana trees on a regional scale in southern China - Xiang, Wenhua; Liu, Shaohui; Deng, Xiangwen; Shen, Aihua; Lei, Xiangdong; Tian, Dalun; Zhao, Meifang; Peng, Changhui (Ecological Research, 2011)
Abstract Applying allometric equations in combination with forest inventory data is an effective approach to use when qualifying forest biomass and carbon storage on a regional scale. The objectives of this study were to (1) develop general allometric tree component biomass equations and (2) investigate tree biomass allocation patterns for Pinus massoniana , a principal tree species native to southern China, by applying 197 samples across 20 site locations. The additive allometric equations utilized to compute stem, branch, needle, root, aboveground, and total tree biomass were developed by nonlinear seemingly unrelated regression. Results show that the relative proportion of stem biomass to tree biomass increased while the contribution of canopy biomass to tree biomass decreased as trees continued to grow through time. Total root biomass was a large biomass pool in itself, and its relative proportion to tree biomass exhibited a slight increase with tree growth. Although equations employing stem diameter at breast height (dbh) alone as a predictor could accurately predict stem, aboveground, root, and total tree biomass, they were poorly fitted to predict the canopy biomass component. The inclusion of the tree height ( H ) variable either slightly improved or did not in any way increase model fitness. Validation results demonstrate that these equations are suitable to estimate stem, aboveground, and total tree biomass across a broad range of P . massoniana stands on a regional scale.

Selected papers presented in symposia organized at the 2009 conference of the International Society for Ecological Modelling (ISEM) in Quebec City, Canada, October 6–9, 2009 - Larocque, Guy R.; Yue, Tian-Xiang; Peng, Changhui; Bhatti, Jagtar; Etterson, Matthew A.; Kazanci, Caner; Goethals, Peter (Ecological Modelling, 2011)

Leaf respiration/photosynthesis relationship and variation: an investigation of 39 woody and herbaceous species in east subtropical China - Chu, Ziyan; Lu, Yijun; Chang, Jie; Wang, Meng; Jiang, Hong; He, Jinsheng; Peng, Changhui; Ge, Ying (Trees, 2011)

Heavy metal accumulation by panicled goldenrain tree (Koelreuteria paniculata) and common elaeocarpus (Elaeocarpus decipens) in abandoned mine soils in southern China - Tian, Dalun; Zhu, Fan; Yan, Wende; Xi, Fang; Xiang, Wenhua; Deng, Xiangwen; Wang, Guangjun; Peng, Changhui (Journal of Environmental Sciences, 2009)

CH4 concentrations and fluxes in a subtropical metropolitan river network: Watershed urbanization impacts and environmental controls - Wang, Xiaofeng; He, Yixin; Chen, Huai; Yuan, Xingzhong; Peng, Changhui; Yue, Junsheng; Zhang, Qiaoyong; Zhou, Lilei (Science of The Total Environment, 2018)

C:N:P stoichiometry of plants, soils, and microorganisms: Response to altered precipitation - Li, Jiwei; Deng, Lei; Peñuelas, Josep; Wu, Jianzhao; Shangguan, Zhouping; Sardans, Jordi; Peng, Changhui; Kuzyakov, Yakov (Global Change Biology, 2023)
Abstract Precipitation changes modify C, N, and P cycles, which regulate the functions and structure of terrestrial ecosystems. Although altered precipitation affects above‐ and belowground C:N:P stoichiometry, considerable uncertainties remain regarding plant–microbial nutrient allocation strategies under increased (IPPT) and decreased (DPPT) precipitation. We meta‐analyzed 827 observations from 235 field studies to investigate the effects of IPPT and DPPT on the C:N:P stoichiometry of plants, soils, and microorganisms. DPPT reduced leaf C:N ratio, but increased the leaf and root N:P ratios reflecting stronger decrease of P compared with N mobility in soil under drought. IPPT increased microbial biomass C (+13%), N (+15%), P (26%), and the C:N ratio, whereas DPPT decreased microbial biomass N (−12%) and the N:P ratio. The C:N and N:P ratios of plant leaves were more sensitive to medium DPPT than to IPPT because drought increased plant N content, particularly in humid areas. The responses of plant and soil C:N:P stoichiometry to altered precipitation did not fit the double asymmetry model with a positive asymmetry under IPPT and a negative asymmetry under extreme DPPT. Soil microorganisms were more sensitive to IPPT than to DPPT, but they were more sensitive to extreme DPPT than extreme IPPT, consistent with the double asymmetry model. Soil microorganisms maintained stoichiometric homeostasis, whereas N:P ratios of plants follow that of the soils under altered precipitation. In conclusion, specific N allocation strategies of plants and microbial communities as well as N and P availability in soil critically mediate C:N:P stoichiometry by altered precipitation that need to be considered by prediction of ecosystem functions and C cycling under future climate change scenarios.

Divergent response of leaf unfolding to climate warming in subtropical and temperate zones - Yu, Haiying; Yang, Lilin; Wang, Zuhua; Guo, Liang; Peng, Changhui; Yao, Qifu; Mo, Zhongmei; Tan, Tinghong (Agricultural and Forest Meteorology, 2023)

The carbon flux of global rivers: A re-evaluation of amount and spatial patterns - Li, Mingxu; Peng, Changhui; Wang, Meng; Xue, Wei; Zhang, Kerou; Wang, Kefeng; Shi, Guohua; Zhu, Qiuan (Ecological Indicators, 2017)

Simulated effects of nitrogen saturation on the global carbon budget using the IBIS model - Lu, Xuehe; Jiang, Hong; Liu, Jinxun; Zhang, Xiuying; Jin, Jiaxin; Zhu, Qiuan; Zhang, Zhen; Peng, Changhui (Scientific Reports, 2016)
Abstract Over the past 100 years, human activity has greatly changed the rate of atmospheric N (nitrogen) deposition in terrestrial ecosystems, resulting in N saturation in some regions of the world. The contribution of N saturation to the global carbon budget remains uncertain due to the complicated nature of C-N (carbon-nitrogen) interactions and diverse geography. Although N deposition is included in most terrestrial ecosystem models, the effect of N saturation is frequently overlooked. In this study, the IBIS (Integrated BIosphere Simulator) was used to simulate the global-scale effects of N saturation during the period 1961–2009. The results of this model indicate that N saturation reduced global NPP (Net Primary Productivity) and NEP (Net Ecosystem Productivity) by 0.26 and 0.03 Pg C yr −1 , respectively. The negative effects of N saturation on carbon sequestration occurred primarily in temperate forests and grasslands. In response to elevated CO 2 levels, global N turnover slowed due to increased biomass growth, resulting in a decline in soil mineral N. These changes in N cycling reduced the impact of N saturation on the global carbon budget. However, elevated N deposition in certain regions may further alter N saturation and C-N coupling.

A global meta-analysis of changes in soil carbon, nitrogen, phosphorus and sulfur, and stoichiometric shifts after forestation - Shi, Shengwei; Peng, Changhui; Wang, Meng; Zhu, Qiuan; Yang, Gang; Yang, Yanzheng; Xi, Tingting; Zhang, Tinglong (Plant and Soil, 2016)

Estimating global natural wetland methane emissions using process modelling: spatio‐temporal patterns and contributions to atmospheric methane fluctuations - Zhu, Qiuan; Peng, Changhui; Chen, Huai; Fang, Xiuqin; Liu, Jinxun; Jiang, Hong; Yang, Yanzheng; Yang, Gang (Global Ecology and Biogeography, 2015)
Abstract Aim The fluctuations of atmospheric methane ( CH 4 ) that have occurred in recent decades are not fully understood, particularly with regard to the contribution from wetlands. The application of spatially explicit parameters has been suggested as an effective method for reducing uncertainties in bottom‐up approaches to wetland CH 4 emissions, but has not been included in recent studies. Our goal was to estimate spatio‐temporal patterns of global wetland CH 4 emissions using a process model and then to identify the contribution of wetland emissions to atmospheric CH 4 fluctuations. Location Global. Methods A process‐based model integrated with full descriptions of methanogenesis ( TRIPLEX‐GHG ) was used to simulate global wetland CH 4 emissions. Results Global annual wetland CH 4 emissions ranged from 209 to 245 T g CH 4 year −1 between 1901 and 2012, with peaks occurring in 1991 and 2012. There is a decreasing trend between 1990 and 2010 with a rate of approximately 0.48 T g CH 4 year −1 , which was largely caused by emissions from tropical wetlands showing a decreasing trend of 0.44 T g CH 4 year −1 since the 1970s. Emissions from tropical, temperate and high‐latitude wetlands comprised 59, 26 and 15% of global emissions, respectively. Main conclusion Global wetland CH 4 emissions, the interannual variability of which was primary controlled by tropical wetlands, partially drive the atmospheric CH 4 burden. The stable to decreasing trend in wetland CH 4 emissions, a result of a balance of emissions from tropical and extratropical wetlands, was a particular factor in slowing the atmospheric CH 4 growth rate during the 1990s. The rapid decrease in tropical wetland CH 4 emissions that began in 2000 was supposed to offset the increase in anthropogenic emissions and resulted in a relatively stable level of atmospheric CH 4 from 2000 to 2006. Increasing wetland CH 4 emissions, particularly after 2010, should be an important contributor to the growth in atmospheric CH 4 seen since 2007.

Monitoring the impact of aerosol contamination on the drought-induced decline of gross primary productivity - Zhang, Yao; Li, Weizhong; Zhu, Qiuan; Chen, Huai; Fang, Xiuqin; Zhang, Tinglong; Zhao, Pengxiang; Peng, Changhui (International Journal of Applied Earth Observation and Geoinformation, 2015)

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009 - Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui (Journal of Applied Remote Sensing, 2014)

Quantification of soil respiration in forest ecosystems across China - Song, Xinzhang; Peng, Changhui; Zhao, Zhengyong; Zhang, Zhiting; Guo, Baohua; Wang, Weifeng; Jiang, Hong; Zhu, Qiuan (Atmospheric Environment, 2014)

High carbon dioxide uptake by subtropical forest ecosystems in the East Asian monsoon region - Yu, Guirui; Chen, Zhi; Piao, Shilong; Peng, Changhui; Ciais, Philippe; Wang, Qiufeng; Li, Xuanran; Zhu, Xianjin (Proceedings of the National Academy of Sciences, 2014)
Significance Understanding the location of carbon sources and sinks is essential for accurately predicting future changes in atmospheric carbon dioxide and climate. Mid- to high-latitude terrestrial ecosystems are well known to be the principal carbon sink regions, yet less attention has been paid to the mid- to low-latitude ecosystems. In this study, long-term eddy covariance observations demonstrate that there is a high carbon dioxide uptake (net ecosystem productivity) by the mid- to low-latitude East Asian monsoon subtropical forests that were shaped by the uplift of the Tibetan Plateau. Increasing nitrogen deposition, a young forest age structure, and sufficient water and heat availability combined to contribute to this large carbon dioxide uptake. , Temperate- and high-latitude forests have been shown to contribute a carbon sink in the Northern Hemisphere, but fewer studies have addressed the carbon balance of the subtropical forests. In the present study, we integrated eddy covariance observations established in the 1990s and 2000s to show that East Asian monsoon subtropical forests between 20°N and 40°N represent an average net ecosystem productivity (NEP) of 362 ± 39 g C m −2 yr −1 (mean ± 1 SE). This average forest NEP value is higher than that of Asian tropical and temperate forests and is also higher than that of forests at the same latitudes in Europe–Africa and North America. East Asian monsoon subtropical forests have comparable NEP to that of subtropical forests of the southeastern United States and intensively managed Western European forests. The total NEP of East Asian monsoon subtropical forests was estimated to be 0.72 ± 0.08 Pg C yr −1 , which accounts for 8% of the global forest NEP. This result indicates that the role of subtropical forests in the current global carbon cycle cannot be ignored and that the regional distributions of the Northern Hemisphere's terrestrial carbon sinks are needed to be reevaluated. The young stand ages and high nitrogen deposition, coupled with sufficient and synchronous water and heat availability, may be the primary reasons for the high NEP of this region, and further studies are needed to quantify the contribution of each underlying factor.

Applying an artificial neural network to simulate and predict Chinese fir (Cunninghamia lanceolata) plantation carbon flux in subtropical China - Wen, Xuding; Zhao, Zhonghui; Deng, Xiangwen; Xiang, Wenhua; Tian, Dalun; Yan, Wende; Zhou, Xiaolu; Peng, Changhui (Ecological Modelling, 2014)

Monitoring and estimating drought-induced impacts on forest structure, growth, function, and ecosystem services using remote-sensing data: recent progress and future challenges - Zhang, Yao; Peng, Changhui; Li, Weizhong; Fang, Xiuqin; Zhang, Tinglong; Zhu, Qiuan; Chen, Huai; Zhao, Pengxiang (Environmental Reviews, 2013)
Alongside global warming, droughts are expected to increase in frequency, severity, and extent in the near future, which will likely result in significant impacts on forest growth, production, structure, composition, and ecosystem services. However, due to spatial and temporal characteristics, it is difficult to monitor and assess the potential effects of droughts. Remote sensing can provide an effective way to obtain real-time conditions of forests affected by drought and offer a range of spatial and temporal insights into drought-induced changes to forest ecosystem structure, function, and services. Remote sensing is rapidly developing as more satellites are launched. In situ and remotely sensed data fusion techniques have achieved notable success in assessing drought-induced damage to forests and carbon cycles. Even so, constraints still exist when using satellite data. The objectives of this review are to (1) briefly review existing data sources and methods of remote sensing; (2) synthesize current applications and contributions of remote sensing in monitoring and estimating impacts of droughts on forest ecosystems; and (3) highlight research gaps and future challenges.

Stumps increased soil respiration in a subtropical Moso bamboo (Phyllostachys edulis) plantation under nitrogen addition - Li, Quan; Ma, Qiuhui; Gao, Jinpei; Zhang, Junbo; Li, Yongfu; Shi, Man; Peng, Changhui; Song, Xinzhang (Agricultural and Forest Meteorology, 2022)

Biochar amendments increase soil organic carbon storage and decrease global warming potentials of soil CH4 and N2O under N addition in a subtropical Moso bamboo plantation - Li, Quan; Cui, Kunkai; Lv, Jianhua; Zhang, Junbo; Peng, Changhui; Li, Yongfu; Gu, Zhikang; Song, Xinzhang (Forest Ecosystems, 2022)

Tillage activates iron to prevent soil organic carbon loss following forest conversion to cornfields in tropical acidic red soils - Zong, Mingming; Lin, Chen; Li, Shiyu; Li, Haixia; Duan, Changqun; Peng, Changhui; Guo, Yongxing; An, Ruiqi (Science of The Total Environment, 2021)

Management scheme influence and nitrogen addition effects on soil CO2, CH4, and N2O fluxes in a Moso bamboo plantation - Zhang, Junbo; Li, Quan; Lv, Jianhua; Peng, Changhui; Gu, Zhikang; Qi, Lianghua; Song, Xuzhong; Song, Xinzhang (Forest Ecosystems, 2021)
Abstract Background It is still not clear whether the effects of N deposition on soil greenhouse gas (GHG) emissions are influenced by plantation management schemes. A field experiment was conducted to investigate the effects of conventional management (CM) versus intensive management (IM), in combination with simulated N deposition levels of control (ambient N deposition), 30 kg N·ha − 1 ·year − 1 (N30, ambient + 30 kg N·ha − 1 ·year − 1 ), 60 kg N·ha − 1 ·year − 1 (N60, ambient + 60 kg N·ha − 1 ·year − 1 ), or 90 kg N·ha − 1 ·year − 1 (N90, ambient + 90 kg N·ha − 1 ·year − 1 ) on soil CO 2 , CH 4 , and N 2 O fluxes. For this, 24 plots were set up in a Moso bamboo ( Phyllostachys edulis ) plantation from January 2013 to December 2015. Gas samples were collected monthly from January 2015 to December 2015. Results Compared with CM, IM significantly increased soil CO 2 emissions and their temperature sensitivity ( Q 10 ) but had no significant effects on soil CH 4 uptake or N 2 O emissions. In the CM plots, N30 and N60 significantly increased soil CO 2 emissions, while N60 and N90 significantly increased soil N 2 O emissions. In the IM plots, N30 and N60 significantly increased soil CO 2 and N 2 O emissions, while N60 and N90 significantly decreased soil CH 4 uptake. Overall, in both CM and IM plots, N30 and N60 significantly increased global warming potentials, whereas N90 did not significantly affect global warming potential. However, N addition significantly decreased the Q 10 value of soil CO 2 emissions under IM but not under CM. Soil microbial biomass carbon was significantly and positively correlated with soil CO 2 and N 2 O emissions but significantly and negatively correlated with soil CH 4 uptake. Conclusion Our results indicate that management scheme effects should be considered when assessing the effect of atmospheric N deposition on GHG emissions in bamboo plantations.

Evaluation of Future Impacts of Climate Change, CO2, and Land Use Cover Change on Global Net Primary Productivity Using a Processed Model - Hu, Xiao; He, Yujie; Kong, Ze; Zhang, Jiang; Yuan, Minshu; Yu, Le; Peng, Changhui; Zhu, Qiuan (Land, 2021)
Few studies have focused on the combined impact of climate change, CO2, and land-use cover change (LUCC), especially the evaluation of the impact of LUCC on net primary productivity (NPP) in the future. In this study, we simulated the overall NPP change trend from 2010 to 2100 and its response to climatic factors, CO2 concentration, and LUCC conditions under three typical emission scenarios (Representative Concentration Pathway RCP2.6, RCP4.5, and RCP8.5). (1) Under the predicted global pattern, NPP showed an increasing trend, with the most prominent variation at the end of the century. The increasing trend is mainly caused by the positive effect of CO2 on NPP. However, the increasing trend of LUCC has only a small positive effect. (2) Under the RCP 8.5 scenario, from 2090 to 2100, CO2 has the most significant positive impact on tropical areas, reaching 8.328 Pg C Yr−1. Under the same conditions, climate change has the greatest positive impact on the northern high latitudes (1.175 Pg C Yr−1), but it has the greatest negative impact on tropical areas, reaching −4.842 Pg C Yr−1. (3) The average contribution rate of LUCC to NPP was 6.14%. Under the RCP8.5 scenario, LUCC made the largest positive contribution on NPP (0.542 Pg C Yr−1) globally from 2010 to 2020.

Observed Methane Uptake and Emissions at the Ecosystem Scale and Environmental Controls in a Subtropical Forest - Wang, Hui; Li, Hong; Liu, Zhihao; Lv, Jianhua; Song, Xinzhang; Li, Quan; Jiang, Hong; Peng, Changhui (Land, 2021)
Methane (CH4) is one of the three most important greenhouse gases. To date, observations of ecosystem-scale methane (CH4) fluxes in forests are currently lacking in the global CH4 budget. The environmental factors controlling CH4 flux dynamics remain poorly understood at the ecosystem scale. In this study, we used a state-of-the-art eddy covariance technique to continuously measure the CH4 flux from 2016 to 2018 in a subtropical forest of Zhejiang Province in China, quantify the annual CH4 budget and investigate its control factors. We found that the total annual CH4 budget was 1.15 ± 0.28~4.79 ± 0.49 g CH4 m−2 year−1 for 2017–2018. The daily CH4 flux reached an emission peak of 0.145 g m−2 d−1 during winter and an uptake peak of −0.142 g m−2 d−1 in summer. During the whole study period, the studied forest region acted as a CH4 source (78.65%) during winter and a sink (21.35%) in summer. Soil temperature had a negative relationship (p < 0.01; R2 = 0.344) with CH4 flux but had a positive relationship with soil moisture (p < 0.01; R2 = 0.348). Our results showed that soil temperature and moisture were the most important factors controlling the ecosystem-scale CH4 flux dynamics of subtropical forests in the Tianmu Mountain Nature Reserve in Zhejiang Province, China. Subtropical forest ecosystems in China acted as a net source of methane emissions from 2016 to 2018, providing positive feedback to global climate warming.

Leaf Trait Covariation and Its Controls: A Quantitative Data Analysis Along a Subtropical Elevation Gradient - Yang, Yanzheng; Gou, Ruikun; Li, Wei; Kassout, Jalal; Wu, Jun; Wang, Liming; Peng, Changhui; Lin, Guanghui (Journal of Geophysical Research: Biogeosciences, 2021)
Abstract Elevation gradients are frequently treated as useful space‐for‐time substitutions for inferring trait variations in response to different environmental conditions. The independent variations in leaf traits in response to elevation are well understood, but far less is known about trait covariation and its controls. This limits our understanding of the principles and mechanisms of leaf trait covariation, especially along elevation gradients in subtropical forests. Here, we studied the covariation among seven functional traits, including leaf size (LS), leaf nitrogen per unit mass ( N mass ), leaf nitrogen per unit area ( N area ), leaf mass per area (LMA), leaf dry matter content (LDMC), leaf thickness (LT) and the leaf internal‐to‐ambient CO 2 ratio ( C i : C a , termed χ ). Sampling was conducted on 41 species in a subtropical forest on Mount Huangshan, China, and the data were analyzed using multivariate analysis and variance partitioning procedures. We found that (a) The first three principal components captured 79% of the total leaf trait covariation, which was caused mainly by within site differences; (b) N mass and LDMC were positively correlated with soil water content (SW) and negatively correlated with vapor pressure deficit (VPD), while χ showed negative relationships with elevation; and (c) 78% of the variation in the studied plant functional traits could be explained by climate, soil, and family controls in combination, while family distribution was the most important determining factor for trait covariation along the elevation gradient. Our findings provide relevant insights into plant adaptation to environmental gradients and present useful guidelines for ecosystem management and planning. , Plain Language Summary Changes of plant functional traits along elevation gradient are important indicators which reflect the behaviors and adaptations of plants. In this study we first analyzed the dominant signals of seven leaf functional traits and then we depicted the response of seven traits to changing elevation environments, and finally we quantified the contributions of climate, soil, and vegetation distribution. Our findings validate the hypothesis that trait covariation, and thus adaptation, occurs in response to the elevation gradients that most plant species experience. , Key Points The first three principal components captured 79% of the total leaf trait covariation Leaf nitrogen content ( N mass ) and leaf dry mass content (LDMC) were positively correlated with soil water content and negatively correlated with vapor pressure deficit Vegetation (family) distribution was the most important determining factor for trait covariation along the elevation gradient

No evidence for carryover effect in tree rings based on a pulse-labelling experiment on Juniperus communis in South Germany - He, Minhui; Bräuning, Achim; Rossi, Sergio; Gebrekirstos, Aster; Grießinger, Jussi; Mayr, Christoph; Peng, Changhui; Yang, Bao (Trees, 2021)

Nitrogen addition increased CO2 uptake more than non-CO2 greenhouse gases emissions in a Moso bamboo forest - Song, Xinzhang; Peng, Changhui; Ciais, Philippe; Li, Quan; Xiang, Wenhua; Xiao, Wenfa; Zhou, Guomo; Deng, Lei (Science Advances, 2020)
Moso bamboo forests have greater net carbon uptake benefits with increasing nitrogen deposition in the coming decades. , Atmospheric nitrogen (N) deposition affects the greenhouse gas (GHG) balance of ecosystems through the net atmospheric CO 2 exchange and the emission of non-CO 2 GHGs (CH 4 and N 2 O). We quantified the effects of N deposition on biomass increment, soil organic carbon (SOC), and N 2 O and CH 4 fluxes and, ultimately, the net GHG budget at ecosystem level of a Moso bamboo forest in China. Nitrogen addition significantly increased woody biomass increment and SOC decomposition, increased N 2 O emission, and reduced soil CH 4 uptake. Despite higher N 2 O and CH 4 fluxes, the ecosystem remained a net GHG sink of 26.8 to 29.4 megagrams of CO 2 equivalent hectare −1 year −1 after 4 years of N addition against 22.7 hectare −1 year −1 without N addition. The total net carbon benefits induced by atmospheric N deposition at current rates of 30 kilograms of N hectare −1 year −1 over Moso bamboo forests across China were estimated to be of 23.8 teragrams of CO 2 equivalent year −1 .

