Future changes and driving factors of global peak vegetation growth based on CMIP6 simulations

被引:20
作者
Teng, Hongfen [1 ]
Chen, Songchao [2 ]
Hu, Bifeng [3 ]
Shi, Zhou [4 ,5 ]
机构
[1] Wuhan Inst Technol, Sch Environm Ecol & Biol Engn, Wuhan 430205, Peoples R China
[2] ZJU Hangzhou Global Sci & Technol Innovat Ctr, Hangzhou 311200, Peoples R China
[3] Jiangxi Univ Finance & Econ, Sch Tourism & Urban Management, Dept Land Resource Management, Nanchang 330013, Peoples R China
[4] Zhejiang Univ, Coll Environm & Resource Sci, Hangzhou 310058, Peoples R China
[5] Key Lab Agr Remote Sensing & Informat Syst, Hangzhou, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Future scenario; Climate change; Peak vegetation growth; Environmental driver; Machine learning; CLIMATE-CHANGE; TERRESTRIAL ECOSYSTEMS; ATMOSPHERIC CO2; LAND-COVER; GREEN-UP; SOIL; DYNAMICS; MODELS; PRECIPITATION; FEEDBACKS;
D O I
10.1016/j.ecoinf.2023.102031
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
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.
引用
收藏
页数:12
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