title: Grassland gross carbon dioxide uptake based on an improved model tree ensemble approach considering human interventions: global estimation and covariation with climate.
abstract: Grassland ecosystems act as a crucial role in the global carbon cycle and provide vital ecosystem services for many species. However, these low-productivity and water-limited ecosystems are sensitive and vulnerable to climate perturbations and human intervention, the latter of which is often not considered due to lack of spatial information regarding the grassland management. Here by the application of a model tree ensemble (MTE-GRASS) trained on local eddy covariance data and using as predictors gridded climate and management intensity field (grazing and cutting), we first provide an estimate of global grassland gross primary production (GPP). GPP from our study compares well (modeling efficiency NSE = 0.85 spatial; NSE between 0.69 and 0.94 interannual) with that from flux measurement. Global grassland GPP was on average 11 ± 0.31 Pg C yr-1and exhibited significantly increasing trend at both annual and seasonal scales, with an annual increase of 0.023 Pg C (0.2%) from 1982 to 2011. Meanwhile, we found that at both annual and seasonal scale, the trend (except for northern summer) and interannual variability of the GPP are primarily driven by arid/semiarid ecosystems, the latter of which is due to the larger variation in precipitation. Grasslands in arid/semiarid regions have a stronger (33 g C m-2yr-1/100 mm) and faster (0- to 1-month time lag) response to precipitation than those in other regions. Although globally spatial gradients (71%) and interannual changes (51%) in GPP were mainly driven by precipitation, where most regions with arid/semiarid climate zone, temperature and radiation together shared half of GPP variability, which is mainly distributed in the high-latitude or cold regions. Our findings and the results of other studies suggest the overwhelming importance of arid/semiarid regions as a control on grassland ecosystems carbon cycle. Similarly, under the projected future climate change, grassland ecosystems in these regions will be potentially greatly influenced.
authors.affiliation: College of Tourism and Environment, Shaanxi Normal University, Xi'an, 710119, China.|State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.|Shaanxi Key Laboratory of Tourism Informatics, Xi'an, 710119, China.|Research Center for Geographical Environment Change and Sustainable Development, Shaanxi Normal University, Xi'an, 710119, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Liang
authors.affiliation: State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
authors.forename: Yihe
authors.initials: Y
authors.lastname: Lü
authors.affiliation: College of Tourism and Environment, Shaanxi Normal University, Xi'an, 710119, China.|Shaanxi Key Laboratory of Tourism Informatics, Xi'an, 710119, China.|Research Center for Geographical Environment Change and Sustainable Development, Shaanxi Normal University, Xi'an, 710119, China.
authors.forename: Weibin
authors.initials: W
authors.lastname: Zhang
authors.affiliation: College of Tourism and Environment, Shaanxi Normal University, Xi'an, 710119, China.
authors.forename: Shuai
authors.initials: S
authors.lastname: Li
authors.affiliation: College of Tourism and Environment, Shaanxi Normal University, Xi'an, 710119, China.|Shaanxi Key Laboratory of Tourism Informatics, Xi'an, 710119, China.|Research Center for Geographical Environment Change and Sustainable Development, Shaanxi Normal University, Xi'an, 710119, China.
authors.forename: Zhao
authors.initials: Z
authors.lastname: Jin
authors.affiliation: LSCE, UMR CEA-CNRS, Bat. 709, CE, L'Orme des Merisiers, F-91191, Gif-sur-Yvette, France.
authors.forename: Philippe
authors.initials: P
authors.lastname: Ciais
authors.affiliation: State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
authors.forename: Bojie
authors.initials: B
authors.lastname: Fu
authors.affiliation: State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
authors.forename: Shuai
authors.initials: S
authors.lastname: Wang
authors.affiliation: College of Tourism and Environment, Shaanxi Normal University, Xi'an, 710119, China.|Shaanxi Key Laboratory of Tourism Informatics, Xi'an, 710119, China.|Research Center for Geographical Environment Change and Sustainable Development, Shaanxi Normal University, Xi'an, 710119, China.
authors.forename: Jianwu
authors.initials: J
authors.lastname: Yan
authors.affiliation: College of Tourism and Environment, Shaanxi Normal University, Xi'an, 710119, China.|Shaanxi Key Laboratory of Tourism Informatics, Xi'an, 710119, China.
authors.forename: Junyi
authors.initials: J
authors.lastname: Li
authors.affiliation: College of Tourism and Environment, Shaanxi Normal University, Xi'an, 710119, China.
authors.forename: Huimin
authors.initials: H
authors.lastname: Su
mesh_terms: D057486:Carbon Cycle; D002245:Carbon Dioxide; D002980:Climate; D057231:Climate Change; D017753:Ecosystem; D065948:Grassland; D014197:Trees
chemical_list: D002245:Carbon Dioxide
keywords: arid/semiarid ecosystems; climate control; data-driven method; global grassland GPP; grazing and cutting; model tree ensembles; spatiotemporal patterns