Dynamics of soil water extractable organic carbon and inorganic nitrogen and their environmental controls in mountain forest and meadow ecosystems in China - Zhang, Junjun; Peng, Changhui; Xue, Wei; Yang, Bin; Yang, Zhenan; Niu, Shuli; Zhu, Qiuan; Wang, Meng (CATENA, 2020)

High uncertainties detected in the wetlands distribution of the Qinghai–Tibet Plateau based on multisource data - Wang, Jieyi; Zhu, Qiuan; Yang, Yan; Zhang, Xian; Zhang, Jiang; Yuan, Minshu; Chen, Huai; Peng, Changhui (Landscape and Ecological Engineering, 2020)

A review of the mechanisms and controlling factors of methane dynamics in forest ecosystems - Feng, Huili; Guo, Jiahuan; Han, Menghua; Wang, Weifeng; Peng, Changhui; Jin, Jiaxin; Song, Xinzhang; Yu, Shuiqiang (Forest Ecology and Management, 2020)

Estimating soil organic carbon redistribution in three major river basins of China based on erosion processes - Yang, Yan; Zhu, Qiuan; Liu, Jinxun; Li, Mingxu; Yuan, Minshu; Chen, Huai; Peng, Changhui; Yang, Zhenan (Soil Research, 2020)
Soil erosion by water affects soil organic carbon (SOC) migration and distribution, which are important processes for defining ecosystem carbon sources and sinks. Little has been done to quantify soil carbon erosion in the three major basins in China, the Yangtze River, Yellow River and Pearl River Basins, which contain the most eroded areas. This research attempts to quantify the lateral movement of SOC based on spatial and temporal patterns of water erosion rates derived from an empirical Unit Stream Power Erosion Deposition Model (USPED) model. The water erosion rates simulated by the USPED model agreed reasonably with observations (R2 = 0.43, P < 0.01). We showed that regional water erosion ranged within 23.3–50 Mg ha–1 year–1 during 1992–2013, inducing the lateral redistribution of SOC caused by erosion in the range of 0.027–0.049 Mg C ha–1 year–1, and that caused by deposition of 0.0079–0.015 Mg C ha–1 year–1, in the three basins. The total eroded SOC was 0.006, 0.002 and 0.001 Pg year–1 in the Yangtze River, Yellow River and Pearl River Basins respectively. The net eroded SOC in the three basins was ~0.0075 Pg C year–1. Overall, the annual average redistributed SOC rate caused by erosion was greater than that caused by deposition, and the SOC loss in the Yangtze River Basin was greatest among the three basins. Our study suggests that considering both processes of erosion and deposition – as well as effects of topography, rainfall, land use types and their interactions – on these processes are important to understand SOC redistribution caused by water erosion.

Quantifying the Effects of Vegetation Restorations on the Soil Erosion Export and Nutrient Loss on the Loess Plateau - Zhao, Jun; Feng, Xiaoming; Deng, Lei; Yang, Yanzheng; Zhao, Zhong; Zhao, Pengxiang; Peng, Changhui; Fu, Bojie (Frontiers in Plant Science, 2020)
The transport of eroded soil to rivers changes the nutrient cycles of river ecosystems and has significant impacts on the regional eco-environment and human health. The Loess Plateau, a leading vegetation restoration region in China and the world, has experienced severe soil erosion and nutrient loss, however, the extent to which vegetation restoration prevents soil erosion export (to rivers) and it caused nutrient loss is unknown. To evaluate the effects of the first stage of the Grain for Green Project (GFGP) on the Loess Plateau (started in 1999 and ended in 2013), we analyzed the vegetation change trends and quantified the effects of GFGP on soil erosion export (to rivers) and it caused nutrient loss by considering soil erosion processes. The results were as follows: (1) in the first half of study period (from 1982 to 1998), the vegetation cover changed little, but after the implementation of the first stage of the GFGP (from 1999 to 2013), the vegetation cover of 75.0% of the study area showed a significant increase; (2) The proportion of eroded areas decreased from 41.8 to 26.7% as a result of the GFGP, and the erosion intensity lessened in most regions; the implementation significantly reduce the soil nutrient loss; (3) at the county level, soil erosion export could be avoided significantly by the increasing of vegetation greenness in the study area ( R = −0.49). These results illustrate the relationships among changes in vegetation cover, soil erosion and nutrient export, which could provide a reference for local government for making ecology-relative policies.

Drivers of soil microbial metabolic limitation changes along a vegetation restoration gradient on the Loess Plateau, China - Deng, Lei; Peng, Changhui; Huang, Chunbo; Wang, Kaibo; Liu, Qiuyu; Liu, Yulin; Hai, Xuying; Shangguan, Zhouping (Geoderma, 2019)

Quantifying leaf‐trait covariation and its controls across climates and biomes - Yang, Yanzheng; Wang, Han; Harrison, Sandy P.; Prentice, I. Colin; Wright, Ian J.; Peng, Changhui; Lin, Guanghui (New Phytologist, 2019)
Summary Plant functional ecology requires the quantification of trait variation and its controls. Field measurements on 483 species at 48 sites across China were used to analyse variation in leaf traits, and assess their predictability. Principal components analysis ( PCA ) was used to characterize trait variation, redundancy analysis ( RDA ) to reveal climate effects, and RDA with variance partitioning to estimate separate and overlapping effects of site, climate, life‐form and family membership. Four orthogonal dimensions of total trait variation were identified: leaf area ( LA ), internal‐to‐ambient CO 2 ratio (χ), leaf economics spectrum traits (specific leaf area ( SLA ) versus leaf dry matter content ( LDMC ) and nitrogen per area ( N area )), and photosynthetic capacities ( V cmax , J max at 25°C). LA and χ covaried with moisture index. Site, climate, life form and family together explained 70% of trait variance. Families accounted for 17%, and climate and families together 29%. LDMC and SLA showed the largest family effects. Independent life‐form effects were small. Climate influences trait variation in part by selection for different life forms and families. Trait values derived from climate data via RDA showed substantial predictive power for trait values in the available global data sets. Systematic trait data collection across all climates and biomes is still necessary.

Vegetation restoration stimulates soil carbon sequestration and stabilization in a subtropical area of southern China - Gu, Xiang; Fang, Xi; Xiang, Wenhua; Zeng, Yelin; Zhang, Shiji; Lei, Pifeng; Peng, Changhui; Kuzyakov, Yakov (CATENA, 2019)

Weakening of the ‘enzymatic latch’ mechanism following long-term fertilization in a minerotrophic peatland - Li, Tong; Bu, Zhaojun; Liu, Wenyan; Zhang, Mingying; Peng, Changhui; Zhu, Qiuan; Shi, Shengwei; Wang, Meng (Soil Biology and Biochemistry, 2019)

Assessment of frozen ground organic carbon pool on the Qinghai-Tibet Plateau - Jiang, Lin; Chen, Huai; Zhu, Qiuan; Yang, Yanzheng; Li, Mingxu; Peng, Changhui; Zhu, Dan; He, Yixin (Journal of Soils and Sediments, 2019)

Correcting the overestimate of forest biomass carbon on the national scale - Zhou, Xiaolu; Lei, Xiangdong; Peng, Changhui; Wang, Weifeng; Zhou, Carl; Liu, Caixia; Liu, Zhenggang (Methods in Ecology and Evolution, 2016)
Summary For decades, researchers have thought it was difficult to remove the uncertainty from the estimates of forest carbon storage and its changes on national sales. This is not only because of stochasticity in the data but also the bias to overcome in the computations. Most studies of the estimation, however, ignore quantitative analyses for the latter uncertainty. This bias primarily results from the widely used volume‐biomass method via scaling up forest biomass from limited sample plots to large areas. This paper addresses (i) the mechanism of scaling‐up error occurrence, and (ii) the quantitative effects of the statistical factors on the error. The error compensators were derived, and expressed by ternary functions with three variables: expectation, variance and the power in the volume‐biomass equation. This is based on analysing the effect of power‐law function convexity on scaling‐up error by solving the difference of both sides of the weighted Jensen inequality. The simulated data and the national forest inventory of China were used for algorithm testing and application, respectively. Scaling‐up error occurrence stems primarily from an effect of the distribution heterogeneity of volume density on the total biomass amount, and secondarily from the extent of function nonlinearities. In our experiments, on average 94·2% of scaling‐up error can be reduced for the statistical populations of forest stands in a region. China's forest biomass carbon was estimated as approximately 6·0 PgC or less at the beginning of the 2010s after on average 1·1% error compensation. The results of both the simulated data experiment and national‐scale estimation suggest that the biomass is overestimated for young forests more than others. It implies a necessity to compensate scaling‐up error, especially for the areas going through extensive afforestation and reforestation in past decades. This study highlights the importance of understanding how both the function nonlinearity and the statistics of the variables quantitatively affect the scaling‐up error. Generally, the presented methods will help to translate fine‐scale ecological relationships to estimate coarser scale ecosystem properties by correcting aggregation errors.

Relationship between environmental pollution and economic development in late-developing regions shows an inverted V - Yu, Yadong; Duan, Changqun; Li, Shiyu; Peng, Changhui; Yang, Jian; Yan, Kun; Bi, Xiaoyi; Zou, Ping (Science of The Total Environment, 2022)

Vegetation types and flood water level are dominant factors controlling the carbon sequestration potential in Dongting Lake floodplain, China - Wang, Tao; Deng, Zhengmiao; Zhang, Chengyi; Zou, Yeai; Xie, Yonghong; Li, Feng; Xiao, Fengjin; Peng, Changhui (Science of The Total Environment, 2024)

An optimized water table depth detected for mitigating global warming potential of greenhouse gas emissions in wetland of Qinghai-Tibetan Plateau - Zhang, Jiang; Chen, Huai; Wang, Meng; Liu, Xinwei; Peng, Changhui; Wang, Le; Yu, Dongxue; Zhu, Qiuan (iScience, 2024)

Vegetation browning: global drivers, impacts, and feedbacks - Liu, Qiuyu; Peng, Changhui; Schneider, Robert; Cyr, Dominic; Liu, Zelin; Zhou, Xiaolu; Du, Mingxi; Li, Peng; Jiang, Zihan; McDowell, Nate G.; Kneeshaw, Daniel (Trends in Plant Science, 2023)

Net fluxes of ammonium and nitrate in association with H+ fluxes in fine roots of Populus popularis - Luo, Jie; Qin, Jingjing; He, Fangfang; Li, Hong; Liu, Tongxian; Polle, Andrea; Peng, Changhui; Luo, Zhi-Bin (Planta, 2013)

Changes in carbon, nutrients and stoichiometric relations under different soil depths, plant tissues and ages in black locust plantations - Li, Hong; Li, Jing; He, Yalong; Li, Shaojun; Liang, Zongsuo; Peng, Changhui; Polle, Andrea; Luo, Zhi-Bin (Acta Physiologiae Plantarum, 2013)

Simulating carbon exchange of Canadian boreal forests - Sun, Jianfeng; Peng, Changhui; McCaughey, Harry; Zhou, Xiaolu; Thomas, Valerie; Berninger, Frank; St-Onge, Benoît.; Hua, Dong (Ecological Modelling, 2008)

Carbon fluxes and soil carbon dynamics along a gradient of biogeomorphic succession in alpine wetlands of Tibetan Plateau - Wang, Hao; Yu, Lingfei; Chen, Litong; Zhang, Zhenhua; Li, Xuefei; Liang, Naishen; Peng, Changhui; He, Jin-Sheng (Fundamental Research, 2023)

Evaluating the carbon budget pattern of Chinese terrestrial ecosystem from 1960 to 2006 using Integrated Biosphere Simulator - Yang Yanzheng, 杨延征; Ma Yuandan, 马元丹; Jiang Hong, 江洪; Zhu Qiu'an, 朱求安; Liu Jinxun, 刘金勋; Peng Changhui, 彭长辉 (Acta Ecologica Sinica, 2016)

Nitrous oxide emission from infralittoral zone and pelagic zone in a shallow lake: Implications for whole lake flux estimation and lake restoration - Zhu, Dan; Wu, Yan; Wu, Ning; Chen, Huai; He, Yixin; Zhang, Yongmei; Peng, Changhui; Zhu, Qiu'an (Ecological Engineering, 2015)

Carbon accumulation and sequestration of lakes in China during the Holocene - Wang, Mei; Chen, Huai; Yu, Zicheng; Wu, Jianghua; Zhu, Qiu'an; Peng, Changhui; Wang, Yanfen; Qin, Boqiang (Global Change Biology, 2015)
Abstract Understanding the responses of lake systems to past climate change and human activity is critical for assessing and predicting the fate of lake carbon (C) in the future. In this study, we synthesized records of the sediment accumulation from 82 lakes and of C sequestration from 58 lakes with direct organic C measurements throughout China. We also identified the controlling factors of the long‐term sediment and C accumulation dynamics in these lakes during the past 12 ka (1 ka = 1000 cal yr BP ). Our results indicated an overall increasing trend of sediment and C accumulation since 12 ka, with an accumulation peak in the last couple of millennia for lakes in China, corresponding to terrestrial organic matter input due to land‐use change. The Holocene lake sediment accumulation rate ( SAR ) and C accumulation rate ( CAR ) averaged (mean ± SE ) 0.47 ± 0.05 mm yr −1 and 7.7 ± 1.4 g C m −2 yr −1 in China, respectively, comparable to the previous estimates for boreal and temperate regions. The SAR for lakes in the East Plain of subtropical China (1.05 ± 0.28 mm yr −1 ) was higher than those in other regions ( P < 0.05). However, CAR did not vary significantly among regions. Overall, the variability and history of climate and anthropogenic interference regulated the temporal and spatial dynamics of sediment and C sequestration for lakes in China. We estimated the total amount of C burial in lakes of China as 8.0 ± 1.0 Pg C. This first estimation of total C storage and dynamics in lakes of China confirms the importance of lakes in land C budget in monsoon‐influenced regions.

Relationship between Air Pollutants and Economic Development of the Provincial Capital Cities in China during the Past Decade - Luo, Yunpeng; Chen, Huai; Zhu, Qiu'an; Peng, Changhui; Yang, Gang; Yang, Yanzheng; Zhang, Yao (PLoS ONE, 2014)

Growing season temperature and precipitation affect nutrient resorption in herbaceous species through a foliar stoichiometric control strategy - Liu, Xiaowei; Wang, Youqi; Fu, Wenhui; Yuan, Zhiyou; Yu, Qiang; Peng, Changhui; Koerner, Sally E.; Guo, Liang (Plant and Soil, 2023)

Vulnerability of maize, millet, and rice yields to growing season precipitation and socio-economic proxies in Cameroon - Epule, Terence Epule; Chehbouni, Abdelghani; Dhiba, Driss; Etongo, Daniel; Driouech, Fatima; Brouziyne, Youssef; Peng, Changhui (PLOS ONE, 2021)
In sub-Saharan Africa growing season precipitation is affected by climate change. Due to this, in Cameroon, it is uncertain how some crops are vulnerable to growing season precipitation. Here, an assessment of the vulnerability of maize, millet, and rice to growing season precipitation is carried out at a national scale and validated at four sub-national scales/sites. The data collected were historical yield, precipitation, and adaptive capacity data for the period 1961–2019 for the national scale analysis and 1991–2016 for the sub-national scale analysis. The crop yield data were collected for maize, millet, and rice from FAOSTAT and the global yield gap atlas to assess the sensitivity both nationally and sub-nationally. Historical data on mean crop growing season and mean annul precipitation were collected from a collaborative database of UNDP/Oxford University and the climate portal of the World Bank to assess the exposure both nationally and sub-nationally. To assess adaptive capacity, literacy, and poverty rate proxies for both the national and regional scales were collected from KNOEMA and the African Development Bank. These data were analyzed using a vulnerability index that is based on sensitivity, exposure, and adaptive capacity. The national scale results show that millet has the lowest vulnerability index while rice has the highest. An inverse relationship between vulnerability and adaptive capacity is observed. Rice has the lowest adaptive capacity and the highest vulnerability index. Sub-nationally, this work has shown that northern maize is the most vulnerable crop followed by western highland rice. This work underscores the fact that at different scales, crops are differentially vulnerable due to variations in precipitation, temperature, soils, access to farm inputs, exposure to crop pest and variations in literacy and poverty rates. Therefore, caution should be taken when transitioning from one scale to another to avoid generalization. Despite these differences, in the sub-national scale, western highland rice is observed as the second most vulnerable crop, an observation similar to the national scale observation.

Land-use changes driven by ‘Grain for Green’ program reduced carbon loss induced by soil erosion on the Loess Plateau of China - Deng, Lei; Kim, Dong-Gill; Li, Miaoyu; Huang, Chunbo; Liu, Qiuyu; Cheng, Min; Shangguan, Zhouping; Peng, Changhui (Global and Planetary Change, 2019)

Increasing net primary production in China from 1982 to 1999 - Fang, Jingyun; Piao, Shilong; Field, Christopher B.; Pan, Yude; Guo, Qinghua; Zhou, Liming; Peng, Changhui; Tao, Shu (Frontiers in Ecology and the Environment, 2003)

Central Role of Nitrogen Fertilizer Relative to Water Management in Determining Direct Nitrous Oxide Emissions From Global Rice‐Based Ecosystems - Song, Hanxiong; Zhu, Qiuan; Blanchet, Jean‐Pierre; Chen, Zhi; Zhang, Kerou; Li, Tong; Zhou, Feng; Peng, Changhui (Global Biogeochemical Cycles, 2023)
Abstract The increasing atmospheric nitrous oxide (N 2 O) concentration stems from the development of agriculture. However, N 2 O emissions from global rice‐based ecosystems have not been explicitly and systematically quantified. Therefore, this study aims to estimate the spatiotemporal magnitudes of the N 2 O emissions from global rice‐based ecosystems and determine different contribution factors by improving a process‐based biogeochemical model, TRIPLEX‐GHG v2.0. Model validation suggested that the modeled N 2 O agreed well with field observations under varying management practices at daily, seasonal, and annual steps. Simulated N 2 O emissions from global rice‐based ecosystems exhibited significant increasing trends from 0.026 ± 0.0013 to 0.18 ± 0.003 TgN yr −1 from 1910 to 2020, with ∼69.5% emissions attributed to the rice‐growing seasons. Irrigated rice ecosystems accounted for a majority of global rice N 2 O emissions (∼76.9%) because of their higher N 2 O emission rates than rainfed systems. Regarding spatial analysis, Southern China, Northeast India, and Southeast Asia are hotspots for rice‐based N 2 O emissions. Experimental scenarios revealed that N fertilizer is the largest global rice‐N 2 O source, especially since the 1960s (0.047 ± 0.010 TgN yr −1 , 35.24%), while the impact of expanded irrigation plays a minor role. Overall, this study provides a better understanding of the rice‐based ecosystem in the global agricultural N 2 O budget; further, it quantitively demonstrated the central role of N fertilizer in rice‐based N 2 O emissions by including rice crop calendars, covering non‐rice growing seasons, and differentiating the effects of various water regimes and input N forms. Our findings emphasize the significance of co‐management of N fertilizer and water regimes in reducing the net climate impact of global rice cultivation. , Plain Language Summary Nitrous oxide (N 2 O) is a greenhouse gas with ∼300 times greater effect on climate warming than carbon dioxide. Global croplands represent the largest source of anthropogenic N 2 O emissions. However, the contribution of global rice‐based cropping ecosystems to the N 2 O budget remains largely uncertain because of inconsistent observed results. Inspired by the increasing availability of reliable global data sets, we improved and applied a process‐based biogeochemical model by describing the dynamics of various microbial activities to simulate N 2 O emissions from rice‐based ecosystems on a global scale. Model simulations showed that 0.18 million tons of N 2 O‐N were emitted from global rice‐based N 2 O emissions in the 2010s, which was five times larger than that in the 1910s. In the context of regional contribution, southern China, northern India, and Southeast Asia are responsible for more than 80% of the total emissions during 1910–2020. Results suggest that N fertilizer is the most important rice‐N 2 O source quantitively and that increasing irrigation exerts a buffering effect. This study confirmed the potential mitigating effect of co‐managing N fertilizer and irrigation on mitigating rice‐based N 2 O emissions globally. , Key Points N 2 O emissions from global rice‐based ecosystem increased from 0.026 to 0.18 TgN yr −1 between 1910 and 2020 Irrigated rice‐based ecosystems showed larger N 2 O fluxes than rainfed rice globally due to higher N fertilizer use and frequent aerations N fertilizer represents the largest N 2 O source, and co‐management of N fertilizer and flooding regimes is important for mitigation

Eradicating invasive Spartina alterniflora with alien Sonneratia apetala and its implications for invasion controls - Chen, Huai; Liao, Baowen; Liu, Bin’er; Peng, Changhui; Zhang, Yao; Guan, Wei; Zhu, Qiu’an; Yang, Gang (Ecological Engineering, 2014)

Regional drought-induced reduction in the biomass carbon sink of Canada's boreal forests - Ma, Zhihai; Peng, Changhui; Zhu, Qiuan; Chen, Huai; Yu, Guirui; Li, Weizhong; Zhou, Xiaolu; Wang, Weifeng; Zhang, Wenhua (Proceedings of the National Academy of Sciences, 2012)
The boreal forests, identified as a critical “tipping element” of the Earth's climate system, play a critical role in the global carbon budget. Recent findings have suggested that terrestrial carbon sinks in northern high-latitude regions are weakening, but there has been little observational evidence to support the idea of a reduction of carbon sinks in northern terrestrial ecosystems. Here, we estimated changes in the biomass carbon sink of natural stands throughout Canada's boreal forests using data from long-term forest permanent sampling plots. We found that in recent decades, the rate of biomass change decreased significantly in western Canada (Alberta, Saskatchewan, and Manitoba), but there was no significant trend for eastern Canada (Ontario and Quebec). Our results revealed that recent climate change, and especially drought-induced water stress, is the dominant cause of the observed reduction in the biomass carbon sink, suggesting that western Canada's boreal forests may become net carbon sources if the climate change–induced droughts continue to intensify.

