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

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

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

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

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

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

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

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

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

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

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

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

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

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

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