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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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