Carbon sequestration by Chinese bamboo forests and their ecological benefits: assessment of potential, problems, and future challenges - Song, Xinzhang; Zhou, Guomo; Jiang, Hong; Yu, Shuquan; Fu, Jinhe; Li, Weizhong; Wang, Weifeng; Ma, Zhihai; Peng, Changhui (Environmental Reviews, 2011)

Quantifying carbon storage for tea plantations in China - Li, Shiyu; Wu, Xu; Xue, Hui; Gu, Baojng; Cheng, Hao; Zeng, Jianming; Peng, Changhui; Ge, Ying; Chang, Jie (Agriculture, Ecosystems & Environment, 2011)

Evaluating the effects of future climate change and elevated CO2 on the water use efficiency in terrestrial ecosystems of China - Zhu, Qiuan; Jiang, Hong; Peng, Changhui; Liu, Jinxun; Wei, Xiaohua; Fang, Xiuqin; Liu, Shirong; Zhou, Guomo; Yu, Shuquan (Ecological Modelling, 2011)

Leaf δ13 C reflects ecosystem patterns and responses of alpine plants to the environments on the Tibetan Plateau - Song, Minghua; Duan, Deyu; Chen, Hui; Hu, Qiwu; Zhang, Feng; Xu, Xingliang; Tian, Yuqiang; Ouyang, Hua; Peng, Changhui (Ecography, 2008)
Leaf δ 13 C is an indicator of water‐use efficiency and provides useful information on the carbon and water balance of plants over longer periods. Variation in leaf δ 13 C between or within species is determined by plant physiological characteristics and environmental factors. We hypothesized that variation in leaf δ 13 C values among dominant species reflected ecosystem patterns controlled by large‐scale environmental gradients, and that within‐species variation indicates plant adaptability to environmental conditions. To test these hypotheses, we collected leaves of dominant species from six ecosystems across a horizontal vegetation transect on the Tibetan Plateau, as well as leaves of Kobresia pygmaea (herbaceous) throughout its distribution and leaves of two coniferous tree species ( Picea crassifolia, Abies fabri ) along an elevation gradient throughout their distribution in the Qilian Mountains and Gongga Mountains, respectively. Leaf δ 13 C of dominant species in the six ecosystems differed significantly, with values for evergreen coniferous<evergreen broadleaved tree<alpine shrub<sedges∼graminoid<xeromorphs. Leaf δ 13 C values of the dominant species and of K. pygmaea were negatively correlated with annual precipitation along a water gradient, but leaf δ 13 C of A. fabri was not significantly correlated with precipitation in habitats without water‐stress. This confirms that variation of δ 13 C between or within species reflects plant responses to environmental conditions. Leaf δ 13 C of the dominant species also reflected water patterns on the Tibetan Plateau, providing evidence that precipitation plays a primary role in controlling ecosystem changes from southeast to northwest on the Tibetan Plateau.

Effect of Drought on Agronomic Traits of Rice and Wheat: A Meta-Analysis - Zhang, Jinmeng; Zhang, Shiqiao; Cheng, Min; Jiang, Hong; Zhang, Xiuying; Peng, Changhui; Lu, Xuehe; Zhang, Minxia; Jin, Jiaxin (International Journal of Environmental Research and Public Health, 2018)
Drought has been one of the most important limiting factors for crop production, which deleteriously affects food security worldwide. The main objective of the present study was to quantitatively assess the effect of drought on the agronomic traits (e.g., plant height, biomass, yield, and yield components) of rice and wheat in combination with several moderators (e.g., drought stress intensity, rooting environment, and growth stage) using a meta-analysis study. The database was created from 55 published studies on rice and 60 published studies on wheat. The results demonstrated that drought decreased the agronomic traits differently between rice and wheat among varying growth stages. Wheat and rice yields decreased by 27.5% and 25.4%, respectively. Wheat grown in pots showed greater decreases in agronomic traits than those grown in the field. Rice showed opposite growing patterns when compared to wheat in rooting environments. The effect of drought on rice increased with plant growth and drought had larger detrimental influences during the reproductive phase (e.g., blooming stage, filling stage, and maturity). However, an exception was found in wheat, which had similar decreased performance during the complete growth cycle. Based on these results, future droughts could produce lower yields of rice and wheat when compared to the current drought.

Data supporting assessment for nitrous oxide emissions from soils under traditional cropland and apple orchard in the Loess Plateau of China - Pang, Junzhu; Wang, Xiaoke; Peng, Changhui; Mu, Yujing; Ouyang, Zhiyun; Lu, Fei; Zhang, Hongxing; Zhang, Shuoxin; Liu, Wenzhao (Data in Brief, 2018)

Hydrologic and Edaphic Controls on Soil Carbon Emission in Dongting Lake Floodplain, China - Deng, Zhengmiao; Li, Youzhi; Xie, Yonghong; Peng, Changhui; Chen, Xinsheng; Li, Feng; Ren, Yijie; Pan, Baihan; Zhang, Chengyi (Journal of Geophysical Research: Biogeosciences, 2018)
Abstract Wetlands play a critical role in mitigating carbon emission. However, little is known about soil carbon emission and their environmental controls from inland floodplain wetlands. This study aimed to determine the effects of hydrologic and edaphic controllers (water table depth [ WTD ], soil temperature [ Ts ], and soil water content [ SWC ]) on soil C emission in Dongting Lake wetland, China. One‐year emissions were measured in Carex meadow and mudflat using static chambers during 2013 to 2014, including nonflooded season ( NFs ) and flooded season ( Fs ). The results showed that soil C emission in the Carex meadow and mudflat was 307.8 and 264.3 g C·m −2 ·year −1 , respectively, and 50–66% of soil C were emitted during NFs. Compared with NFs, CO 2 emission was significantly decreased by 57% but CH 4 emission was significantly increased by 38 times during Fs in the Carex meadow. Stepwise regression combined with structural equation model analysis showed that CO 2 and CH 4 flux were mainly influenced by Ts during NFs, and they were controlled by water temperature ( Tw ) during Fs. During NFs, CO 2 flux increased with increasing Ts and SWC but decreased significantly when SWC was over 66% and 52% in the Carex meadow and mudflat, respectively. CH 4 flux showed an emission pulse at SWC and Ts of 65% and 17.2 °C, respectively. These results indicate that flooding significantly inhibited soil CO 2 emission but stimulated CH 4 emission. The continuous decrease of flooding days caused by anthropogenic disturbances may induce soil C loss in Dongting Lake wetlands. , Key Points Soil C emission in Dongting Lake floodplain was 264.3–307.8 g C.m ‐2 .year ‐1 Flooding significantly inhibited soil CO 2 emission but stimulated CH 4 emission The decline of flooding days in Dongting Lake wetlands can potentially increase soil C loss

Modeling Gross Primary Production of a Typical Coastal Wetland in China Using MODIS Time Series and CO2 Eddy Flux Tower Data - Kang, Xiaoming; Yan, Liang; Zhang, Xiaodong; Li, Yong; Tian, Dashuan; Peng, Changhui; Wu, Haidong; Wang, Jinzhi; Zhong, Lei (Remote Sensing, 2018)
How to effectively combine remote sensing data with the eddy covariance (EC) technique to accurately quantify gross primary production (GPP) in coastal wetlands has been a challenge and is also important and necessary for carbon (C) budgets assessment and climate change studies at larger scales. In this study, a satellite-based Vegetation Photosynthesis Model (VPM) combined with EC measurement and Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to evaluate the phenological characteristics and the biophysical performance of MODIS-based vegetation indices (VIs) and the feasibility of the model for simulating GPP of coastal wetland ecosystems. The results showed that greenness-related and water-related VIs can better identify the green-up and the senescence phases of coastal wetland vegetation, corresponds well with the C uptake period and the phenological patterns that were delineated by GPP from EC tower (GPPEC). Temperature can explain most of the seasonal variation in VIs and GPPEC fluxes. Both enhanced vegetation index (EVI) and water-sensitive land surface water index (LSWI) have a higher predictive power for simulating GPP in this coastal wetland. The comparisons between modeled GPP (GPPVPM) and GPPEC indicated that VPM model can commendably simulate the trajectories of the seasonal dynamics of GPPEC fluxes in terms of patterns and magnitudes, explaining about 85% of GPPEC changes over the study years (p < 0.0001). The results also demonstrate the potential of satellite-driven VPM model for modeling C uptake at large spatial and temporal scales in coastal wetlands, which can provide valuable production data for the assessment of global wetland C sink/source.

Improving a Process-Based Model to Simulate Forest Carbon Allocation under Varied Stand Density - Jiao, Wenxing; Wang, Weifeng; Peng, Changhui; Lei, Xiangdong; Ruan, Honghua; Li, Haikui; Yang, Yanrong; Grabarnik, Pavel; Shanin, Vladimir (Forests, 2022)
Carbon allocation is an important mechanism through which plants respond to environmental changes. To enhance our understanding of maximizing carbon uptake by controlling planting densities, the carbon allocation module of a process-based model, TRIPLEX-Management, was modified and improved by introducing light, soil water, and soil nitrogen availability factors to quantify the allocation coefficients for different plant organs. The modified TRIPLEX-Management model simulation results were verified against observations from northern Jiangsu Province, China, and then the model was used to simulate dynamic changes in forest carbon under six density scenarios (200, 400, 600, 800, 1000, and 1200 stems ha−1). The mean absolute errors between the predicted and observed variables of the mean diameter at breast height, mean height, and estimated aboveground biomass ranged from 15.0% to 26.6%, and were lower compared with the original model simulated results, which ranged from 24.4% to 60.5%. The normalized root mean square errors ranged from 0.2 to 0.3, and were lower compared with the original model simulated results, which ranged from 0.3 to 0.6. The Willmott index between the predicted and observed variables also varied from 0.5 to 0.8, indicating that the modified TRIPLEX-Management model could accurately simulate the dynamic changes in poplar (Populus spp.) plantations with different densities in northern Jiangsu Province. The density scenario results showed that the leaf and fine root allocation coefficients decreased with the increase in stand density, while the stem allocation increased. Overall, our study showed that the optimum stand density (approximately 400 stems ha−1) could reach the highest aboveground biomass for poplar stands and soil organic carbon storage, leading to higher ecological functions related to carbon sequestration without sacrificing wood production in an economical way in northern Jiangsu Province. Therefore, reasonable density control with different soil and climate conditions should be recommended to maximize carbon sequestration.

Nitrogen addition promotes terrestrial plants to allocate more biomass to aboveground organs: A global meta‐analysis - Feng, Huili; Guo, Jiahuan; Peng, Changhui; Kneeshaw, Daniel; Roberge, Gabrielle; Pan, Chang; Ma, Xuehong; Zhou, Dan; Wang, Weifeng (Global Change Biology, 2023)
Abstract A significant increase in reactive nitrogen (N) added to terrestrial ecosystems through agricultural fertilization or atmospheric deposition is considered to be one of the most widespread drivers of global change. Modifying biomass allocation is one primary strategy for maximizing plant growth rate, survival, and adaptability to various biotic and abiotic stresses. However, there is much uncertainty as to whether and how plant biomass allocation strategies change in response to increased N inputs in terrestrial ecosystems. Here, we synthesized 3516 paired observations of plant biomass and their components related to N additions across terrestrial ecosystems worldwide. Our meta‐analysis reveals that N addition (ranging from 1.08 to 113.81 g m −2 year −1 ) increased terrestrial plant biomass by 55.6% on average. N addition has increased plant stem mass fraction, shoot mass fraction, and leaf mass fraction by 13.8%, 12.9%, and 13.4%, respectively, but with an associated decrease in plant reproductive mass (including flower and fruit biomass) fraction by 3.4%. We further documented a reduction in plant root‐shoot ratio and root mass fraction by 27% (21.8%–32.1%) and 14.7% (11.6%–17.8%), respectively, in response to N addition. Meta‐regression results showed that N addition effects on plant biomass were positively correlated with mean annual temperature, soil available phosphorus, soil total potassium, specific leaf area, and leaf area per plant. Nevertheless, they were negatively correlated with soil total N, leaf carbon/N ratio, leaf carbon and N content per leaf area, as well as the amount and duration of N addition. In summary, our meta‐analysis suggests that N addition may alter terrestrial plant biomass allocation strategies, leading to more biomass being allocated to aboveground organs than belowground organs and growth versus reproductive trade‐offs. At the global scale, leaf functional traits may dictate how plant species change their biomass allocation pattern in response to N addition.

Spatial variations in soil organic carbon, nitrogen and phosphorus concentrations related to stand characteristics in subtropical areas - Jiang, Fang; Wu, Xiaohong; Xiang, Wenhua; Fang, Xi; Zeng, Yeling; Ouyang, Shuai; Lei, Pifeng; Deng, Xiangwen; Peng, Changhui (Plant and Soil, 2017)

Spatial and seasonal variations of leaf area index (LAI) in subtropicalsecondary forests related to floristic composition and stand characters - Zhu, Wenjuan; Xiang, Wenhua; Pan, Qiong; Zeng, Yelin; Ouyang, Shuai; Lei, Pifeng; Deng, Xiangwen; Fang, Xi; Peng, Changhui (Biogeosciences, 2016)
Abstract. Leaf area index (LAI) is an important parameter related to carbon, water, and energy exchange between canopy and atmosphere and is widely applied in process models that simulate production and hydrological cycles in forest ecosystems. However, fine-scale spatial heterogeneity of LAI and its controlling factors have yet to be fully understood in Chinese subtropical forests. We used hemispherical photography to measure LAI values in three subtropical forests (Pinus massoniana–Lithocarpus glaber coniferous and evergreen broadleaved mixed forests, Choerospondias axillaris deciduous broadleaved forests, and L. glaber–Cyclobalanopsis glauca evergreen broadleaved forests) from April 2014 to January 2015. Spatial heterogeneity of LAI and its controlling factors were analysed using geostatistical methods and the generalised additive models (GAMs) respectively. Our results showed that LAI values differed greatly in the three forests and their seasonal variations were consistent with plant phenology. LAI values exhibited strong spatial autocorrelation for the three forests measured in January and for the L. glaber–C. glauca forest in April, July, and October. Obvious patch distribution pattern of LAI values occurred in three forests during the non-growing period and this pattern gradually dwindled in the growing season. Stem number, crown coverage, proportion of evergreen conifer species on basal area basis, proportion of deciduous species on basal area basis, and forest types affected the spatial variations in LAI values in January, while stem number and proportion of deciduous species on basal area basis affected the spatial variations in LAI values in July. Floristic composition, spatial heterogeneity, and seasonal variations should be considered for sampling strategy in indirect LAI measurement and application of LAI to simulate functional processes in subtropical forests.

Temperature sensitivity of soil carbon dioxide and nitrous oxide emissions in mountain forest and meadow ecosystems in China - Zhang, Junjun; Peng, Changhui; Zhu, Qiuan; Xue, Wei; Shen, Yan; Yang, Yanzheng; Shi, Guohua; Shi, Shengwei; Wang, Meng (Atmospheric Environment, 2016)

Plant phenological modeling and its application in global climate change research: overview and future challenges - Zhao, Meifang; Peng, Changhui; Xiang, Wenhua; Deng, Xiangwen; Tian, Dalun; Zhou, Xiaolu; Yu, Guirui; He, Honglin; Zhao, Zhonghui (Environmental Reviews, 2013)
Plants interact to the seasonality of their environments, and changes in plant phenology have long been regarded as sensitive indicators of climatic change. Plant phenology modeling has been shown to be the simplest and most useful tool to assess phenol–climate shifts. Temperature, solar radiation, and water availability are assumed to be the key factors that control plant phenology. Statistical, mechanistic, and theoretical approaches have often been used for the parameterization of plant phenology models. The statistical approaches correlate the timing of phenological events to environmental factors or heat unit accumulations. The approaches have the simplified calculation procedures, correct phenological mechanism assumptions, but limited applications and predictive abilities. The mechanistic approaches describe plant phenology with the known or assumed “cause–effect relationships” between biological processes and key driving variables. The mechanistic approaches have the improved parameter processes, realistic assumptions, broad applications, and effective predictions. The theoretical approaches assume cost–benefit tradeoff strategies in trees. These methods are capable of capturing and quantifying the potential impacts and consequences of global climate change and human activity. However, certain limitations still exist related to our understanding of phenological mechanisms in relation to (1) interactions between plants and their specific climates, (2) the integration of both field observational and remote sensing data with plant phenology models across taxa and ecosystem type, (3) amplitude clarification of scale-related sensitivity to global climate change, and (4) improvements in parameterization processes and the overall reduction of modeling uncertainties to forecast impacts of future climate change on plant phenological dynamics. To improve our capacity in the prediction of the amplitude of plant phenological responses with regard to both structural and functional sensitivity to future global climate change, it is important to refine modeling methodologies by applying long-term and large-scale observational data. It is equally important to consider other less used but critical factors (such as heredity, pests, and anthropogenic drivers), apply advanced model parameterization and data assimilation techniques, incorporate process-based plant phenology models as a dynamic component into global vegetation dynamic models, and test plant phenology models against long-term ground observations and high-resolution satellite data across different spatial and temporal scales.

Application of TRIPLEX model for predicting Cunninghamia lanceolata and Pinus massoniana forest stand production in Hunan Province, southern China - Zhao, Meifang; Xiang, Wenhua; Deng, Xiangwen; Tian, Dalun; Huang, Zhihong; Zhou, Xiaolu; Yu, Guirui; He, Honglin; Peng, Changhui (Ecological Modelling, 2013)

Ecosystem service multifunctionality of Chinese fir plantations differing in stand age and implications for sustainable management - Zeng, Yelin; Wu, Huili; Ouyang, Shuai; Chen, Liang; Fang, Xi; Peng, Changhui; Liu, Shirong; Xiao, Wenfa; Xiang, Wenhua (Science of The Total Environment, 2021)

Using machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests - Chen, Jiaxin; Yang, Hongqiang; Man, Rongzhou; Wang, Weifeng; Sharma, Mahadev; Peng, Changhui; Parton, John; Zhu, Huaiping; Deng, Ziwang (Forest Ecology and Management, 2020)

The impact of secondary forest restoration on multiple ecosystem services and their trade-offs - Zeng, Yelin; Gou, Mengmeng; Ouyang, Shuai; Chen, Liang; Fang, Xi; Zhao, Lijuan; Li, Jiaxiang; Peng, Changhui; Xiang, Wenhua (Ecological Indicators, 2019)

Nitrous oxide emissions from soils under traditional cropland and apple orchard in the semi-arid Loess Plateau of China - Pang, Junzhu; Wang, Xiaoke; Peng, Changhui; Mu, Yujing; Ouyang, Zhiyun; Lu, Fei; Zhang, Hongxing; Zhang, Shuoxin; Liu, Wenzhao (Agriculture, Ecosystems & Environment, 2019)

Spatial and temporal variations of N2O emissions from global forest and grassland ecosystems - Zhang, Kerou; Zhu, Qiuan; Liu, Jinxun; Wang, Meng; Zhou, Xiaolu; Li, Mingxu; Wang, Kefeng; Ding, Juhua; Peng, Changhui (Agricultural and Forest Meteorology, 2019)

Changes in soil organic carbon and microbial carbon storage projected during the 21st century using TRIPLEX-MICROBE - Wang, Kefeng; Peng, Changhui; Zhu, Qiuan; Wang, Meng; Wang, Gangsheng; Zhou, Xiaolu; Yang, Yanzheng; Ding, Juhua; Wei, Hua (Ecological Indicators, 2019)

Simulation of dissolved organic carbon concentrations and fluxes in Chinese monsoon forest ecosystems using a modified TRIPLEX-DOC model - Shi, Shengwei; Yang, Mingxia; Hou, Yue; Peng, Changhui; Wu, Haibin; Zhu, Qiuan; Liang, Qiong; Xie, Junfei; Wang, Meng (Science of The Total Environment, 2019)

Global responses of wetland methane emissions to extreme temperature and precipitation - Xu, Min; Zhang, Jiang; Zhang, Zhen; Wang, Meng; Chen, Huai; Peng, Changhui; Yu, Dongxue; Zhan, Hao; Zhu, Qiuan (Environmental Research, 2024)

Phenolic compounds weaken the impact of drought on soil enzyme activity in global wetlands - Li, Tong; Ge, Leming; Zhao, Ruotong; Peng, Changhui; Zhou, Xiaolu; Li, Peng; Liu, Zelin; Song, Hanxiong; Tang, Jiayi; Zhang, Cicheng; Li, Quan; Wang, Meng; et al. (Frontiers in Microbiology, 2024)
Soil enzymes play a central role in carbon and nutrient cycling, and their activities can be affected by drought-induced oxygen exposure. However, a systematic global estimate of enzyme sensitivity to drought in wetlands is still lacking. Through a meta-analysis of 55 studies comprising 761 paired observations, this study found that phosphorus-related enzyme activity increased by 38% as result of drought in wetlands, while the majority of other soil enzyme activities remained stable. The expansion of vascular plants under long-term drought significantly promoted the accumulation of phenolic compounds. Using a 2-week incubation experiment with phenol supplementation, we found that phosphorus-related enzyme could tolerate higher biotoxicity of phenolic compounds than other enzymes. Moreover, a long-term (35 years) drainage experiment in a northern peatland in China confirmed that the increased phenolic concentration in surface layer resulting from a shift in vegetation composition inhibited the increase in enzyme activities caused by rising oxygen availability, except for phosphorus-related enzyme. Overall, these results demonstrate the complex and resilient nature of wetland ecosystems, with soil enzymes showing a high degree of adaptation to drought conditions. These new insights could help evaluate the impact of drought on future wetland ecosystem services and provide a theoretical foundation for the remediation of degraded wetlands.

