Abstract

Recent concurrent processes of vegetation greening and reduced resilience (the capacity to recover from disturbances) worldwide have brought many uncertainties into sustainable ecosystems in the future. However, little is known about the conditions and extent to which greening affects resilience changes. Here we assess both vegetation dynamics and resilience in China’s Loess Plateau from 2000 to 2020 using satellite-based vegetation data and an early warning indicator. Our results reveal an overall greening trend in vegetated areas, while resilience shifted from gains to losses at a breakpoint in 2010. Vegetation greening generally contributed to resilience gains, whereas increased temperature and precipitation variability contributed to the resilience loss observed in 2011–2020. These findings provide empirical evidence that vegetation greening does not necessarily correspond to an increase in resilience. We therefore recommend integrating resilience indicators into ecological restoration and conservation efforts to gain a more comprehensive understanding of vegetation states and support effective ecosystem stewardship.

Increased temperature and precipitation variability partially offset the greater ability of vegetation to recover from disturbances with the greening of the Chinese Loess Plateau in 2000–2020, resulting in a loss of resilience after 2010, suggests an analysis of satellite vegetation data.

Details

Title
Vegetation resilience does not increase consistently with greening in China’s Loess Plateau
Author
Wang, Zhuangzhuang 1   VIAFID ORCID Logo  ; Fu, Bojie 1   VIAFID ORCID Logo  ; Wu, Xutong 2 ; Li, Yingjie 3   VIAFID ORCID Logo  ; Feng, Yuhao 4   VIAFID ORCID Logo  ; Wang, Shuai 2   VIAFID ORCID Logo  ; Wei, Fangli 1 ; Zhang, Liwei 5 

 Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, State Key Laboratory of Urban and Regional Ecology, Beijing, China (GRID:grid.419052.b) (ISNI:0000 0004 0467 2189); University of Chinese Academy of Sciences, Beijing, China (GRID:grid.410726.6) (ISNI:0000 0004 1797 8419) 
 Beijing Normal University, State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964) 
 Stanford University, Natural Capital Project, Stanford, USA (GRID:grid.168010.e) (ISNI:0000 0004 1936 8956) 
 Peking University, Institute of Ecology, College of Urban and Environmental Sciences, Beijing, China (GRID:grid.11135.37) (ISNI:0000 0001 2256 9319) 
 School of Geography and Tourism of Shaanxi Normal University, Xi’an, China (GRID:grid.412498.2) (ISNI:0000 0004 1759 8395) 
Pages
336
Publication year
2023
Publication date
Dec 2023
Publisher
Nature Publishing Group
e-ISSN
26624435
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2867415452
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.