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.

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.

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.

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)

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)

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)

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.

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)

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.

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)

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.

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)

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)

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)

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.

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)

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)

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)

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.

Soil GHG fluxes are altered by N deposition: New data indicate lower N stimulation of the N_2 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.

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.

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).

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)

Nitrogen addition increased CO_2 uptake more than non-CO_2 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 .

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.

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)

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)

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.

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)

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)

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)

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.

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.

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

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

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.

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)

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.

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.

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)

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.

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.

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)

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.

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.

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.

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.

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)

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.

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)

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

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)

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)

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.

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)

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)

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)

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)

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

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.

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.

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.

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)

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)

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)

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)

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.

Effects of plant functional group removal on community structure, diversity and production in Alpine meadow - Jiang Lin, 姜林，胡骥，杨振安，詹伟，赵川，朱单，何奕忻，陈槐，彭长辉 (Acta Ecologica Sinica, 2021)

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.

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.

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.

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)

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)

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)

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.

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.

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.

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)

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.

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)

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.

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.

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)

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)

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.

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)

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)

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.

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)

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)

Cold‐Season Methane Fluxes Simulated by GCP‐CH_4 Models - Ito, A.; Li, T.; Qin, Z.; Melton, J. R.; Tian, H.; Kleinen, T.; Zhang, W.; Zhang, Z.; Joos, F.; Ciais, P.; Hopcroft, P. O.; Beerling, D. J.; et al. (Geophysical Research Letters, 2023)
Abstract Cold‐season methane (CH 4 ) emissions may be poorly constrained in wetland models. We examined cold‐season CH 4 emissions simulated by 16 models participating in the Global Carbon Project model intercomparison and analyzed temporal and spatial patterns in simulation results using prescribed inundation data for 2000–2020. Estimated annual CH 4 emissions from northern (>60°N) wetlands averaged 10.0 ± 5.5 Tg CH 4 yr −1 . While summer CH 4 emissions were well simulated compared to in‐situ flux measurement observations, the models underestimated CH 4 during September to May relative to annual total (27 ± 9%, compared to 45% in observations) and substantially in the months with subzero air temperatures (5 ± 5%, compared to 27% in observations). Because of winter warming, nevertheless, the contribution of cold‐season emissions was simulated to increase at 0.4 ± 0.8% decade −1 . Different parameterizations of processes, for example, freezing–thawing and snow insulation, caused conspicuous variability among models, implying the necessity of model refinement. , Plain Language Summary Wetlands in the northern high latitudes are a major source of methane (CH 4 ) to the atmosphere, mainly during the warm season. Previously, models have assumed that cold‐season CH 4 emissions are low, but recent observations suggest high‐latitude wetlands can be substantial sources even in winter. We compared CH 4 emissions simulated by 16 state‐of‐the‐art wetland models, participating in a model intercomparison project with a focus on the cold‐season in northern wetlands. The model simulations indicated that nearly one third of annual emissions were simulated to occur from September to May, and CH 4 emissions to the atmosphere were not negligible even under freezing air temperatures, although the results differed greatly among the models. However, field studies suggest cold‐season emissions account for an even larger fraction of annual emissions. These results highlight the contribution of cold‐season emissions to the annual CH 4 budget, which future climatic warming is expected to affect severely, and they also show that simulations of cold‐season CH 4 emissions from wetlands need to be improved. , Key Points Cold‐season methane (CH 4 ) emissions simulated by 16 Global Carbon Project‐CH 4 wetland models were analyzed Most models underestimate the cold‐season emissions in comparison with observational data Further model improvement by including cold‐season processes is required to reduce the model bias and uncertainty

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.

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)

Effects of daily variation of hydro-thermal factors on alpine grassland productivity on the Qinghai-Tibet Plateau - Ma Fulin, 马扶林，刘小伟，朵莹 (Acta Ecologica Sinica, 2023)

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)

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.

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)

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)

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)

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.

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET‐CH_4 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

Research progress, challenges, and prospects of PM_2.5 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.

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)

Temporal and spatial variation of vegetation photosynthetic phenology in Dongting Lake basin and its response to climate change - Ren, Pei-Xin; Li, Peng; Peng, Chang-Hui; Zhou, Xiao-Lu; Yang, Ming-Xia; 1College of Geographic Sciences, Hunan Normal University, Changsha 410081, China; 2Department of Biology Sciences, Institute of Environment Sciences, University of Quebec at Montreal, Montreal H3C 3P8, Canada (Chinese Journal of Plant Ecology, 2023)

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)

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.

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)

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)

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)

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

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)

Global Climate Change Increases Terrestrial Soil CH_4 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

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)

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.

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)

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)

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.

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.

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)

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)

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)

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)

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.

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)

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)

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)

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.

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)

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)

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

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)

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)

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.

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.

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.

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)

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)

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)

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.

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.

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)

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.

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)

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)

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.

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

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.

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.

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.

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.

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.

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)

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)

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.