Does growing vegetables in plastic greenhouses enhance regional ecosystem services beyond the food supply? - Chang, Jie; Wu, Xu; Wang, Yan; Meyerson, Laura A; Gu, Baojing; Min, Yong; Xue, Hui; Peng, Changhui; Ge, Ying (Frontiers in Ecology and the Environment, 2013)
In recent years, plastic greenhouse vegetable cultivation (PGVC) has expanded worldwide, particularly in China, where it accounts for more than 90% of all global PGVC operations. As compared with conventional agricultural methods, PGVC has doubled crop yields by extending growing seasons and intensifying agriculture. PGVC also offers more ecosystem services relative to conventional approaches, including greater soil carbon sequestration, lower water consumption, and improved soil protection at regional scales. The economic benefits of this easily implemented agricultural method are attractive to small‐holder farmers. However, greater environmental impacts (eg greenhouse‐gas emissions, generation of large amounts of plastic waste) are associated with PGVC than with conventional approaches. Here, we review what is currently known about PGVC and identify future research priorities that will comprehensively assess the ecosystem services offered by this method of cultivation, as well as its environmental impacts and socioeconomic benefits.

The effects of plant diversity on nitrous oxide emissions in hydroponic microcosms - Sun, Hongying; Zhang, Chongbang; Song, Changchun; Chang, Scott X.; Gu, Baojing; Chen, Zhengxin; Peng, Changhui; Chang, Jie; Ge, Ying (Atmospheric Environment, 2013)

Cadmium tolerance in six poplar species - He, Jiali; Ma, Chaofeng; Ma, Yonglu; Li, Hong; Kang, Jingquan; Liu, Tongxian; Polle, Andrea; Peng, Changhui; Luo, Zhi-Bin (Environmental Science and Pollution Research, 2013)

Spatiotemporal Variations in Nitrous Oxide Emissions from an Open Fen on the Qinghai–Tibetan Plateau: a 3-Year Study - Chen, Huai; Wang, Yanfen; Wu, Ning; Zhu, Dan; Li, Wei; Gao, Yongheng; Zhu, Qiu’an; Yang, Gang; Peng, Changhui (Water, Air, & Soil Pollution, 2012)

The role of technology and policy in mitigating regional nitrogen pollution - Gu, Baojing; Zhu, Yimei; Chang, Jie; Peng, Changhui; Liu, Dong; Min, Yong; Luo, Weidong; Howarth, Robert W; Ge, Ying (Environmental Research Letters, 2011)

Anatomical, physiological and transcriptional responses of two contrasting poplar genotypes to drought and re‐watering - Cao, Xu; Jia, Jingbo; Zhang, Chao; Li, Hong; Liu, Tongxian; Jiang, Xiangning; Polle, Andrea; Peng, Changhui; Luo, Zhi‐Bin (Physiologia Plantarum, 2014)
Populus × euramericana (Pe) displays higher stable carbon isotope composition ( δ 13 C ) and intrinsic water use efficiency ( WUE i ) than Populus cathayana (Pc) under unlimited water conditions, rendering us to hypothesize that Pe is better acclimated to water deficiency than Pc. To examine this hypothesis, saplings of Pc and Pe were exposed to drought and subsequently re‐watered. Pc and Pe exhibited distinct anatomical, physiological and transcriptional responses in acclimation to drought and re‐watering, mainly due to stronger responsiveness of transcriptional regulation of genes encoding plasma membrane intrinsic proteins ( PIPs ), higher starch accumulation, δ 13 C , stable nitrogen isotope composition ( δ 15 N ) and WUE i , and lower reactive oxygen species ( ROS ) accumulation and scavenging in Pe. In acclimation to drought, both poplar genotypes demonstrated altered anatomical properties, declined height growth, differential expression of PIP s, activation of ABA signaling pathway, decreased total soluble sugars and starch, increased δ 13 C, δ 15 N and WUE i , and shifted homeostasis of ROS production and scavenging, and these changes can be recovered upon re‐watering. These data indicate that Pe is more tolerant to drought than Pc, and that anatomical, physiological and transcriptional acclimation to drought and re‐watering is essential for poplars to survive and grow under projected dry climate scenarios in the future.

Ectomycorrhizas with P axillus involutus enhance cadmium uptake and tolerance in P opulus × canescens - Ma, Yonglu; He, Jiali; Ma, Chaofeng; Luo, Jie; Li, Hong; Liu, Tongxian; Polle, Andrea; Peng, Changhui; Luo, Zhi‐Bin (Plant, Cell & Environment, 2014)
Ectomycorrhizas ( EMs ), which are symbiotic organs formed between tree roots and certain fungi, can mediate cadmium ( Cd ) tolerance of host plants, but the underlying physiological and molecular mechanisms are not fully understood. P opulus × canescens was inoculated with or without P axillus involutus (strain MAJ ) and subsequently exposed to 0 or 50 μM CdSO 4 . Higher net Cd 2+ influx in EMs well corresponded to higher transcript levels of genes involved in Cd 2+ uptake, transport and detoxification processes than those in nonmycorrhizal roots. Higher CO 2 assimilation, improved nutrient and carbohydrate status, and alleviated oxidative stress were found in mycorrhizal compared to nonmycorrhizal poplars despite higher Cd 2+ accumulation. , Abstract Ectomycorrhizas ( EMs ), which are symbiotic organs formed between tree roots and certain fungi, can mediate cadmium ( Cd ) tolerance of host plants, but the underlying physiological and molecular mechanisms are not fully understood. To investigate EMs mediated Cd tolerance in woody plants, P opulus × canescens was inoculated with P axillus involutus (strain MAJ ) to establish mycorrhizal roots. Mycorrhizal poplars and non‐mycorrhizal controls were exposed to 0 or 50 μ M CdSO 4 . EMs displayed higher net Cd 2+ influx than non‐mycorrhizal roots. Net Cd 2+ influx was coupled with net H + efflux and inactivation of plasma membrane ( PM ) H + ‐ ATPases reduced Cd 2+ uptake of EMs less than of non‐mycorrhizal roots. Consistent with higher Cd 2+ uptake in EMs , in most cases, transcript levels of genes involved in Cd 2+ uptake, transport and detoxification processes were increased in EMs compared to non‐mycorrhizal roots. Higher CO 2 assimilation, improved nutrient and carbohydrate status, and alleviated oxidative stress were found in mycorrhizal compared to non‐mycorrhizal poplars despite higher Cd 2+ accumulation. These results indicate that mycorrhizas increase Cd 2+ uptake, probably by an enlarged root volume and overexpression of genes involved in Cd 2+ uptake and transport, and concurrently enhance P o. × canescens Cd tolerance by increased detoxification, improved nutrient and carbohydrate status and defence preparedness.

Nitrogen depositions increase soil respiration and decrease temperature sensitivity in a Moso bamboo forest - Li, Quan; Song, Xinzhang; Chang, Scott X.; Peng, Changhui; Xiao, Wenfa; Zhang, Junbo; Xiang, Wenhua; Li, Yan; Wang, Weifeng (Agricultural and Forest Meteorology, 2019)

Dynamics of SARS-CoV-2 spreading under the influence of environmental factors and strategies to tackle the pandemic: A systematic review - Asif, Zunaira; Chen, Zhi; Stranges, Saverio; Zhao, Xin; Sadiq, Rehan; Olea-Popelka, Francisco; Peng, Changhui; Haghighat, Fariborz; Yu, Tong (Sustainable Cities and Society, 2022)

A climate change‐induced threat to the ecological resilience of a subtropical monsoon evergreen broad‐leaved forest in Southern China - Zhou, Guoyi; Peng, Changhui; Li, Yuelin; Liu, Shizhong; Zhang, Qianmei; Tang, Xuli; Liu, Juxiu; Yan, Junhua; Zhang, Deqiang; Chu, Guowei (Global Change Biology, 2013)
Abstract Recent studies have suggested that tropical forests may not be resilient against climate change in the long term, primarily owing to predicted reductions in rainfall and forest productivity, increased tree mortality, and declining forest biomass carbon sinks. These changes will be caused by drought‐induced water stress and ecosystem disturbances. Several recent studies have reported that climate change has increased tree mortality in temperate and boreal forests, or both mortality and recruitment rates in tropical forests. However, no study has yet examined these changes in the subtropical forests that account for the majority of China's forested land. In this study, we describe how the monsoon evergreen broad‐leaved forest has responded to global warming and drought stress using 32 years of data from forest observation plots. Due to an imbalance in mortality and recruitment, and changes in diameter growth rates between larger and smaller trees and among different functional groups, the average DBH of trees and forest biomass have decreased. Sap flow measurements also showed that larger trees were more stressed than smaller trees by the warming and drying environment. As a result, the monsoon evergreen broad‐leaved forest community is undergoing a transition from a forest dominated by a cohort of fewer and larger individuals to a forest dominated by a cohort of more and smaller individuals, with a different species composition, suggesting that subtropical forests are threatened by their lack of resilience against long‐term climate change.

Constructed wetlands as biofuel production systems - Liu, Dong; Wu, Xu; Chang, Jie; Gu, Baojing; Min, Yong; Ge, Ying; Shi, Yan; Xue, Hui; Peng, Changhui; Wu, Jianguo (Nature Climate Change, 2012)

A drought-induced pervasive increase in tree mortality across Canada's boreal forests - Peng, Changhui; Ma, Zhihai; Lei, Xiangdong; Zhu, Qiuan; Chen, Huai; Wang, Weifeng; Liu, Shirong; Li, Weizhong; Fang, Xiuqin; Zhou, Xiaolu (Nature Climate Change, 2011)

Quantification of net carbon flux from plastic greenhouse vegetable cultivation: A full carbon cycle analysis - Wang, Yan; Xu, Hao; Wu, Xu; Zhu, Yimei; Gu, Baojing; Niu, Xiaoyin; Liu, Anqin; Peng, Changhui; Ge, Ying; Chang, Jie (Environmental Pollution, 2011)

Evaluating the spatiotemporal variations of water budget across China over 1951–2006 using IBIS model - Zhu, Qiuan; Jiang, Hong; Liu, Jinxun; Wei, Xiaohua; Peng, Changhui; Fang, Xiuqing; Liu, Shirong; Zhou, Guomo; Yu, Shuquan; Ju, Weiming (Hydrological Processes, 2010)
Abstract The Integrated Biosphere Simulator is used to evaluate the spatial and temporal patterns of the crucial hydrological variables [run‐off and actual evapotranspiration (AET)] of the water balance across China for the period 1951–2006 including a precipitation analysis. Results suggest three major findings. First, simulated run‐off captured 85% of the spatial variability and 80% of the temporal variability for 85 hydrological gauges across China. The mean relative errors were within 20% for 66% of the studied stations and within 30% for 86% of the stations. The Nash–Sutcliffe coefficients indicated that the quantity pattern of run‐off was also captured acceptably except for some watersheds in southwestern and northwestern China. The possible reasons for underestimation of run‐off in the Tibetan plateau include underestimation of precipitation and uncertainties in other meteorological data due to complex topography, and simplified representations of the soil depth attribute and snow processes in the model. Second, simulated AET matched reasonably with estimated values calculated as the residual of precipitation and run‐off for watersheds controlled by the hydrological gauges. Finally, trend analysis based on the Mann–Kendall method indicated that significant increasing and decreasing patterns in precipitation appeared in the northwest part of China and the Yellow River region, respectively. Significant increasing and decreasing trends in AET were detected in the Southwest region and the Yangtze River region, respectively. In addition, the Southwest region, northern China (including the Heilongjiang, Liaohe, and Haihe Basins), and the Yellow River Basin showed significant decreasing trends in run‐off, and the Zhemin hydrological region showed a significant increasing trend. Copyright © 2009 John Wiley & Sons, Ltd.

Carbon storage by ecological service forests in Zhejiang Province, subtropical China - Zhang, Jun; Ge, Ying; Chang, Jie; Jiang, Bo; Jiang, Hong; Peng, Changhui; Zhu, Jinru; Yuan, Weigao; Qi, Lianzhong; Yu, Shuquan (Forest Ecology and Management, 2007)

Climate change mitigation potential of kitchen waste utilization in China for combined heat and power production - Liu, Weiguo; Zhang, Dan; Tian, Jiajing; Yu, Feiyan; Xie, Yuanming; Cheng, Shengkui; Li, Qiang; Li, Weizhong; Peng, Changhui; Yan, Yan (Science of The Total Environment, 2023)

Global estimates of forest soil methane flux identify a temperate and tropical forest methane sink - Feng, Huili; Guo, Jiahuan; Peng, Changhui; Ma, Xuehong; Kneeshaw, Daniel; Chen, Huai; Liu, Qiuyu; Liu, Mengyao; Hu, Cheng; Wang, Weifeng (Geoderma, 2023)

rTRIPLEXCWFlux: An R package for carbon–water coupling model to simulate net ecosystem productivity and evapotranspiration in forests - Sun, Shulan; Ouyang, Shuai; Hu, Yanting; Zhao, Zhonghui; Liu, Meixian; Chen, Liang; Zeng, Yelin; Peng, Changhui; Zhou, Xiaolu; Xiang, Wenhua (Environmental Modelling & Software, 2023)

Towards a universal model for carbon dioxide uptake by plants - Wang, Han; Prentice, I. Colin; Keenan, Trevor F.; Davis, Tyler W.; Wright, Ian J.; Cornwell, William K.; Evans, Bradley J.; Peng, Changhui (Nature Plants, 2017)

Archaeal communities in the sediments of different mangrove stands at Dongzhaigang, China - Li, Wei; Guan, Wei; Chen, Huai; Liao, Baowen; Hu, Ji; Peng, Changhui; Rui, Junpeng; Tian, Jianqing; Zhu, Dan; He, Yixin (Journal of Soils and Sediments, 2016)

Using ecosystem service bundles to detect trade-offs and synergies across urban–rural complexes - Yang, Guofu; Ge, Ying; Xue, Hui; Yang, Wu; Shi, Yan; Peng, Changhui; Du, Yuanyuan; Fan, Xing; Ren, Yuan; Chang, Jie (Landscape and Urban Planning, 2015)

Agricultural carbon flux changes driven by intensive plastic greenhouse cultivation in five climatic regions of China - Wu, Xu; Ge, Ying; Wang, Yan; Liu, Dong; Gu, Baojing; Ren, Yuan; Yang, Guofu; Peng, Changhui; Cheng, Jihua; Chang, Jie (Journal of Cleaner Production, 2015)

Elevation‐induced climate change as a dominant factor causing the late Miocene C4 plant expansion in the Himalayan foreland - Wu, Haibin; Guo, Zhengtang; Guiot, Joël; Hatté, Christine; Peng, Changhui; Yu, Yanyan; Ge, Junyi; Li, Qin; Sun, Aizhi; Zhao, Deai (Global Change Biology, 2014)
Abstract During the late Miocene, a dramatic global expansion of C 4 plant distribution occurred with broad spatial and temporal variations. Although the event is well documented, whether subsequent expansions were caused by a decreased atmospheric CO 2 concentration or climate change is a contentious issue. In this study, we used an improved inverse vegetation modeling approach that accounts for the physiological responses of C 3 and C 4 plants to quantitatively reconstruct the paleoclimate in the Siwalik of Nepal based on pollen and carbon isotope data. We also studied the sensitivity of the C 3 and C 4 plants to changes in the climate and the atmospheric CO 2 concentration. We suggest that the expansion of the C 4 plant distribution during the late Miocene may have been primarily triggered by regional aridification and temperature increases. The expansion was unlikely caused by reduced CO 2 levels alone. Our findings suggest that this abrupt ecological shift mainly resulted from climate changes related to the decreased elevation of the Himalayan foreland.

Nitrous oxide fluxes from three forest types of the tropical mountain rainforests on Hainan Island, China - Bai, Zhenzhi; Yang, Gang; Chen, Huai; Zhu, Qiuan; Chen, Dexiang; Li, Yide; Wang, Xu; Wu, Zhongmin; Zhou, Guangyi; Peng, Changhui (Atmospheric Environment, 2014)

Effects of soil warming, rainfall reduction and water table level on CH 4 emissions from the Zoige peatland in China - Yang, Gang; Chen, Huai; Wu, Ning; Tian, Jianqing; Peng, Changhui; Zhu, Qiuan; Zhu, Dan; He, Yixin; Zheng, Qunying; Zhang, Changbing (Soil Biology and Biochemistry, 2014)

Spatiotemporal patterns and drivers of stem methane flux from two poplar forests with different soil textures - Han, Menghua; Feng, Huili; Peng, Changhui; Lei, Xiangdong; Xue, Jianhui; Malghani, Saadatullah; Ma, Xuehong; Song, Xinzhang; Wang, Weifeng (Tree Physiology, 2022)
Abstract In forest ecosystems, the majority of methane (CH4) research focuses on soils, whereas tree stem CH4 flux and driving factors remain poorly understood. We measured the in situ stem CH4 flux using the static chamber–gas chromatography method at different heights in two poplar (Populus spp.) forests with separate soil textures. We evaluated the relationship between stem CH4 fluxes and environmental factors with linear mixed models and estimated the tree CH4 emission rate at the stand level. Our results showed that poplar stems were a net source of atmospheric CH4. The mean stem CH4 emission rates were 97.51 ± 6.21 μg·m−2·h−1 in Sihong and 67.04 ± 5.64 μg·m−2·h−1 in Dongtai. The stem CH4 emission rate in Sihong with clay loam soils was significantly higher (P < 0.001) than that in Dongtai with sandy loam soils. The stem CH4 emission rate also showed a seasonal variation, minimum in winter and maximum in summer. The stem CH4 emission rate generally decreased with increasing sampling height. Although the differences in CH4 emission rates between stem heights were significant in the annual averages, these differences were driven by differences observed in the summer. Stem CH4 emission rates were significantly and positively correlated with air temperature (P < 0.001), relative humidity (P < 0.001), soil water content (P < 0.001) and soil CH4 flux (P < 0.001). At these sites, the soil emitted CH4 to the atmosphere in summer (mainly from June to September) but absorbed CH4 from the atmosphere during the other season. At the stand level, tree CH4 emissions accounted for 2–35.4% of soil CH4 uptake. Overall, tree stem CH4 efflux could be an important component of the forest CH4 budget. Therefore, it is necessary to conduct more in situ monitoring of stem CH4 flux to accurately estimate the CH4 budget in the future.

Corrigendum: Extrapolation and Uncertainty Evaluation of Carbon Dioxide and Methane Emissions in the Qinghai-Tibetan Plateau Wetlands Since the 1960s - Zhang, Jiang; Zhu, Qiuan; Yuan, Minshu; Liu, Xinwei; Chen, Huai; Peng, Changhui; Wang, Meng; Yang, Zhenan; Jiang, Lin; Zhao, Pengxiang (Frontiers in Earth Science, 2021)

Water table drawdown increases plant biodiversity and soil polyphenol in the Zoige Plateau - Zeng, Jia; Chen, Huai; Bai, Yinping; Dong, Faqin; Peng, Changhui; Yan, Fei; Cao, Qin; Yang, Zhenan; Yang, Suizhuang; Yang, Gang (Ecological Indicators, 2021)

Quantifying Leaf Trait Covariations and Their Relationships with Plant Adaptation Strategies along an Aridity Gradient - Yang, Yanzheng; Kang, Le; Zhao, Jun; Qi, Ning; Li, Ruonan; Wen, Zhongming; Kassout, Jalal; Peng, Changhui; Lin, Guanghui; Zheng, Hua (Biology, 2021)
A trait-based approach is an effective way to quantify plant adaptation strategies in response to changing environments. Single trait variations have been well depicted before; however, multi-trait covariations and their roles in shaping plant adaptation strategies along aridity gradients remain unclear. The purpose of this study was to reveal multi-trait covariation characteristics, their controls and their relevance to plant adaptation strategies. Using eight relevant plant functional traits and multivariate statistical approaches, we found the following: (1) the eight studied traits show evident covariation characteristics and could be grouped into four functional dimensions linked to plant strategies, namely energy balance, resource acquisition, resource investment and water use efficiency; (2) leaf area (LA) together with traits related to the leaf economic spectrum, including leaf nitrogen content per area (Narea), leaf nitrogen per mass (Nmass) and leaf dry mass per area (LMA), covaried along the aridity gradient (represented by the moisture index, MI) and dominated the trait–environmental change axis; (3) together, climate, soil and family can explain 50.4% of trait covariations; thus, vegetation succession along the aridity gradient cannot be neglected in trait covariations. Our findings provide novel perspectives toward a better understanding of plant adaptations to arid conditions and serve as a reference for vegetation restoration and management programs in arid regions.

Extrapolation and Uncertainty Evaluation of Carbon Dioxide and Methane Emissions in the Qinghai-Tibetan Plateau Wetlands Since the 1960s - Zhang, Jiang; Zhu, Qiuan; Yuan, Minshu; Liu, Xinwei; Chen, Huai; Peng, Changhui; Wang, Meng; Yang, Zhenan; Jiang, Lin; Zhao, Pengxiang (Frontiers in Earth Science, 2020)
Wetlands are important modulators of atmospheric greenhouse gas (GHGs) concentrations. However, little is known about the magnitudes and spatiotemporal patterns of GHGs fluxes in wetlands on the Qinghai-Tibetan Plateau (QTP), the world’s largest and highest plateau. In this study, we measured soil temperature and the fluxes of carbon dioxide (CO 2 ) and methane (CH 4 ) in an alpine wetland on the QTP from April 2017 to April 2019 by the static chamber method, and from January 2017 to December 2017 by the eddy covariance (EC) method. The CO 2 and CH 4 emission measurements from both methods showed different relationships to soil temperature at different timescales (annual and seasonal). Based on such relationship patterns and soil temperature data (1960–2017), we extrapolated the CO 2 and CH 4 emissions of study site for the past 57 years: the mean CO 2 emission rate was 91.38 mg C m –2 h –1 on different measurement methods and timescales, with the range of the mean emission rate from 35.10 to 146.25 mg C m –2 h –1 , while the mean CH 4 emission rate was 2.75 mg C m –2 h –1 , with the ranges of the mean emission rate from 1.41 to 3.85 mg C m –2 h –1 . The estimated regional CO 2 and CH 4 emissions from permanent wetlands on the QTP were 94.29 and 2.37 Tg C year –1 , respectively. These results indicate that uncertainties caused by measuring method and timescale should be fully considered when extrapolating wetland GHGs fluxes from local sites to the regional level. Moreover, the results of global warming potential showed that CO 2 dominates the GHG balance of wetlands on the QTP.

