Future changes and driving factors of global peak vegetation growth based on CMIP6 simulations |
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| Institution: | 1. School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China;2. ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou 311200, China;3. Department of Land Resource Management, School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330013, China;4. College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China;5. Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang Province, Hangzhou 310058, China.;1. Achutha Menon Centre for Health Science Studies, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India;2. Department of Health and Family Welfare, Government of Punjab, India;1. Environmental Systems Engineering, Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2, Canada;2. Johnson Shoyama Graduate School of Public Policy, University of Regina, Saskatchewan S4S 0A2, Canada;1. Department of Zoology, Entomology & Fisheries Sciences, Makerere University, P.O. Box 7062, Kampala, Uganda;2. Department of Biology, Coe College, 1220 1st Avenue NE, Cedar Rapids, IA 52402, USA;1. Department of Computer Science and Engineering, Y.S.R University College of Engineering & Technology, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India;2. Department of Computer Science and Engineering, R.V.R. & J.C. College of Engineering, Guntur, Andhra Pradesh, India;3. Department of Computer Science and Engineering, V.R. Siddhartha Engineering College, Vijayawada, Andhra Pradesh, India |
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| Abstract: | Accurate detection and attribution of changes in global peak vegetation growth at the annual scale are prerequisites for characterising the productivity of terrestrial ecosystems and developing strategies for the sustainable management of ecosystems. This study examined the long-term global normalised difference vegetation index during the baseline period (1982–2015) and found widespread greening in 70% of global vegetated areas in response to climate warming. However, climate change is not the only cause of global greening. The spatial variability in the response of global vegetation to environmental factors has not been well established. The Cubist model was used to investigate the relationship between peak vegetation growth and environmental variables. The results showed that 64% of the spatial variation in greening/browning can be explained by climate (including precipitation and temperature), followed by atmospheric components of nitrogen deposition and carbon dioxide concentration (17%), terrain properties (12%), and soil properties (7%). By incorporating future climate and atmospheric component projections from the Coupled Model Intercomparison Project Phase 6 into the model, enhanced vegetation greening was predicted globally, particularly in evergreen needle-leaf forests and grasslands, from 2081 to 2100. Many browning changes were predicted in evergreen and deciduous broadleaf forests, mixed forests, and around areas influenced by human land use. Overall, these findings reveal that environmental factors have relevant integrated impacts on vegetation dynamics under climate change and should be considered during the design of local mitigation and adaptation management strategies. |
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