The effects of persistent drought and waterlogging on the dynamics of nonstructural carbohydrates of Robinia pseudoacacia L. seedlings in Northwest China - Yang, Bin; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Liu, Weiguo; Duan, Min; Wang, Hui; Liu, Zhihao; Guo, Xinyi; Wang, Meng (Forest Ecosystems, 2019)

Variations of Sediment Archaea Communitiesin Different Distribution Areasof Bruguiera gymnoihiza Mangrovein Dongzhaigang, China - Li, Wei; Guan, Wei; Chen, Huai; Liao, Baowen; Hu, Ji; Rui, Junpeng; Peng, Changhui; Zhu, Dan; He, Yixin; Tian, Jianqing (Polish Journal of Environmental Studies, 2019)

Variation in the functional traits of fine roots is linked to phylogenetics in the common tree species of Chinese subtropical forests - Liu, Cong; Xiang, Wenhua; Zou, Limei; Lei, Pifeng; Zeng, Yelin; Ouyang, Shuai; Deng, Xiangwen; Fang, Xi; Liu, Zelin; Peng, Changhui (Plant and Soil, 2019)

Interactive Effect of Radioactive and Heavy-MetalContamination on Soil Enzyme Activityin a Former Uranium Mine - Yang, Gang; Dong, Faqin; Liu, Mingxue; Nie, Xiaoqin; Zong, Meirong; Peng, Changhui; Chen, Huai; Wei, Hongfu; Wang, Pingping; Zhang, Wei (Polish Journal of Environmental Studies, 2018)

Multi-scale temporal variation of methane flux and its controls in a subtropical tidal salt marsh in eastern China - Li, Hong; Dai, Shengqi; Ouyang, Zutao; Xie, Xiao; Guo, Haiqiang; Gu, Caihong; Xiao, Xiangming; Ge, Zhenming; Peng, Changhui; Zhao, Bin (Biogeochemistry, 2018)

Fire effects on soil CH4 and N2O fluxes across terrestrial ecosystems - Guo, Jiahuan; Feng, Huili; Peng, Changhui; Du, Juan; Wang, Weifeng; Kneeshaw, Daniel; Pan, Chang; Roberge, Gabrielle; Feng, Lei; Chen, Anping (Science of The Total Environment, 2024)

Global spectra of plant litter carbon, nitrogen and phosphorus concentrations and returning amounts - Yuan, Ji; Wu, Fuzhong; Peng, Changhui; Peñuelas, Josep; Vallicrosa, Helena; Sardans, Jordi; Peng, Yan; Wu, Qiqian; Li, Zimin; Heděnec, Petr; Li, Zhijie; Tan, Siyi; et al. (Journal of Ecology, 2024)
Abstract Litter decomposition is a key ecological process that determines carbon (C) and nutrient cycling in terrestrial ecosystems. The initial concentrations of C and nutrients in litter play a critical role in this process, yet the global patterns of litter initial concentrations of C, nitrogen (N) and phosphorus (P) are poorly understood. We employed machine learning with a global database to quantitatively assess the global patterns and drivers of leaf litter initial C, N and P concentrations, as well as their returning amounts (i.e. amounts returned to soils). The medians of litter C, N and P concentrations were 46.7, 1.1, and 0.1%, respectively, and the medians of litter C, N and P returning amounts were 1.436, 0.038 and 0.004 Mg ha −1 year −1 , respectively. Soil and climate emerged as the key predictors of leaf litter C, N and P concentrations. Predicted global maps showed that leaf litter N and P concentrations decreased with latitude, while C concentration exhibited an opposite pattern. Additionally, the returning amounts of leaf litter C, N and P all declined from the equator to the poles in both hemispheres. Synthesis : Our results provide a quantitative assessment of the global concentrations and returning amounts of leaf litter C, N and P, which showed new light on the role of leaf litter in global C and nutrients cycling.

Methane emissions from the surface of the Three Gorges Reservoir: CH4 EMISSIONS FROM TGR - Chen, Huai; Yuan, Xingzhong; Chen, Zhongli; Wu, Yuyuan; Liu, Xianshu; Zhu, Dan; Wu, Ning; Zhu, Qiu'an; Peng, Changhui; Li, Weizhong (Journal of Geophysical Research: Atmospheres, 2011)

Assessment of net ecosystem services of plastic greenhouse vegetable cultivation in China - Chang, Jie; Wu, Xu; Liu, Anqin; Wang, Yan; Xu, Bin; Yang, Wu; Meyerson, Laura A.; Gu, Baojing; Peng, Changhui; Ge, Ying (Ecological Economics, 2011)

Simulating carbon dioxide exchange in boreal ecosystems flooded by reservoirs - Kim, Youngil; Roulet, Nigel T.; Li, Changsheng; Frolking, Steve; Strachan, Ian B.; Peng, Changhui; Teodoru, Cristian R.; Prairie, Yves T.; Tremblay, Alain (Ecological Modelling, 2016)

Phosphorus and nitrogen physiology of two contrasting poplar genotypes when exposed to phosphorus and/or nitrogen starvation - Gan, Honghao; Jiao, Yu; Jia, Jingbo; Wang, Xinli; Li, Hong; Shi, Wenguang; Peng, Changhui; Polle, Andrea; Luo, Zhi-Bin (Tree Physiology, 2016)

Drought effects on soil carbon and nitrogen dynamics in global natural ecosystems - Deng, Lei; Peng, Changhui; Kim, Dong-Gill; Li, Jiwei; Liu, Yulin; Hai, Xuying; Liu, Qiuyu; Huang, Chunbo; Shangguan, Zhouping; Kuzyakov, Yakov (Earth-Science Reviews, 2021)

Responses of C:N:P stoichiometric correlations among plants, soils and microorganisms to warming: A meta-analysis - Yu, Zongkai; Zhang, Chao; Liu, Xiaowei; Lei, Jichu; Zhang, Qiang; Yuan, Zhiyou; Peng, Changhui; Koerner, Sally E.; Xu, Jianchu; Guo, Liang (Science of The Total Environment, 2024)

Global Priority Conservation Areas in the Face of 21st Century Climate Change - Li, Junsheng; Lin, Xin; Chen, Anping; Peterson, Townsend; Ma, Keping; Bertzky, Monika; Ciais, Philippe; Kapos, Valerie; Peng, Changhui; Poulter, Benjamin (PLoS ONE, 2013)

Assessment of private economic benefits and positive environmental externalities of tea plantation in China - Xue, Hui; Ren, Xiaoyi; Li, Shiyu; Wu, Xu; Cheng, Hao; Xu, Bin; Gu, Baojing; Yang, Guofu; Peng, Changhui; Ge, Ying; Chang, Jie (Environmental Monitoring and Assessment, 2013)

TRIPLEX model testing and application for predicting forest growth and biomass production in the subtropical forest zone of China's Zhejiang Province - Zhang, Jun; Chu, Ziyan; Ge, Ying; Zhou, Xiaolu; Jiang, Hong; Chang, Jie; Peng, Changhui; Zheng, Jiawen; Jiang, Bo; Zhu, Jinru; Yu, Shuquan (Ecological Modelling, 2008)

Stable oxic-anoxic transitional interface is beneficial to retard soil carbon loss in drained peatland - Liu, Liangfeng; Tian, Jianqing; Wang, Hongjun; Xue, Dan; Huang, Xinya; Wu, Ning; Wang, Meng; Xu, Xingliang; Peng, Changhui; Wang, Yanfen; Chen, Huai (Soil Biology and Biochemistry, 2023)

Global Climate Change Increases Terrestrial Soil CH4 Emissions - Guo, Jiahuan; Feng, Huili; Peng, Changhui; Chen, Huai; Xu, Xuan; Ma, Xuehong; Li, Li; Kneeshaw, Daniel; Ruan, Honghua; Yang, Hongqiang; Wang, Weifeng (Global Biogeochemical Cycles, 2023)
Abstract Increased greenhouse gas emissions are causing unprecedented climate change, which is, in turn, altering emissions and removals (referring to the oxidation of atmospheric CH 4 by methanotrophs within the soil) of the atmospheric CH 4 in terrestrial ecosystems. In the global CH 4 budget, wetlands are the dominant natural source and upland soils are the primary biological sink. However, it is unclear whether and how the soil CH 4 exchanges across terrestrial ecosystems and the atmosphere will be affected by warming and changes in precipitation patterns. Here, we synthesize 762 observations of in situ soil CH 4 flux data based on the chamber method from the past three decades related to temperature and precipitation changes across major terrestrial ecosystems worldwide. Our meta‐analysis reveals that warming (average warming of +2°C) promotes upland soil CH 4 uptake and wetland soil CH 4 emission. Decreased precipitation (ranging from −100% to −7% of local mean annual precipitation) stimulates upland soil CH 4 uptake. Increased precipitation (ranging from +4% to +94% of local mean annual precipitation) accelerates the upland soil CH 4 emission. By 2100, under the shared socioeconomic pathway with a high radiative forcing level (SSP585), CH 4 emissions from global terrestrial ecosystems will increase by 22.8 ± 3.6 Tg CH 4 yr −1 as an additional CH 4 source, which may be mainly attributed to the increase in precipitation over 30°N latitudes. Our meta‐analysis strongly suggests that future climate change would weaken the natural buffering ability of terrestrial ecosystems on CH 4 fluxes and thus contributes to a positive feedback spiral. , Plain Language Summary This study is the first investigation to include scenarios of CH 4 sink–source transition due to climate change and provides the global estimate of soil CH 4 budgets in natural terrestrial ecosystems in the context of climate change. The enhanced effect of climate change on CH 4 emissions was mainly attributed to increased CH 4 emissions from natural upland ecosystems. Although an increased CH 4 uptake by forest and grassland soils caused by increased temperature and decreased precipitation can offset some part of additional CH 4 sources, the substantial increase of increased precipitation on CH 4 emissions makes these sinks insignificant. These findings highlight that future climate change would weaken the natural buffering ability of terrestrial ecosystems on CH 4 emissions and thus form a positive feedback spiral between methane emissions and climate change. , Key Points This study is the first CH 4 budget investigation to include CH 4 sink‐source transition due to climate change Climate change is estimated to add 22.8 ± 3.6 Tg CH 4 yr −1 emission by 2100 under the high socioeconomic pathway Climate change weakens the buffering capacity of upland soils to CH 4 emissions

A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China - Yang, Yanzheng; Zhu, Qiuan; Peng, Changhui; Wang, Han; Xue, Wei; Lin, Guanghui; Wen, Zhongming; Chang, Jie; Wang, Meng; Liu, Guobin; Li, Shiqing (Scientific Reports, 2016)
Abstract Increasing evidence indicates that current dynamic global vegetation models (DGVMs) have suffered from insufficient realism and are difficult to improve, particularly because they are built on plant functional type (PFT) schemes. Therefore, new approaches, such as plant trait-based methods, are urgently needed to replace PFT schemes when predicting the distribution of vegetation and investigating vegetation sensitivity. As an important direction towards constructing next-generation DGVMs based on plant functional traits, we propose a novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China. The results demonstrated that a Gaussian mixture model (GMM) trained with a LMA-N mass -LAI data combination yielded an accuracy of 72.82% in simulating vegetation distribution, providing more detailed parameter information regarding community structures and ecosystem functions. The new approach also performed well in analyses of vegetation sensitivity to different climatic scenarios. Although the trait-climate relationship is not the only candidate useful for predicting vegetation distributions and analysing climatic sensitivity, it sheds new light on the development of next-generation trait-based DGVMs.

The Spatial and Temporal Distribution of Dissolved Organic Carbon Exported from Three Chinese Rivers to the China Sea - Shi, Guohua; Peng, Changhui; Wang, Meng; Shi, Shengwei; Yang, Yanzheng; Chu, Junyao; Zhang, Junjun; Lin, Guanghui; Shen, Yan; Zhu, Qiuan (PLOS ONE, 2016)

Plant functional trait diversity and structural diversity co-underpin ecosystem multifunctionality in subtropical forests - Ouyang, Shuai; Gou, Mengmeng; Lei, Pifeng; Liu, Yue; Chen, Liang; Deng, Xiangwen; Zhao, Zhonghui; Zeng, Yelin; Hu, Yanting; Peng, Changhui; Xiang, Wenhua (Forest Ecosystems, 2023)

Responses of soil CH4 fluxes to nitrogen addition in two tropical montane rainforests in southern China - Wu, Fangtao; Peng, Changhui; Wang, Chuanyao; Chen, Huai; Liu, Weiguo; Liu, Zhihao; Wang, Hui; Li, Hong; Chen, Dexiang; Li, Yide; Liu, Shirong (Forest Ecosystems, 2022)

Quantification of Ecosystem-Scale Methane Sinks Observed in a Tropical Rainforest in Hainan, China - Liu, Zhihao; Li, Hong; Wu, Fangtao; Wang, Hui; Chen, Huai; Zhu, Qiuan; Yang, Gang; Liu, Weiguo; Chen, Dexiang; Li, Yide; Peng, Changhui (Land, 2022)
Tropical rainforest ecosystems are important when considering the global methane (CH4) budget and in climate change mitigation. However, there is a lack of direct and year-round observations of ecosystem-scale CH4 fluxes from tropical rainforest ecosystems. In this study, we examined the temporal variations in CH4 flux at the ecosystem scale and its annual budget and environmental controlling factors in a tropical rainforest of Hainan Island, China, using 3 years of continuous eddy covariance measurements from 2016 to 2018. Our results show that CH4 uptake generally occurred in this tropical rainforest, where strong CH4 uptake occurred in the daytime, and a weak CH4 uptake occurred at night with a mean daily CH4 flux of −4.5 nmol m−2 s−1. In this rainforest, the mean annual budget of CH4 for the 3 years was −1260 mg CH4 m−2 year−1. Furthermore, the daily averaged CH4 flux was not distinctly different between the dry season and wet season. Sixty-nine percent of the total variance in the daily CH4 flux could be explained by the artificial neural network (ANN) model, with a combination of air temperature (Tair), latent heat flux (LE), soil volumetric water content (VWC), atmospheric pressure (Pa), and soil temperature at −10 cm (Tsoil), although the linear correlation between the daily CH4 flux and any of these individual variables was relatively low. This indicates that CH4 uptake in tropical rainforests is controlled by multiple environmental factors and that their relationships are nonlinear. Our findings also suggest that tropical rainforests in China acted as a CH4 sink during 2016–2018, helping to counteract global warming.

Identifying the greenhouses by Google Earth Engine to promote the reuse of fragmented land in urban fringe - Yang, Guofu; Xu, Ronghua; Chen, Yi; Wu, Zhaoping; Du, Yuanyuan; Liu, Shun; Qu, Zelong; Guo, Kejian; Peng, Changhui; Chang, Jie; Ge, Ying (Sustainable Cities and Society, 2021)

Contrasting responses of soil exoenzymatic interactions and the dissociated carbon transformation to short- and long-term drainage in a minerotrophic peatland - Li, Tong; Ge, Leming; Huang, Jingjing; Yuan, Xin; Peng, Changhui; Wang, Shengzhong; Bu, Zhaojun; Zhu, Qiuan; Wang, Zucheng; Liu, Weiguo; Wang, Meng (Geoderma, 2020)

Tree growth rate and soil nutrient status determine the shift in nutrient-use strategy of Chinese fir plantations along a chronosequence - Wu, Huili; Xiang, Wenhua; Ouyang, Shuai; Xiao, Wenfa; Li, Shenggong; Chen, Liang; Lei, Pifeng; Deng, Xiangwen; Zeng, Yelin; Zeng, Lixiong; Peng, Changhui (Forest Ecology and Management, 2020)

Distribution margins as natural laboratories to infer species’ flowering responses to climate warming and implications for frost risk - Guo, Liang; Wang, Jinghong; Li, Mingjun; Liu, Lu; Xu, Jianchu; Cheng, Jimin; Gang, Chengcheng; Yu, Qiang; Chen, Ji; Peng, Changhui; Luedeling, Eike (Agricultural and Forest Meteorology, 2019)

Immediate and carry-over effects of increased soil frost on soil respiration and microbial activity in a spruce forest - Yang, Kaijun; Peng, Changhui; Peñuelas, Josep; Kardol, Paul; Li, Zhijie; Zhang, Li; Ni, Xiangyin; Yue, Kai; Tan, Bo; Yin, Rui; Xu, Zhenfeng (Soil Biology and Biochemistry, 2019)

Trait-Based Climate Change Predictions of Vegetation Sensitivity and Distribution in China - Yang, Yanzheng; Zhao, Jun; Zhao, Pengxiang; Wang, Hui; Wang, Boheng; Su, Shaofeng; Li, Mingxu; Wang, Liming; Zhu, Qiuan; Pang, Zhiyong; Peng, Changhui (Frontiers in Plant Science, 2019)

Responses of nitrogen concentrations and pools to multiple environmental change drivers: A meta‐analysis across terrestrial ecosystems - Yue, Kai; Peng, Yan; Fornara, Dario A.; Van Meerbeek, Koenraad; Vesterdal, Lars; Yang, Wanqin; Peng, Changhui; Tan, Bo; Zhou, Wei; Xu, Zhenfeng; Ni, Xiangyin; Zhang, Li; et al. (Global Ecology and Biogeography, 2019)
Abstract Aim We sought to understand how the individual and combined effects of multiple environmental change drivers differentially influence terrestrial nitrogen (N) concentrations and N pools and whether the interactive effects of these drivers are mainly antagonistic, synergistic or additive. Location Worldwide. Time period Contemporary. Major taxa studied Plants, soil, and soil microbes in terrestrial ecosystems. Methods We synthesized data from manipulative field studies from 758 published articles to estimate the individual, combined and interactive effects of key environmental change drivers (elevated CO 2 , warming, N addition, phosphorus addition, increased rainfall and drought) on plant, soil, and soil microbe N concentrations and pools using meta‐analyses. We assessed the influences of moderator variables on these effects through structural equation modelling. Results We found that (a) N concentrations and N pools were significantly affected by the individual and combined effects of multiple drivers, with N addition (either alone or in combination with another driver) showing the strongest positive effects; (b) the individual and combined effects of these drivers differed significantly between N concentrations and N pools in plants, but seldom in soils and microbes; (c) additive effects of driver pairs on N concentrations and pools were much more common than synergistic or antagonistic effects across plants, soils and microbes; and (d) environmental and experimental factors were important moderators of the individual, combined and interactive effects of these drivers on terrestrial N. Main conclusions Our results indicate that terrestrial N concentrations and N pools, especially those of plants, can be significantly affected by the individual and combined effects of environmental change drivers, with the interactive effects of these drivers being mostly additive. Our findings are important because they contribute to the development of models to better predict how altered N availability affects ecosystem carbon cycling under future environmental changes.

Methane emissions from rice paddies natural wetlands, lakes in China: synthesis new estimate - Chen, Huai; Zhu, Qiu'an; Peng, Changhui; Wu, Ning; Wang, Yanfen; Fang, Xiuqin; Jiang, Hong; Xiang, Wenhua; Chang, Jie; Deng, Xiangwen; Yu, Guirui (Global Change Biology, 2013)
Abstract Sources of methane ( CH 4 ) become highly variable for countries undergoing a heightened period of development due to both human activity and climate change. An urgent need therefore exists to budget key sources of CH 4 , such as wetlands (rice paddies and natural wetlands) and lakes (including reservoirs and ponds), which are sensitive to these changes. For this study, references in relation to CH 4 emissions from rice paddies, natural wetlands, and lakes in C hina were first reviewed and then reestimated based on the review itself. Total emissions from the three CH 4 sources were 11.25 Tg CH 4 yr −1 (ranging from 7.98 to 15.16 Tg CH 4 yr −1 ). Among the emissions, 8.11 Tg CH 4 yr −1 (ranging from 5.20 to 11.36 Tg CH 4 yr −1 ) derived from rice paddies, 2.69 Tg CH 4 yr −1 (ranging from 2.46 to 3.20 Tg CH 4 yr −1 ) from natural wetlands, and 0.46 Tg CH 4 yr −1 (ranging from 0.33 to 0.59 Tg CH 4 yr −1 ) from lakes (including reservoirs and ponds). Plentiful water and warm conditions, as well as its large rice paddy area make rice paddies in southeastern C hina the greatest overall source of CH 4 , accounting for approximately 55% of total paddy emissions. Natural wetland estimates were slightly higher than the other estimates owing to the higher CH 4 emissions recorded within Q inghai‐ T ibetan P lateau peatlands. Total CH 4 emissions from lakes were estimated for the first time by this study, with three quarters from the littoral zone and one quarter from lake surfaces. Rice paddies, natural wetlands, and lakes are not constant sources of CH 4 , but decreasing ones influenced by anthropogenic activity and climate change. A new progress‐based model used in conjunction with more observations through model‐data fusion approach could help obtain better estimates and insights with regard to CH 4 emissions deriving from wetlands and lakes in C hina.

Inter-Annual Variations of Methane Emission from an Open Fen on the Qinghai-Tibetan Plateau: A Three-Year Study - Chen, Huai; Wu, Ning; Wang, Yanfen; Zhu, Dan; Zhu, Qiu’an; Yang, Gang; Gao, Yongheng; Fang, Xiuqin; Wang, Xu; Peng, Changhui (PLoS ONE, 2013)

Nitrous oxide emissions from the surface of the Three Gorges Reservoir - Zhu, Dan; Chen, Huai; Yuan, Xingzhong; Wu, Ning; Gao, Yongheng; Wu, Yan; Zhang, Yongmei; Peng, Changhui; Zhu, Qiu’an; Yang, Gang; Wu, Jianghua (Ecological Engineering, 2013)

Climatic drivers and ecological implications of variation in the time interval between leaf-out and flowering - Guo, Liang; Liu, Xiaowei; Alatalo, Juha M.; Wang, Chuanyao; Xu, Jianchu; Yu, Haiying; Chen, Ji; Yu, Qiang; Peng, Changhui; Dai, Junhu; Luedeling, Eike (Current Biology, 2023)

Soil properties and species composition under different grazing intensity in an alpine meadow on the eastern Tibetan Plateau, China - Yang, Zhen’an; Xiong, Wan; Xu, Yingyi; Jiang, Lin; Zhu, Erxiong; Zhan, Wei; He, Yixin; Zhu, Dan; Zhu, Qiuan; Peng, Changhui; Chen, Huai (Environmental Monitoring and Assessment, 2016)

Photosynthetic and hydraulic traits influence forest resistance and resilience to drought stress across different biomes - Hu, Yanting; Xiang, Wenhua; Schäfer, Karina V.R.; Lei, Pifeng; Deng, Xiangwen; Forrester, David I.; Fang, Xi; Zeng, Yelin; Ouyang, Shuai; Chen, Liang; Peng, Changhui (Science of The Total Environment, 2022)

Recoupling Industrial Dairy Feedlots and Industrial Farmlands Mitigates the Environmental Impacts of Milk Production in China - Fan, Xing; Chang, Jie; Ren, Yuan; Wu, Xu; Du, Yuanyuan; Xu, Ronghua; Liu, Dong; Chang, Scott X.; Meyerson, Laura A.; Peng, Changhui; Ge, Ying (Environmental Science & Technology, 2018)

C-Lock (Patent Pending): A System for Estimating and Certifying Carbon Emission Reduction Credits for the Sequestration of Soil Carbon on Agricultural Land - Zimmerman, Patrick R.; Price, Maribeth; Peng, Changhui; Capehart, William J.; Updegraff, Karen; Kozak, Patrick; Vierling, Lee; Baker, Elaine; Kopp, Fred; Duke, Genet; Das, Chandan (Mitigation and Adaptation Strategies for Global Change, 2005)

Weak impact of nutrient enrichment on peat: Evidence from physicochemical properties - Li, Tong; Yuan, Xin; Ge, Leming; Cao, Chenhao; Suo, Yuchen; Bu, Zhao-Jun; Peng, Changhui; Song, Hanxiong; Liu, Ziping; Liu, Shasha; Wang, Meng (Frontiers in Ecology and Evolution, 2022)
Atmospheric deposition of nitrogen (N) and phosphorus (P) far exceeding the pre-industrial levels have the potential to change carbon (C) dynamics in northern peatlands. However, the responses of soil C concentration and organo-chemical composition to different rates and durations of nutrient enrichment are still unclear. Here, we compared the short- (3 years) and long-term (10 years) effects of N and P fertilizations on the physicochemical properties of peat and porewater in a bog-fen complex in northern China. Our results showed that the short-term fertilization increased Sphagnum moss cover, while the expansion of vascular plants was observed owing to the long-term fertilization. The preserved soil C did not vary considerably after the short- and long-term fertilizations. The harsh soil conditions may impede the decomposition of organic matters by soil microorganisms during the short-term fertilization. For the long-term fertilization, the input of high-phenolic litters owing to vascular plant expansion likely exerted an important control on soil C dynamics. These processes constrained the variation in soil C concentrations when the addition rate and cumulative amount of external N and P increased, which will advance our understanding and prediction of the resilience of soil C storage to imbalanced nutrient enrichment of N and P in northern peatlands.

Carbon dynamics of peatlands in China during the Holocene - Wang, Mei; Chen, Huai; Wu, Ning; Peng, Changhui; Zhu, Qiuan; Zhu, Dan; Yang, Gang; Wu, Jianghua; He, Yixin; Gao, Yongheng; Tian, Jianqing; Zhao, Xinquan (Quaternary Science Reviews, 2014)

Carbon and nitrogen cycling on the Qinghai–Tibetan Plateau - Chen, Huai; Ju, Peijun; Zhu, Qiuan; Xu, Xingliang; Wu, Ning; Gao, Yongheng; Feng, Xiaojuan; Tian, Jianqing; Niu, Shuli; Zhang, Yangjian; Peng, Changhui; Wang, Yanfen (Nature Reviews Earth & Environment, 2022)

Temperature and Moisture Modulate the Contribution of Soil Fauna to Litter Decomposition via Different Pathways - Tan, Bo; Yin, Rui; Zhang, Jian; Xu, Zhenfeng; Liu, Yang; He, Shuqin; Zhang, Li; Li, Han; Wang, Lixia; Liu, Sining; You, Chengming; Peng, Changhui (Ecosystems, 2021)

Nitrogen addition mediates the response of foliar stoichiometry to phosphorus addition: a meta-analysis - You, Chengming; Peng, Changhui; Xu, Zhenfeng; Liu, Yang; Zhang, Li; Yin, Rui; Liu, Lin; Li, Han; Wang, Lixia; Liu, Sining; Tan, Bo; Kardol, Paul (Ecological Processes, 2021)
Abstract Background Changes in foliar nitrogen (N) and phosphorus (P) stoichiometry play important roles in predicting the effects of global change on ecosystem structure and function. However, there is substantial debate on the effects of P addition on foliar N and P stoichiometry, particularly under different levels of N addition. Thus, we conducted a global meta-analysis to investigate how N addition alters the effects of P addition on foliar N and P stoichiometry across different rates and durations of P addition and plant growth types based on more than 1150 observations. Results We found that P addition without N addition increased foliar N concentrations, whereas P addition with N addition had no effect. The positive effects of P addition on foliar P concentrations were greater without N addition than with N addition. Additionally, the effects of P addition on foliar N, P and N:P ratios varied with the rate and duration of P addition. In particular, short-term or low-dose P addition with and without N addition increased foliar N concentration, and the positive effects of short-term or low-dose P addition on foliar P concentrations were greater without N addition than with N addition. The responses of foliar N and P stoichiometry of evergreen plants to P addition were greater without N addition than with N addition. Moreover, regardless of N addition, soil P availability was more effective than P resorption efficiency in predicting the changes in foliar N and P stoichiometry in response to P addition. Conclusions Our results highlight that increasing N deposition might alter the response of foliar N and P stoichiometry to P addition and demonstrate the important effect of the experimental environment on the results. These results advance our understanding of the response of plant nutrient use efficiency to P addition with increasing N deposition.

Interspecific difference in N:P stoichiometric homeostasis drives nutrient release and soil microbial community composition during decomposition - Song, Hanxiong; Huang, Jingjing; Ge, Leming; Peng, Changhui; Zhao, Pengxiang; Guo, Xinyi; Li, Tong; Shen, Xiaojuan; Zhu, Qiuan; Liu, Weiguo; Wei, Hua; Wang, Meng (Plant and Soil, 2020)

The effects of the soil environment on soil organic carbon in tea plantations in Xishuangbanna, southwestern China - Di, Sun; Zong, Mingming; Li, Shiyu; Li, Haixia; Duan, Changqun; Peng, Changhui; Zhao, Yonggui; Bai, Jinyue; Lin, Chen; Feng, Yuan; Huang, Wuping; Wang, Di (Agriculture, Ecosystems & Environment, 2020)

The linkage between vegetation and soil nutrients and their variation under different grazing intensities in an alpine meadow on the eastern Qinghai-Tibetan Plateau - Yang, Zhenan; Zhu, Qiuan; Zhan, Wei; Xu, Yingyi; Zhu, Erxiong; Gao, Yongheng; Li, Shiqing; Zheng, Qunying; Zhu, Dan; He, Yixin; Peng, Changhui; Chen, Huai (Ecological Engineering, 2018)

The microbial mechanisms by which long-term heavy metal contamination affects soil organic carbon levels - Xiao, Zhineng; Duan, Changqun; Li, Shiyu; Chen, Ji; Peng, Changhui; Che, Rongxiao; Liu, Chang'e; Huang, Yin; Mei, Runran; Xu, Liangliang; Luo, Pengfei; Yu, Yadong (Chemosphere, 2023)

The 5000-year climate change of northeastern Qinghai-Tibetan Plateau and historical ecology of Zoige wetlands - He Yixin, 何奕忻; Wu Ning, 吴宁; Zhu Qiu'an, 朱求安; Chen Huai, 陈槐; Zhu Dan, 朱单; Peng Changhui, 彭长辉; Yang Gang, 杨刚; Gao Yongheng, 高永恒; Zhao Chuan, 赵川 (Acta Ecologica Sinica, 2014)

Carbon and Water Use Efficiencies: A Comparative Analysis of Ten Terrestrial Ecosystem Models under Changing Climate - El Masri, Bassil; Schwalm, Christopher; Huntzinger, Deborah N.; Mao, Jiafu; Shi, Xiaoying; Peng, Changhui; Fisher, Joshua B.; Jain, Atul K.; Tian, Hanqin; Poulter, Benjamin; Michalak, Anna M. (Scientific Reports, 2019)
Abstract Terrestrial ecosystems carbon and water cycles are tightly coupled through photosynthesis and evapotranspiration processes. The ratios of carbon stored to carbon uptake and water loss to carbon gain are key ecophysiological indicators essential to assess the magnitude and response of the terrestrial plant to the changing climate. Here, we use estimates from 10 terrestrial ecosystem models to quantify the impacts of climate, atmospheric CO 2 concentration, and nitrogen (N) deposition on water use efficiency (WUE), and carbon use efficiency (CUE). We find that across models, WUE increases over the 20 th Century particularly due to CO 2 fertilization and N deposition and compares favorably to experimental studies. Also, the results show a decrease in WUE with climate for the last 3 decades, in contrasts with up-scaled flux observations that demonstrate a constant WUE. Modeled WUE responds minimally to climate with modeled CUE exhibiting no clear trend across space and time. The divergence between simulated and observationally-constrained WUE and CUE is driven by modeled NPP and autotrophic respiration, nitrogen cycle, carbon allocation, and soil moisture dynamics in current ecosystem models. We suggest that carbon-modeling community needs to reexamine stomatal conductance schemes and the soil-vegetation interactions for more robust modeling of carbon and water cycles.

Climate warming accelerates carbon release from foliar litter—A global synthesis - Chen, Zihao; Ni, Xiangyin; Patoine, Guillaume; Peng, Changhui; Yue, Kai; Yuan, Ji; Wu, Qiuxia; Eisenhauer, Nico; Guerra, Carlos A.; Bol, Roland; Wu, Fuzhong; Wang, G. Geoff (Global Change Biology, 2024)
Abstract With over one‐third of terrestrial net primary productivity transferring to the litter layer annually, the carbon release from litter serves as a crucial valve in atmospheric carbon dioxide concentrations. However, few quantitative global projections of litter carbon release rate in response to climate change exist. Here, we combined a global foliar litter carbon release dataset (8973 samples) to generate spatially explicitly estimates of the response of their residence time ( τ ) to climate change. Results show a global mean litter carbon release rate () of 0.69 year −1 (ranging from 0.09–5.6 year −1 ). Under future climate scenarios, global mean τ is projected to decrease by a mean of 2.7% (SSP 1–2.6) and 5.9% (SSP 5–8.5) during 2071–2100 period. Locally, the alleviation of temperature and moisture restrictions corresponded to obvious decreases in τ in cold and arid regions, respectively. In contract, τ in tropical humid broadleaf forests increased by 4.6% under SSP 5–8.5. Our findings highlight the vegetation type as a powerful proxy for explaining global patterns in foliar litter carbon release rates and the role of climate conditions in predicting responses of carbon release to climate change. Our observation‐based estimates could refine carbon cycle parameterization, improving projections of carbon cycle–climate feedbacks.

Climate-driven increase of natural wetland methane emissions offset by human-induced wetland reduction in China over the past three decades - Zhu, Qiuan; Peng, Changhui; Liu, Jinxun; Jiang, Hong; Fang, Xiuqin; Chen, Huai; Niu, Zhenguo; Gong, Peng; Lin, Guanghui; Wang, Meng; Wang, Han; Yang, Yanzheng; et al. (Scientific Reports, 2016)
Abstract Both anthropogenic activities and climate change can affect the biogeochemical processes of natural wetland methanogenesis. Quantifying possible impacts of changing climate and wetland area on wetland methane (CH 4 ) emissions in China is important for improving our knowledge on CH 4 budgets locally and globally. However, their respective and combined effects are uncertain. We incorporated changes in wetland area derived from remote sensing into a dynamic CH 4 model to quantify the human and climate change induced contributions to natural wetland CH 4 emissions in China over the past three decades. Here we found that human-induced wetland loss contributed 34.3% to the CH 4 emissions reduction (0.92 TgCH 4 ), and climate change contributed 20.4% to the CH 4 emissions increase (0.31 TgCH 4 ), suggesting that decreasing CH 4 emissions due to human-induced wetland reductions has offset the increasing climate-driven CH 4 emissions. With climate change only, temperature was a dominant controlling factor for wetland CH 4 emissions in the northeast (high latitude) and Qinghai-Tibet Plateau (high altitude) regions, whereas precipitation had a considerable influence in relative arid north China. The inevitable uncertainties caused by the asynchronous for different regions or periods due to inter-annual or seasonal variations among remote sensing images should be considered in the wetland CH 4 emissions estimation.

Interannual variation in methane emissions from tropical wetlands triggered by repeated El Niño Southern Oscillation - Zhu, Qiuan; Peng, Changhui; Ciais, Philippe; Jiang, Hong; Liu, Jinxun; Bousquet, Philippe; Li, Shiqin; Chang, Jie; Fang, Xiuqin; Zhou, Xiaolu; Chen, Huai; Liu, Shirong; et al. (Global Change Biology, 2017)
Abstract Methane (CH 4 ) emissions from tropical wetlands contribute 60%–80% of global natural wetland CH 4 emissions. Decreased wetland CH 4 emissions can act as a negative feedback mechanism for future climate warming and vice versa. The impact of the El Niño–Southern Oscillation (ENSO) on CH 4 emissions from wetlands remains poorly quantified at both regional and global scales, and El Niño events are expected to become more severe based on climate models’ projections. We use a process‐based model of global wetland CH 4 emissions to investigate the impacts of the ENSO on CH 4 emissions in tropical wetlands for the period from 1950 to 2012. The results show that CH 4 emissions from tropical wetlands respond strongly to repeated ENSO events, with negative anomalies occurring during El Niño periods and with positive anomalies occurring during La Niña periods. An approximately 8‐month time lag was detected between tropical wetland CH 4 emissions and ENSO events, which was caused by the combined time lag effects of ENSO events on precipitation and temperature over tropical wetlands. The ENSO can explain 49% of interannual variations for tropical wetland CH 4 emissions. Furthermore, relative to neutral years, changes in temperature have much stronger effects on tropical wetland CH 4 emissions than the changes in precipitation during ENSO periods. The occurrence of several El Niño events contributed to a lower decadal mean growth rate in atmospheric CH 4 concentrations throughout the 1980s and 1990s and to stable atmospheric CH 4 concentrations from 1999 to 2006, resulting in negative feedback to global warming.

A Process‐Based Model Integrating Remote Sensing Data for Evaluating Ecosystem Services - Niu, Zhongen; He, Honglin; Peng, Shushi; Ren, Xiaoli; Zhang, Li; Gu, Fengxue; Zhu, Gaofeng; Peng, Changhui; Li, Pan; Wang, Junbang; Ge, Rong; Zeng, Na; et al. (Journal of Advances in Modeling Earth Systems, 2021)
Abstract Terrestrial ecosystems provide multiple services interacting in complex ways. However, most ecosystem services (ESs) models (e.g., InVEST and ARIES) ignored the relationships among ESs. Process‐based models can overcome this limitation, and the integration of ecological models with remote sensing data could greatly facilitate the investigation of the complex ecological processes. Therefore, based on the Carbon and Exchange between Vegetation, Soil, and Atmosphere (CEVSA) models, we developed a process‐based ES model (CEVSA‐ES) integrating remotely sensed leaf area index to evaluate four important ESs (i.e., productivity provision, carbon sequestration, water retention, and soil retention) at annual timescale in China. Compared to the traditional terrestrial biosphere models, the main innovation of CEVSA‐ES model was the consideration of soil erosion processes and its impact on carbon cycling. The new version also improved the carbon‐water cycle algorithms. Then, the Sobol and DEMC methods that integrated the CEVSA‐ES model with nine flux sites comprising 39 site‐years were used to identify and optimize parameters. Finally, the model using the optimized parameters was validated at 26 field sites comprising 135 site‐years. Simulation results showed good fits with ecosystem processes, explaining 95%, 92%, 76%, and 65% interannual variabilities of gross primary productivity, ecosystem respiration, net ecosystem productivity, and evapotranspiration, respectively. The CEVSA‐ES model performed well for productivity provision and carbon sequestration, which explained 96% and 81% of the spatial‐temporal variations of the observed annual productivity provision and carbon sequestration, respectively. The model also captured the interannual trends of water retention and soil erosion for most sites or basins. , Plain Language Summary Terrestrial ecosystems simultaneously provide multiple ecosystem services (ESs). The common environmental drivers and internal mechanisms lead to nonlinear and dynamic relationships among ESs. Assessing the spatiotemporal changes of ESs have recently emerged as an element of ecosystem management and environmental policies. However, appropriate methods linking ESs to biogeochemical and biophysical processes are still lacking. In this study, we developed a process‐based model Carbon and Exchange between Vegetation, Soil, and Atmosphere (CEVSA‐ES) that integrates remote sensing data for evaluating ESs. We first described the model framework and detailed algorithms of the processes related to ESs. Then a model‐fusion method was applied to optimize parameters to which the model was sensitive and to improve model performance based on multi‐source observational data. The calibrated CEVSA‐ES model showed good performance for carbon and water fluxes (i.e., gross primary productivity, ecosystem respiration, net ecosystem productivity, and evapotranspiration). The CEVSA‐ES model performed well for productivity provision, and carbon sequestration. It also captured the interannual trends of water retention and soil erosion for most sites or basins in Chinese terrestrial ecosystems. The CEVSA‐ES model not only has the potential to improve the accuracy of simulated ESs, but also can capture the relationships among ESs, which could support the trade‐offs and synergies among ESs. , Key Points We developed an ecosystem service model Carbon and Exchange between Vegetation, Soil, and Atmosphere‐ecosystem services (CEVSA‐ES) that integrates ecosystem processes with satellite‐based data Accounting for soil retention/erosion and its impact on carbon cycling was the main difference from other process‐based models The CEVSA‐ES model with optimized parameters explained 47%–96% of the spatial and temporal variations of four ecosystem services in China

An inventory of biogenic volatile organic compounds for a subtropical urban–rural complex - Chang, Jie; Ren, Yuan; Shi, Yan; Zhu, Yimei; Ge, Ying; Hong, Shengmao; Jiao, Li; Lin, Fengmei; Peng, Changhui; Mochizuki, Tomoki; Tani, Akira; Mu, Ying; et al. (Atmospheric Environment, 2012)

N-fertilization has different effects on the growth, carbon and nitrogen physiology, and wood properties of slow- and fast-growing Populus species - Li, Hong; Li, Mengchun; Luo, Jie; Cao, Xu; Qu, Long; Gai, Ying; Jiang, Xiangning; Liu, Tongxian; Bai, Hua; Janz, Dennis; Polle, Andrea; Peng, Changhui; et al. (Journal of Experimental Botany, 2012)

Time-lag effects of flood stimulation on methane emissions in the Dongting Lake floodplain, China - Wang, Tao; Deng, Zhengmiao; Xie, Yonghong; Wang, Buqing; Wu, Shaoan; Li, Feng; Wang, Wei; Zou, Yeai; Li, Xu; Hou, Zhiyong; Zeng, Jing; Wang, Mei; et al. (Agricultural and Forest Meteorology, 2023)

Higher temperature variability reduces temperature sensitivity of vegetation growth in Northern Hemisphere - Wu, Xiuchen; Liu, Hongyan; Li, Xiaoyan; Piao, Shilong; Ciais, Philippe; Guo, Weichao; Yin, Yi; Poulter, Ben; Peng, Changhui; Viovy, Nicolas; Vuichard, Nicolas; Wang, Pei; et al. (Geophysical Research Letters, 2017)
Abstract Interannual air temperature variability has changed over some regions in Northern Hemisphere (NH), accompanying with climate warming. However, whether and to what extent it regulates the interannual sensitivity of vegetation growth to temperature variability (i.e., interannual temperature sensitivity)—one central issue in understanding and predicting the responses of vegetation growth to changing climate—still remains poorly quantified and understood. Here we quantify the relationships between the interannual temperature sensitivity of mean growing‐season (April–October) normalized difference vegetation index (NDVI) and ecosystem model simulations of gross primary productivity (GPP), and variability in mean growing‐season temperature for forest, shrub, and grass over NH. We find that higher interannual variability in mean growing‐season temperature leads to consistent decrease in interannual temperature sensitivity of mean growing‐season NDVI among all vegetation types but not in model simulations of GPP. Drier condition associates with ~130 ± 150% further decrease in interannual temperature sensitivity of mean growing‐season NDVI by temperature variability in forest and shrub. These results illustrate that varying temperature variability can significantly regulate the interannual temperature sensitivity of vegetation growth over NH, interacted with drought variability and nonlinear responses of photosynthesis to temperature. Our findings call for an improved characterization of the nonlinear effects of temperature variability on vegetation growth within global ecosystem models. , Key Points It shows consistent decrease in temperature sensitivity of vegetation growth by temperature variability for all vegetation types Larger decrease in temperature sensitivity of vegetation growth by temperature variability is found in forest and shrub in dry regions Drier condition adds further decrease in temperature sensitivity of vegetation growth by temperature variability for forest and shrub in dry regions

Soil Carbon Dioxide Fluxes from Three Forest Types of the Tropical Montane Rainforest on Hainan Island, China - Jiang, Xinhua; Chen, Huai; Peng, Changhui; Li, Yide; He, Yixin; Chen, Dexiang; Lin, Mingxian; Hu, Ji; Ma, Tianli; Liu, Liangfeng; Liu, Xinwei; Xia, Miao; et al. (Water, Air, & Soil Pollution, 2016)

Higher recent peat C accumulation than that during the Holocene on the Zoige Plateau - Wang, Mei; Yang, Gang; Gao, Yongheng; Chen, Huai; Wu, Ning; Peng, Changhui; Zhu, Qiuan; Zhu, Dan; Wu, Jianghua; He, Yixin; Tian, Jianqing; Zhao, Xinquan; et al. (Quaternary Science Reviews, 2015)

Soil methane uptake by grasslands and forests in China - Wang, Yanfen; Chen, Huai; Zhu, Qiuan; Peng, Changhui; Wu, Ning; Yang, Gang; Zhu, Dan; Tian, Jianqing; Tian, Liuxi; Kang, Xiaoming; He, Yixin; Gao, Yongheng; et al. (Soil Biology and Biochemistry, 2014)

Stand carbon storage and net primary production in China’s subtropical secondary forests are predicted to increase by 2060 - Jin, Jia; Xiang, Wenhua; Zeng, Yelin; Ouyang, Shuai; Zhou, Xiaolu; Hu, Yanting; Zhao, Zhonghui; Chen, Liang; Lei, Pifeng; Deng, Xiangwen; Wang, Hui; Liu, Shirong; et al. (Carbon Balance and Management, 2022)
Abstract Background Forest ecosystems play an important role in carbon sequestration, climate change mitigation, and achieving China's target to become carbon (C) neutral by 2060. However, changes in C storage and net primary production (NPP) in natural secondary forests stemming from tree growth and future climate change have not yet been investigated in subtropical areas in China. Here, we used data from 290 inventory plots in four secondary forests [evergreen broad-leaved forest (EBF), deciduous and evergreen broad-leaved mixed forest (DEF), deciduous broad-leaved forest (DBF), and coniferous and broad-leaved mixed forest (CDF)] at different restoration stages and run a hybrid model (TRIPLEX 1.6) to predict changes in stand carbon storage and NPP under two future climate change scenarios (RCP4.5 and RCP8.5). Results The runs of the hybrid model calibrated and validated by using the data from the inventory plots suggest significant increase in the carbon storage by 2060 under the current climate conditions, and even higher increase under the RCP4.5 and RCP8.5 climate change scenarios. In contrast to the carbon storage, the simulated EBF and DEF NPP declines slightly over the period from 2014 to 2060. Conclusions The obtained results lead to conclusion that proper management of China’s subtropical secondary forests could be considered as one of the steps towards achieving China’s target to become carbon neutral by 2060.

Estimating natural nitrous oxide emissions from the Qinghai–Tibetan Plateau using a process-based model: Historical spatiotemporal patterns and future trends - Zhang, Kerou; Peng, Changhui; Zhu, Qiuan; Li, Mingxu; Yan, Zhongqing; Li, Meng; Yan, Liang; Zhang, Xiaodong; Wang, Jinzhi; Li, Yong; Kang, Enze; Song, Hanxiong; et al. (Ecological Modelling, 2022)

Stability in subtropical forests: The role of tree species diversity, stand structure, environmental and socio‐economic conditions - Ouyang, Shuai; Xiang, Wenhua; Gou, Mengmeng; Chen, Liang; Lei, Pifeng; Xiao, Wenfa; Deng, Xiangwen; Zeng, Lixiong; Li, Jiangrong; Zhang, Tao; Peng, Changhui; Forrester, David I. (Global Ecology and Biogeography, 2021)
Abstract Aim Tree species diversity can increase the stability of ecosystem productivity by increasing mean productivity and/or reducing the standard deviation in productivity. However, stand structure, environmental and socio‐economic conditions influence plant diversity and might strongly influence the relationships between diversity and stability in natural forest communities. The relative importance of these factors for community stability remains poorly understood in complex (species‐rich) subtropical forests. Location Subtropical area of southern China. Time period 1999–2014. Major taxa studied Forest trees. Methods We conducted bivariate analyses to examine the mechanisms (overyielding and species asynchrony) underlying the effects of diversity on stability. Multiple regression models were then used to determine the relative importance of tree species diversity, stand structure, socio‐economic factors and environmental conditions on stability. Structural equation modelling was used to disentangle how these variables directly and/or indirectly affect forest stability. Results Tree species richness exerted a positive effect on stability through overyielding and species asynchrony, and this effect was stronger in mountainous forests than in hilly forests. Species richness positively affected the mean productivity, whereas species asynchrony negatively affected the variability in productivity, hence increasing forest stability. Structural diversity also had a positive effect, whereas population density had a negative effect on stability. Precipitation variability and slope mainly had indirect influences on stability through their effects on tree species richness. Main conclusions Overall, tree species diversity governed stability; however, stand structure, socio‐economic conditions and environmental conditions also played an important role in shaping stability in these forests. Our work highlights the importance of regulating stand structure and socio‐economic factors in forest management and biodiversity conservation, to maintain and enhance their stability to provide ecosystem services in the face of unprecedented anthropogenic activities and global climate change.

Peatland degradation reduces methanogens and methane emissions from surface to deep soils - Yang, Gang; Tian, Jianqing; Chen, Huai; Jiang, Lin; Zhan, Wei; Hu, Ji; Zhu, Erxiong; Peng, Changhui; Zhu, Qiuan; Zhu, Dan; He, Yixin; Li, Mingxu; et al. (Ecological Indicators, 2019)

Comparison of methane emissions among invasive and native mangrove species in Dongzhaigang, Hainan Island - He, Yixin; Guan, Wei; Xue, Dan; Liu, Liangfeng; Peng, Changhui; Liao, Baowen; Hu, Ji; Zhu, Qiu'an; Yang, Yanzhen; Wang, Xu; Zhou, Guanyi; Wu, Zhongming; et al. (Science of The Total Environment, 2019)

The NEBIE plot network: Highlights of long-term scientific studies - Bell, F. Wayne; Dacosta, Jennifer; Newmaster, Steven G.; Mallik, Azim; Hunt, Shelley; Anand, Madhur; Maloles, Jose; Peng, Changhui; Parton, John; McLaughlin, John; Winters, John; Wester, Monique; et al. (The Forestry Chronicle, 2017)
The NEBIE plot network is a stand-scale, multi-agency research project designed to compare the ecological effects of a range of silvicultural treatments in northern temperate and boreal forest regions of Ontario, Canada. While research on silviculture intensities has been previously conducted, the NEBIE plot network is at a larger scale, and covers a wider range of intensities in a variety of northern temperate and boreal forest types. Details about experimental design, treatment designs and research sites, are presented in a companion paper which is published in this edition of The Forestry Chronicle. The operational scale of treatment plots allow for assessment of a variety of forest values. We used a criteria and indicator approach to organize long-term research studies on the network sites, with the goal of providing scientific findings that would inform forest policy. Pre-treatment, and 2-, 5-, and 10-year post-harvesting data have been collected. These initial data add to existing information on the effects of intensification of silviculture on biological diversity, forest productivity, ecosystem health and vitality, soil and water resources, contribution of enhanced forest management global carbon cycles, and long-term multiple socio-economic benefits of northern forests.

Contrasting Soil Bacterial Community, Diversity, and Function in Two Forests in China - Wei, Hua; Peng, Changhui; Yang, Bin; Song, Hanxiong; Li, Quan; Jiang, Lin; Wei, Gang; Wang, Kefeng; Wang, Hui; Liu, Shirong; Liu, Xiaojing; Chen, Dexiang; et al. (Frontiers in Microbiology, 2018)

Effects of canopy gaps on N 2 O fluxes in a tropical montane rainforest in Hainan of China - Yang, Huai; Detto, Matteo; Liu, Shirong; Yuan, Wenping; Hsieh, Cheng-I; Wang, Xu; Chen, Renli; Chen, Huai; Peng, Changhui; Jiang, Xinhua; Li, Yide; Xu, Han; et al. (Ecological Engineering, 2017)

Effect of Grazing Intensities on Soil N2O Emissions from an Alpine Meadow of Zoige Plateau in China - Zhan, Wei; Yang, Zhenan; Liu, Jianliang; Chen, Huai; Yang, Gang; Zhu, Erxiong; Hu, Ji; Jiang, Lin; Liu, Liangfeng; Zhu, Dan; He, Yixin; Zhao, Chuan; et al. (Atmosphere, 2021)
The alpine meadow of Zoige Plateau plays a key role in local livestock production of cattle and sheep. However, it remains unclear how animal grazing or its intensity affect nitrous oxide (N2O) emissions, and the main driving factors. A grazing experiment including four grazing intensities (G0, G0.7, G1.2, G1.6 yak ha−1) was conducted between January 2013 and December 2014 to evaluate the soil nitrous oxide (N2O) fluxes under different grazing intensities in an alpine meadow on the eastern Qinghai–Tibet Plateau of China. The N2O fluxes were examined with gas collected by the static chamber method and by chromatographic concentration analysis. N2O emissions in the growing seasons (from May to September) were lower than that in non-growing seasons (from October to April) in 2013, 1.94 ± 0.30 to 3.37 ± 0.56 kg N2O ha−1 yr−1. Annual mean N2O emission rates were calculated as 1.17 ± 0.50 kg N2O ha−1 yr−1 in non-grazing land (G0) and 1.94 ± 0.23 kg N2O ha−1 yr−1 in the grazing land (G0.7, G1.2, and G1.6). The annual mean N2O flux showed no significant differences between grazing treatments in 2013. However, there were significantly greater fluxes from the G0.7 treatment than from the G1.6 treatment in 2014, especially in the growing season. Over the two years, the soil N2O emission rate was significantly negatively correlated with soil water-filled pore space (WFPS) and dissolved organic carbon (DOC) content as well as positively correlated with soil available phosphorus (P). No relationship was observed between soil N2O emission rate and temperature or rainfall. Our results showed that the meadow soils acted as a source of N2O for most periods and turned into a weak sink of N2O later during the sampling period. Our results highlight the importance of proper grazing intensity in reducing N2O emissions from alpine meadow. The interaction between grazing intensity and N2O emissions should be of more concern during future management of pastures in Zoige Plateau.

Linkage between tree species richness and soil microbial diversity improves phosphorus bioavailability - Wu, Huili; Xiang, Wenhua; Ouyang, Shuai; Forrester, David I.; Zhou, Bo; Chen, Lingxiu; Ge, Tida; Lei, Pifeng; Chen, Liang; Zeng, Yelin; Song, Xinzhang; Peñuelas, Josep; et al. (Functional Ecology, 2019)
Abstract Increased availability of soil phosphorus (P) has recently been recognised as an underlying driving factor for the positive relationship between plant diversity and ecosystem function. The effects of plant diversity on the bioavailable forms of P involved in biologically mediated rhizospheric processes and how the link between plant and soil microbial diversity facilitates soil P bioavailability, however, remain poorly understood. This study quantified four forms of bioavailable P (CaCl 2 ‐P, citric‐P, enzyme‐P and HCl‐P) in mature subtropical forests using a novel biologically based approach, which emulates how rhizospheric processes influence the release and supply of available P. Soil microbial diversity was measured by Illumina high‐throughput sequencing. Our results suggest that tree species richness significantly affects soil microbial diversity ( p < 0.05), increases litter decomposition, fine‐root biomass and length and soil organic carbon and thus increases the four forms of bioavailable P. A structural equation model that links plants, soil microbes and P forms indicated that soil bacterial and fungal diversity play dominant roles in mediating the effects of tree species richness on soil P bioavailability. An increase in the biodiversity of plants, soil bacteria and fungi could maintain soil P bioavailability and alleviate soil P limitations. Our results imply that biodiversity strengthens plant and soil feedback and increases P recycling. A plain language summary is available for this article.

An early warning signal for grassland degradation on the Qinghai-Tibetan Plateau - Zhu, Qiuan; Chen, Huai; Peng, Changhui; Liu, Jinxun; Piao, Shilong; He, Jin-Sheng; Wang, Shiping; Zhao, Xinquan; Zhang, Jiang; Fang, Xiuqin; Jin, Jiaxin; Yang, Qi-En; et al. (Nature Communications, 2023)
Abstract Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO 2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.

Detecting One-Hundred-Year Environmental Changes in Western China Using Seven-Year Repeat Photography - Chen, Huai; Yin, Kaipu; Wang, Haiyan; Zhong, Shenxian; Wu, Ning; Shi, Fusun; Zhu, Dan; Zhu, Qiuan; Wang, Weifeng; Ma, Zhihai; Fang, Xiuqin; Li, Weizhong; et al. (PLoS ONE, 2011)

Effects of stand age, richness and density on productivity in subtropical forests in China - Ouyang, Shuai; Xiang, Wenhua; Wang, Xiangping; Xiao, Wenfa; Chen, Liang; Li, Shenggong; Sun, Han; Deng, Xiangwen; Forrester, David I.; Zeng, Lixiong; Lei, Pifeng; Lei, Xiangdong; et al. (Journal of Ecology, 2019)
Abstract Forest productivity may be determined not only by biodiversity but also by environmental factors and stand structure attributes. However, the relative importance of these factors in determining productivity is still controversial for subtropical forests. Based on a large dataset from 600 permanent forest inventory plots across subtropical China, we examined the relationship between biodiversity and forest productivity and tested whether stand structural attributes (stand density in terms of trees per ha, age and tree size) and environmental factors (climate and site conditions) had larger effects on productivity. Furthermore, we quantified the relative importance of environmental factors, stand structure and diversity in determining forest productivity. Diversity, together with stand structure and site conditions, regulated the variability in forest productivity. The relationship between diversity and forest productivity did not vary along environmental gradients. Stand density and age were more important modulators of forest productivity than diversity. Synthesis . Diversity had significant and positive effects on productivity in species‐rich subtropical forests, but the effects of stand density and age were also important. Our work highlights that while biodiversity conservation is often important, the regulation of stand structure can be even more important to maintain high productivity in subtropical forests.

Nitrogen, water content, phosphorus and active iron jointly regulate soil organic carbon in tropical acid red soil forest - Bai, Jinyue; Zong, Mingming; Li, Shiyu; Li, Haixia; Duan, Changqun; Feng, Yuan; Peng, Changhui; Zhang, Xiaoling; Sun, Di; Lin, Chen; Shi, Yucheng; Zheng, Guangyu; et al. (European Journal of Soil Science, 2021)
Abstract Increasing forest soil organic carbon (SOC) storage is important for reducing carbon dioxide (CO 2 ) emissions from terrestrial ecosystems and mitigating global climate change. Although the effects of altitude, temperature and rainfall on organic carbon have been studied extensively, it is difficult to increase SOC storage by changing these factors in actual forest management. This study determined the SOC, soil physical and chemical properties, nutrient elements, heavy metal elements, soil minerals and microbial biomass in the 0–140‐cm soil layer of the monsoon broad‐leaved forest in the acid red soil region of southwestern China by stratification. We tried to identify the soil factors affecting the SOC storage of the forest in the acid red soil region and determine the weights of the factors affecting the SOC, with the aim of improving the SOC retention capacity in forest management by changing the main soil factors affecting SOC storage. The results showed that the soil factors affecting the forest SOC storage in this area are total nitrogen (N, 22.7%) > soil water content (19.9%) > active iron (including poorly crystalline iron, Fe o , 15.5%) > pH (9.5%) > phosphorus (P, 9.4%) > aluminium (Al, 8.9%) > silicon (Si, 7.1%) > sulphur (S, 6.8%). Of these factors, N, the water content, Fe o , and P are practical factors for forest management, whereas the pH, Al, Si and S are not. SOC was significantly positively correlated with the soil N concentration, water content, active iron content and P concentration ( p < .05). In acidic red soil areas, with active iron as the highlight, N, soil water content, phosphorus and active iron jointly regulate the forest SOC storage capacity. Consequently, in actual forest management, any measures to promote soil N and water content and to activate inactive iron can enhance the storage of SOC, as appropriate input of N and P fertiliser and irrigation in dry years and the dry season. Highlights The soil environmental factors affecting SOC storage in forest soil are quantified Activation of inactive iron helps SOC storage in forest soil Irrigation and N and P input are effective for helping SOC storage in forest soil N, WC, P and Fe o jointly regulate SOC in tropical acid red soil forest

Modern cities modelled as “super‐cells” rather than multicellular organisms: Implications for industry, goods and services - Chang, Jie; Ge, Ying; Wu, Zhaoping; Du, Yuanyuan; Pan, Kaixuan; Yang, Guofu; Ren, Yuan; Heino, Mikko P.; Mao, Feng; Cheong, Kang Hao; Qu, Zelong; Fan, Xing; et al. (BioEssays, 2021)
Abstract The structure and “metabolism” (movement and conversion of goods and energy) of urban areas has caused cities to be identified as “super‐organisms”, placed between ecosystems and the biosphere, in the hierarchy of living systems. Yet most such analogies are weak, and render the super‐organism model ineffective for sustainable development of cities. Via a cluster analysis of 15 shared traits of the hierarchical living system, we found that industrialized cities are more similar to eukaryotic cells than to multicellular organisms; enclosed systems, such as factories and greenhouses, paralleling organelles in eukaryotic cells. We further developed a “super‐cell” industrialized city model: a “eukarcity” with citynucleus (urban area) as a regulating centre, and organaras (enclosed systems, which provide the majority of goods and services) as the functional components, and cityplasm (natural ecosystems and farmlands) as the matrix. This model may improve the vitality and sustainability of cities through planning and management.

Exposures to temperature beyond threshold disproportionately reduce vegetation growth in the northern hemisphere - Wu, Xiuchen; Guo, Weichao; Liu, Hongyan; Li, Xiaoyan; Peng, Changhui; Allen, Craig D; Zhang, Cicheng; Wang, Pei; Pei, Tingting; Ma, Yujun; Tian, Yuhong; Song, Zhaoliang; et al. (National Science Review, 2019)
Abstract In recent decades, terrestrial vegetation in the northern hemisphere (NH) has been exposed to warming and more extremely high temperatures. However, the consequences of these changes for terrestrial vegetation growth remain poorly quantified and understood. By examining a satellite-based vegetation index, tree-ring measurements and land-surface model simulations, we discovered a consistent convex pattern in the responses of vegetation growth to temperature exposure (TE) for forest, shrub and grass in both the temperate (30°−50° N) and boreal (50°−70° N) NH during the period of 1982−2012. The response of vegetation growth to TE for the three vegetation types in both the temperate and boreal NH increased convergently with increasing temperature, until vegetation type-dependent temperature thresholds were reached. A TE beyond these temperature thresholds resulted in disproportionately weak positive or even strong negative responses. Vegetation growth in the boreal NH was more vulnerable to extremely high-temperature events than vegetation growth in the temporal NH. The non-linear responses discovered here provide new insights into the dynamics of northern terrestrial ecosystems in a warmer world.

The impacts of climate change and human activities on biogeochemical cycles on the Q inghai‐ T ibetan P lateau - Chen, Huai; Zhu, Qiuan; Peng, Changhui; Wu, Ning; Wang, Yanfen; Fang, Xiuqing; Gao, Yongheng; Zhu, Dan; Yang, Gang; Tian, Jianqing; Kang, Xiaoming; Piao, Shilong; et al. (Global Change Biology, 2013)
Abstract With a pace of about twice the observed rate of global warming, the temperature on the Qinghai‐Tibetan Plateau (Earth's ‘third pole’) has increased by 0.2 °C per decade over the past 50 years, which results in significant permafrost thawing and glacier retreat. Our review suggested that warming enhanced net primary production and soil respiration, decreased methane ( CH 4 ) emissions from wetlands and increased CH 4 consumption of meadows, but might increase CH 4 emissions from lakes. Warming‐induced permafrost thawing and glaciers melting would also result in substantial emission of old carbon dioxide ( CO 2 ) and CH 4 . Nitrous oxide ( N 2 O ) emission was not stimulated by warming itself, but might be slightly enhanced by wetting. However, there are many uncertainties in such biogeochemical cycles under climate change. Human activities (e.g. grazing, land cover changes) further modified the biogeochemical cycles and amplified such uncertainties on the plateau. If the projected warming and wetting continues, the future biogeochemical cycles will be more complicated. So facing research in this field is an ongoing challenge of integrating field observations with process‐based ecosystem models to predict the impacts of future climate change and human activities at various temporal and spatial scales. To reduce the uncertainties and to improve the precision of the predictions of the impacts of climate change and human activities on biogeochemical cycles, efforts should focus on conducting more field observation studies, integrating data within improved models, and developing new knowledge about coupling among carbon, nitrogen, and phosphorus biogeochemical cycles as well as about the role of microbes in these cycles.

Carbon in Chinese grasslands: meta-analysis and theory of grazing effects - Deng, Lei; Shangguan, Zhouping; Bell, Stephen Mackenzie; Soromotin, Andrey V.; Peng, Changhui; An, Shaoshan; Wu, Xing; Xu, Xingliang; Wang, Kaibo; Li, Jianping; Tang, Zhuangsheng; Yan, Weiming; et al. (Carbon Research, 2023)
Abstract Globally, livestock grazing is an important management factor influencing soil degradation, soil health and carbon (C) stocks of grassland ecosystems. However, the effects of grassland types, grazing intensity and grazing duration on C stocks are unclear across large geographic scales. To provide a more comprehensive assessment of how grazing drives ecosystem C stocks in grasslands, we compiled and analyzed data from 306 studies featuring four grassland types across China: desert steppes, typical steppes, meadow steppes and alpine steppes. Light grazing was the best management practice for desert steppes (< 2 sheep ha −1 ) and typical steppes (3 to 4 sheep ha −1 ), whereas medium grazing pressure was optimal for meadow steppes (5 to 6 sheep ha −1 ) and alpine steppes (7 to 8 sheep ha −1 ) leading to the highest ecosystem C stocks under grazing. Plant biomass (desert steppes) and soil C stocks (meadow steppes) increased under light or medium grazing, confirming the ‘ intermediate disturbance hypothesis ’. Heavy grazing decreased all C stocks regardless of grassland ecosystem types, approximately 1.4 Mg ha −1 per year for the whole ecosystem. The regrowth and regeneration of grasslands in response to grazing intensity (i.e., grazing optimization ) depended on grassland types and grazing duration. In conclusion, grassland grazing is a double-edged sword. On the one hand, proper management (light or medium grazing) can maintain and even increase C stocks above- and belowground, and increase the harvested livestock products from grasslands. On the other hand, human-induced overgrazing can lead to rapid degradation of vegetation and soils, resulting in significant carbon loss and requiring long-term recovery. Grazing regimes (i.e., intensity and duration applied) must consider specific grassland characteristics to ensure stable productivity rates and optimal impacts on ecosystem C stocks. Graphical Abstract

Pervasive decreases in living vegetation carbon turnover time across forest climate zones - Yu, Kailiang; Smith, William K.; Trugman, Anna T.; Condit, Richard; Hubbell, Stephen P.; Sardans, Jordi; Peng, Changhui; Zhu, Kai; Peñuelas, Josep; Cailleret, Maxime; Levanic, Tom; Gessler, Arthur; et al. (Proceedings of the National Academy of Sciences, 2019)
Forests play a major role in the global carbon cycle. Previous studies on the capacity of forests to sequester atmospheric CO 2 have mostly focused on carbon uptake, but the roles of carbon turnover time and its spatiotemporal changes remain poorly understood. Here, we used long-term inventory data (1955 to 2018) from 695 mature forest plots to quantify temporal trends in living vegetation carbon turnover time across tropical, temperate, and cold climate zones, and compared plot data to 8 Earth system models (ESMs). Long-term plots consistently showed decreases in living vegetation carbon turnover time, likely driven by increased tree mortality across all major climate zones. Changes in living vegetation carbon turnover time were negatively correlated with CO 2 enrichment in both forest plot data and ESM simulations. However, plot-based correlations between living vegetation carbon turnover time and climate drivers such as precipitation and temperature diverged from those of ESM simulations. Our analyses suggest that forest carbon sinks are likely to be constrained by a decrease in living vegetation carbon turnover time, and accurate projections of forest carbon sink dynamics will require an improved representation of tree mortality processes and their sensitivity to climate in ESMs.

Global net climate effects of anthropogenic reactive nitrogen - Gong, Cheng; Tian, Hanqin; Liao, Hong; Pan, Naiqing; Pan, Shufen; Ito, Akihiko; Jain, Atul K.; Kou-Giesbrecht, Sian; Joos, Fortunat; Sun, Qing; Shi, Hao; Vuichard, Nicolas; et al. (Nature, 2024)
Abstract Anthropogenic activities have substantially enhanced the loadings of reactive nitrogen (Nr) in the Earth system since pre-industrial times 1,2 , contributing to widespread eutrophication and air pollution 3–6 . Increased Nr can also influence global climate through a variety of effects on atmospheric and land processes but the cumulative net climate effect is yet to be unravelled. Here we show that anthropogenic Nr causes a net negative direct radiative forcing of −0.34 [−0.20, −0.50] W m −2 in the year 2019 relative to the year 1850. This net cooling effect is the result of increased aerosol loading, reduced methane lifetime and increased terrestrial carbon sequestration associated with increases in anthropogenic Nr, which are not offset by the warming effects of enhanced atmospheric nitrous oxide and ozone. Future predictions using three representative scenarios show that this cooling effect may be weakened primarily as a result of reduced aerosol loading and increased lifetime of methane, whereas in particular N 2 O-induced warming will probably continue to increase under all scenarios. Our results indicate that future reductions in anthropogenic Nr to achieve environmental protection goals need to be accompanied by enhanced efforts to reduce anthropogenic greenhouse gas emissions to achieve climate change mitigation in line with the Paris Agreement.

A global strategy to mitigate the environmental impact of China’s ruminant consumption boom - Du, Yuanyuan; Ge, Ying; Ren, Yuan; Fan, Xing; Pan, Kaixuan; Lin, Linshan; Wu, Xu; Min, Yong; Meyerson, Laura A.; Heino, Mikko; Chang, Scott X.; Liu, Xiaozi; et al. (Nature Communications, 2018)
Abstract Rising demand for ruminant meat and dairy products in developing countries is expected to double anthropogenic greenhouse gas and ammonia emissions from livestock by 2050. Mitigation strategies are urgently needed to meet demand while minimizing environmental impacts. Here, we develop scenarios for mitigating emissions under local vs global supply policies using data from 308 livestock farms across mainland China, where emissions intensities are ~50% higher than those in developed nations. Intensification of domestic production and globalized expansion through increased trade result in reductions in global emissions by nearly 30% over a business-as-usual scenario, but at the expense of trading partners absorbing the associated negative externalities of environmental degradation. Only adoption of a mixed strategy combining global best-practice in sustainable intensification of domestic production, with increased green-source trading as a short-term coping strategy, can meet 2050 demand while minimizing the local and global environmental footprint of China’s ruminant consumption boom.

The carbon stock of alpine peatlands on the Qinghai–Tibetan Plateau during the Holocene and their future fate - Chen, Huai; Yang, Gang; Peng, Changhui; Zhang, Yao; Zhu, Dan; Zhu, Qiuan; Hu, Ji; Wang, Mei; Zhan, Wei; Zhu, Erxiong; Bai, Zengzhi; Li, Wei; et al. (Quaternary Science Reviews, 2014)

Integrating terrestrial and aquatic ecosystems to constrain estimates of land-atmosphere carbon exchange - Casas-Ruiz, Joan P.; Bodmer, Pascal; Bona, Kelly Ann; Butman, David; Couturier, Mathilde; Emilson, Erik J. S.; Finlay, Kerri; Genet, Hélène; Hayes, Daniel; Karlsson, Jan; Paré, David; Peng, Changhui; et al. (Nature Communications, 2023)
Abstract In this Perspective, we put forward an integrative framework to improve estimates of land-atmosphere carbon exchange based on the accumulation of carbon in the landscape as constrained by its lateral export through rivers. The framework uses the watershed as the fundamental spatial unit and integrates all terrestrial and aquatic ecosystems as well as their hydrologic carbon exchanges. Application of the framework should help bridge the existing gap between land and atmosphere-based approaches and offers a platform to increase communication and synergy among the terrestrial, aquatic, and atmospheric research communities that is paramount to advance landscape carbon budget assessments.

Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region - Cui, Erqian; Huang, Kun; Arain, Muhammad Altaf; Fisher, Joshua B.; Huntzinger, Deborah N.; Ito, Akihiko; Luo, Yiqi; Jain, Atul K.; Mao, Jiafu; Michalak, Anna M.; Niu, Shuli; Parazoo, Nicholas C.; et al. (Global Biogeochemical Cycles, 2019)
Abstract Global and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe‐Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon‐use efficiency (CUE), vegetation C turnover time ( τ veg ), leaf C fraction (F leaf ), specific leaf area (SLA), and leaf area index (LAI)‐level photosynthesis (P LAI ), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901–2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 ± 21.3%), τ veg (18.2 ± 26.9%), and SLA (27.4±36.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. These results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems. , Key Points A GPP‐traceability framework is established to diagnose the uncertainty sources of modeled GPP Large intermodel differences of modeled GPP result from their different representation of vegetation functional properties Positive bias in simulated GPP over the East Asian monsoon region could be attributed to the higher simulated CUE and SLA comparing with observations

Global vegetation biomass production efficiency constrained by models and observations - He, Yue; Peng, Shushi; Liu, Yongwen; Li, Xiangyi; Wang, Kai; Ciais, Philippe; Arain, M. Altaf; Fang, Yuanyuan; Fisher, Joshua B.; Goll, Daniel; Hayes, Daniel; Huntzinger, Deborah N.; et al. (Global Change Biology, 2020)
Abstract Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon–nitrogen interactions tend to be more realistic. Using observation‐based estimates of global photosynthesis, we quantify the global BP of non‐cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model‐estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).

Global wetland contribution to 2000–2012 atmospheric methane growth rate dynamics - Poulter, Benjamin; Bousquet, Philippe; Canadell, Josep G; Ciais, Philippe; Peregon, Anna; Saunois, Marielle; Arora, Vivek K; Beerling, David J; Brovkin, Victor; Jones, Chris D; Joos, Fortunat; Gedney, Nicola; et al. (Environmental Research Letters, 2017)
Abstract Increasing atmospheric methane (CH 4 ) concentrations have contributed to approximately 20% of anthropogenic climate change. Despite the importance of CH 4 as a greenhouse gas, its atmospheric growth rate and dynamics over the past two decades, which include a stabilization period (1999–2006), followed by renewed growth starting in 2007, remain poorly understood. We provide an updated estimate of CH 4 emissions from wetlands, the largest natural global CH 4 source, for 2000–2012 using an ensemble of biogeochemical models constrained with remote sensing surface inundation and inventory-based wetland area data. Between 2000–2012, boreal wetland CH 4 emissions increased by 1.2 Tg yr −1 (−0.2–3.5 Tg yr −1 ), tropical emissions decreased by 0.9 Tg yr −1 (−3.2−1.1 Tg yr −1 ), yet globally, emissions remained unchanged at 184 ± 22 Tg yr −1 . Changing air temperature was responsible for increasing high-latitude emissions whereas declines in low-latitude wetland area decreased tropical emissions; both dynamics are consistent with features of predicted centennial-scale climate change impacts on wetland CH 4 emissions. Despite uncertainties in wetland area mapping, our study shows that global wetland CH 4 emissions have not contributed significantly to the period of renewed atmospheric CH 4 growth, and is consistent with findings from studies that indicate some combination of increasing fossil fuel and agriculture-related CH 4 emissions, and a decrease in the atmospheric oxidative sink.

Sectoral approaches to improve regional carbon budgets - Smith, Pete; Nabuurs, Gert-Jan; Janssens, Ivan A.; Reis, Stefan; Marland, Gregg; Soussana, Jean-François; Christensen, Torben R.; Heath, Linda; Apps, Mike; Alexeyev, Vlady; Fang, Jingyun; Gattuso, Jean-Pierre; et al. (Climatic Change, 2008)

Global soil nitrous oxide emissions since the preindustrial era estimated by an ensemble of terrestrial biosphere models: Magnitude, attribution, and uncertainty - Tian, Hanqin; Yang, Jia; Xu, Rongting; Lu, Chaoqun; Canadell, Josep G.; Davidson, Eric A.; Jackson, Robert B.; Arneth, Almut; Chang, Jinfeng; Ciais, Philippe; Gerber, Stefan; Ito, Akihiko; et al. (Global Change Biology, 2019)
Abstract Our understanding and quantification of global soil nitrous oxide (N 2 O) emissions and the underlying processes remain largely uncertain. Here, we assessed the effects of multiple anthropogenic and natural factors, including nitrogen fertilizer (N) application, atmospheric N deposition, manure N application, land cover change, climate change, and rising atmospheric CO 2 concentration, on global soil N 2 O emissions for the period 1861–2016 using a standard simulation protocol with seven process‐based terrestrial biosphere models. Results suggest global soil N 2 O emissions have increased from 6.3 ± 1.1 Tg N 2 O‐N/year in the preindustrial period (the 1860s) to 10.0 ± 2.0 Tg N 2 O‐N/year in the recent decade (2007–2016). Cropland soil emissions increased from 0.3 Tg N 2 O‐N/year to 3.3 Tg N 2 O‐N/year over the same period, accounting for 82% of the total increase. Regionally, China, South Asia, and Southeast Asia underwent rapid increases in cropland N 2 O emissions since the 1970s. However, US cropland N 2 O emissions had been relatively flat in magnitude since the 1980s, and EU cropland N 2 O emissions appear to have decreased by 14%. Soil N 2 O emissions from predominantly natural ecosystems accounted for 67% of the global soil emissions in the recent decade but showed only a relatively small increase of 0.7 ± 0.5 Tg N 2 O‐N/year (11%) since the 1860s. In the recent decade, N fertilizer application, N deposition, manure N application, and climate change contributed 54%, 26%, 15%, and 24%, respectively, to the total increase. Rising atmospheric CO 2 concentration reduced soil N 2 O emissions by 10% through the enhanced plant N uptake, while land cover change played a minor role. Our estimation here does not account for indirect emissions from soils and the directed emissions from excreta of grazing livestock. To address uncertainties in estimating regional and global soil N 2 O emissions, this study recommends several critical strategies for improving the process‐based simulations.

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates - Chang, Kuang‐Yu; Riley, William J.; Collier, Nathan; McNicol, Gavin; Fluet‐Chouinard, Etienne; Knox, Sara H.; Delwiche, Kyle B.; Jackson, Robert B.; Poulter, Benjamin; Saunois, Marielle; Chandra, Naveen; Gedney, Nicola; et al. (Global Change Biology, 2023)
Abstract The recent rise in atmospheric methane (CH 4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH 4 source, estimates of global wetland CH 4 emissions vary widely among approaches taken by bottom‐up (BU) process‐based biogeochemical models and top‐down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi‐model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking system to examine the relationship between wetland CH 4 emission estimates and model performance. We find that using better‐performing models identified by observational constraints reduces the spread of wetland CH 4 emission estimates by 62% and 39% for BU‐ and TD‐based approaches, respectively. However, global BU and TD CH 4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH 4 year −1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter‐site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH 4 models to move beyond static benchmarking and focus on evaluating site‐specific and ecosystem‐specific variabilities inferred from observations.

The Global N2O Model Intercomparison Project - Tian, Hanqin; Yang, Jia; Lu, Chaoqun; Xu, Rongting; Canadell, Josep G.; Jackson, Robert B.; Arneth, Almut; Chang, Jinfeng; Chen, Guangsheng; Ciais, Philippe; Gerber, Stefan; Ito, Akihiko; et al. (Bulletin of the American Meteorological Society, 2018)
Abstract Nitrous oxide (N 2 O) is an important greenhouse gas and also an ozone-depleting substance that has both natural and anthropogenic sources. Large estimation uncertainty remains on the magnitude and spatiotemporal patterns of N 2 O fluxes and the key drivers of N 2 O production in the terrestrial biosphere. Some terrestrial biosphere models have been evolved to account for nitrogen processes and to show the capability to simulate N 2 O emissions from land ecosystems at the global scale, but large discrepancies exist among their estimates primarily because of inconsistent input datasets, simulation protocol, and model structure and parameterization schemes. Based on the consistent model input data and simulation protocol, the global N 2 O Model Intercomparison Project (NMIP) was initialized with 10 state-of-the-art terrestrial biosphere models that include nitrogen (N) cycling. Specific objectives of NMIP are to 1) unravel the major N cycling processes controlling N 2 O fluxes in each model and identify the uncertainty sources from model structure, input data, and parameters; 2) quantify the magnitude and spatial and temporal patterns of global and regional N 2 O fluxes from the preindustrial period (1860) to present and attribute the relative contributions of multiple environmental factors to N 2 O dynamics; and 3) provide a benchmarking estimate of N 2 O fluxes through synthesizing the multimodel simulation results and existing estimates from ground-based observations, inventories, and statistical and empirical extrapolations. This study provides detailed descriptions for the NMIP protocol, input data, model structure, and key parameters, along with preliminary simulation results. The global and regional N 2 O estimation derived from the NMIP is a key component of the global N 2 O budget synthesis activity jointly led by the Global Carbon Project and the International Nitrogen Initiative.

Uncertainty analysis of terrestrial net primary productivity and net biome productivity in China during 1901–2005 - Shao, Junjiong; Zhou, Xuhui; Luo, Yiqi; Zhang, Guodong; Yan, Wei; Li, Jiaxuan; Li, Bo; Dan, Li; Fisher, Joshua B.; Gao, Zhiqiang; He, Yong; Huntzinger, Deborah; et al. (Journal of Geophysical Research: Biogeosciences, 2016)
Abstract Despite the importance of net primary productivity (NPP) and net biome productivity (NBP), estimates of NPP and NBP for China are highly uncertain. To investigate the main sources of uncertainty, we synthesized model estimates of NPP and NBP for China from published literature and the Multi‐scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). The literature‐based results showed that total NPP and NBP in China were 3.35 ± 1.25 and 0.14 ± 0.094 Pg C yr −1 , respectively. Classification and regression tree analysis based on literature data showed that model type was the primary source of the uncertainty, explaining 36% and 64% of the variance in NPP and NBP, respectively. Spatiotemporal scales, land cover conditions, inclusion of the N cycle, and effects of N addition also contributed to the overall uncertainty. Results based on the MsTMIP data suggested that model structures were overwhelmingly important (>90%) for the overall uncertainty compared to simulations with different combinations of time‐varying global change factors. The interannual pattern of NPP was similar among diverse studies and increased by 0.012 Pg C yr −1 during 1981–2000. In addition, high uncertainty in China's NPP occurred in areas with high productivity, whereas NBP showed the opposite pattern. Our results suggest that to significantly reduce uncertainty in estimated NPP and NBP, model structures should be substantially tested on the basis of empirical results. To this end, coordinated distributed experiments with multiple global change factors might be a practical approach that can validate specific structures of different models. , Key Points Large uncertainty exists in estimates of terrestrial NPP and NBP in China Methodological differences greatly contribute to the uncertainty in NPP and NBP Uncertainty in the interannual pattern of NBP is greater than that of NPP

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET‐CH4 Sites Using Wavelet Analyses - Zhang, Zhen; Bansal, Sheel; Chang, Kuang‐Yu; Fluet‐Chouinard, Etienne; Delwiche, Kyle; Goeckede, Mathias; Gustafson, Adrian; Knox, Sara; Leppänen, Antti; Liu, Licheng; Liu, Jinxun; Malhotra, Avni; et al. (Journal of Geophysical Research: Biogeosciences, 2023)
Abstract Process‐based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site‐level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model‐observation disagreements are mainly at multi‐day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments. , Plain Language Summary Land surface models are useful tools to estimate and predict wetland methane (CH 4 ) flux but there is no evaluation of modeled CH 4 flux error at different time scales. Here we use a statistical approach and observations from eddy covariance sites to evaluate the performance of seven wetland models for different wetland types. The results suggest models have captured CH 4 flux variability at monthly or seasonal time scales for boreal and Arctic tundra wetlands but failed to capture the observed seasonal variability for temperate and tropical/subtropical wetlands. The analysis suggests that improving modeled flux at short time scale is important for future model development. , Key Points Significant model‐observation disagreements were found at multi‐day and weekly time scales (<15 days) Models captured variability at monthly and seasonal time (42–142 days) scales for boreal and Arctic tundra sites but not for temperate and tropical sites The model errors show that biases at multi‐day time scales may contribute to persistent systematic biases on longer time scales

Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends - Mao, Jiafu; Fu, Wenting; Shi, Xiaoying; Ricciuto, Daniel M; Fisher, Joshua B; Dickinson, Robert E; Wei, Yaxing; Shem, Willis; Piao, Shilong; Wang, Kaicun; Schwalm, Christopher R; Tian, Hanqin; et al. (Environmental Research Letters, 2015)

Field-experiment constraints on the enhancement of the terrestrial carbon sink by CO2 fertilization - Liu, Yongwen; Piao, Shilong; Gasser, Thomas; Ciais, Philippe; Yang, Hui; Wang, Han; Keenan, Trevor F.; Huang, Mengtian; Wan, Shiqiang; Song, Jian; Wang, Kai; Janssens, Ivan A.; et al. (Nature Geoscience, 2019)

Characterizing the performance of ecosystem models across time scales: A spectral analysis of the North American Carbon Program site-level synthesis - Dietze, Michael C.; Vargas, Rodrigo; Richardson, Andrew D.; Stoy, Paul C.; Barr, Alan G.; Anderson, Ryan S.; Arain, M. Altaf; Baker, Ian T.; Black, T. Andrew; Chen, Jing M.; Ciais, Philippe; Flanagan, Lawrence B.; et al. (Journal of Geophysical Research, 2011)

Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand? - Paschalis, Athanasios; Fatichi, Simone; Zscheischler, Jakob; Ciais, Philippe; Bahn, Michael; Boysen, Lena; Chang, Jinfeng; De Kauwe, Martin; Estiarte, Marc; Goll, Daniel; Hanson, Paul J.; Harper, Anna B.; et al. (Global Change Biology, 2020)
Abstract Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model‐data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter‐model variation is generally large and model agreement varies with timescales. In severely water‐limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily–monthly) timescales and reduces on longer (seasonal–annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter‐model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.

Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites - Wu, Donghai; Ciais, Philippe; Viovy, Nicolas; Knapp, Alan K.; Wilcox, Kevin; Bahn, Michael; Smith, Melinda D.; Vicca, Sara; Fatichi, Simone; Zscheischler, Jakob; He, Yue; Li, Xiangyi; et al. (Biogeosciences, 2018)
Abstract. Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

A model‐data intercomparison of CO2 exchange across North America: Results from the North American Carbon Program site synthesis - Schwalm, Christopher R.; Williams, Christopher A.; Schaefer, Kevin; Anderson, Ryan; Arain, M. Altaf; Baker, Ian; Barr, Alan; Black, T. Andrew; Chen, Guangsheng; Chen, Jing Ming; Ciais, Philippe; Davis, Kenneth J.; et al. (Journal of Geophysical Research: Biogeosciences, 2010)
Our current understanding of terrestrial carbon processes is represented in various models used to integrate and scale measurements of CO 2 exchange from remote sensing and other spatiotemporal data. Yet assessments are rarely conducted to determine how well models simulate carbon processes across vegetation types and environmental conditions. Using standardized data from the North American Carbon Program we compare observed and simulated monthly CO 2 exchange from 44 eddy covariance flux towers in North America and 22 terrestrial biosphere models. The analysis period spans ∼220 site‐years, 10 biomes, and includes two large‐scale drought events, providing a natural experiment to evaluate model skill as a function of drought and seasonality. We evaluate models' ability to simulate the seasonal cycle of CO 2 exchange using multiple model skill metrics and analyze links between model characteristics, site history, and model skill. Overall model performance was poor; the difference between observations and simulations was ∼10 times observational uncertainty, with forested ecosystems better predicted than nonforested. Model‐data agreement was highest in summer and in temperate evergreen forests. In contrast, model performance declined in spring and fall, especially in ecosystems with large deciduous components, and in dry periods during the growing season. Models used across multiple biomes and sites, the mean model ensemble, and a model using assimilated parameter values showed high consistency with observations. Models with the highest skill across all biomes all used prescribed canopy phenology, calculated NEE as the difference between GPP and ecosystem respiration, and did not use a daily time step.

A model‐data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis - Schaefer, Kevin; Schwalm, Christopher R.; Williams, Chris; Arain, M. Altaf; Barr, Alan; Chen, Jing M.; Davis, Kenneth J.; Dimitrov, Dimitre; Hilton, Timothy W.; Hollinger, David Y.; Humphreys, Elyn; Poulter, Benjamin; et al. (Journal of Geophysical Research: Biogeosciences, 2012)
Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States and Canada. None of the models in this study match estimated GPP within observed uncertainty. On average, models overestimate GPP in winter, spring, and fall, and underestimate GPP in summer. Models overpredicted GPP under dry conditions and for temperatures below 0°C. Improvements in simulated soil moisture and ecosystem response to drought or humidity stress will improve simulated GPP under dry conditions. Adding a low‐temperature response to shut down GPP for temperatures below 0°C will reduce the positive bias in winter, spring, and fall and improve simulated phenology. The negative bias in summer and poor overall performance resulted from mismatches between simulated and observed light use efficiency (LUE). Improving simulated GPP requires better leaf‐to‐canopy scaling and better values of model parameters that control the maximum potential GPP, such as ε max (LUE), V cmax (unstressed Rubisco catalytic capacity) or J max (the maximum electron transport rate). , Key Points Gross primary productivity (GPP) from 26 models tested at 39 flux tower sites Simulated light use efficiency controls model performance Models overpredict GPP under dry conditions

Biomass offsets little or none of permafrost carbon release from soils, streams, and wildfire: an expert assessment - Abbott, Benjamin W; Jones, Jeremy B; Schuur, Edward A G; Chapin Iii, F Stuart; Bowden, William B; Bret-Harte, M Syndonia; Epstein, Howard E; Flannigan, Michael D; Harms, Tamara K; Hollingsworth, Teresa N; Mack, Michelle C; McGuire, A David; et al. (Environmental Research Letters, 2016)