The contrasting east–west pattern of vegetation restoration under the large‐scale ecological restoration programmes in southwest China. (25th February 2020)

• Record Type: Journal Article
• Authors: Zhao, Haiwei; Wu, Ruidong; Hu, Jinming; Yang, Feiling; Wang, Junjun; Guo, Yang; Zhou, Jian; Wang, Yiting; Zhang, Chen; Feng, Zhixue
• Is Part Of: Land degradation & development. Volume 31:Number 13(2020)
• Page Start: 1688
• Page End: 1698
• Publication Date: 2020-02-25
• Subjects: ecological engineering project -- effectiveness -- land degradation -- NDVI trend -- residual trend analysis -- vegetation dynamics; Land degradation -- Periodicals; Soil conservation -- Periodicals; Reclamation of land -- Periodicals; Land use -- Periodicals; Economic development -- Environmental aspects -- Periodicals; 333.7315
• DOI: 10.1002/ldr.3520
• Languages: English
• ISSNs: 1085-3278

Abstract

Abstract: Ecological restoration programmes (ERPs) play an important role in reversing degraded ecosystems and realizing environmental sustainability. However, few studies have given attention to the spatial heterogeneity in the effectiveness of large‐scale ERPs for restoring vegetation on a broad regional scale. Based on the GIMMS NDVI3g time‐series of southwest China, we determined the spatiotemporal trends of the peak growing season NDVI (PGS‐NDVI) in the pre‐ERP stage (1982–1998) and in the post‐ERP stage (1999–2015). Using the NDVI‐climate regression model developed during the pre‐ERP stage and the residual trend analysis method, we derived the anthropogenic PGS‐NDVI trends of the post‐ERP stage on a per‐pixel and spatial average basis. We found that there existed an east (greening)–west (browning) contrasting pattern in the anthropogenic vegetation change during the post‐ERP stage. The proportions of anthropogenic greening pixels were heterogeneous among provinces, ranging from 66.1% (Guangxi) to 8.6% (Xizang). The ERP effectiveness index and the ERP efficiency index for Guangxi were the highest among the provinces, whereas they were both negative for Yunnan and Xizang. Such contrasting restoration pattern was probably caused by multiple factors, including but not limited to the imbalanced implementation of large‐scale ERPs and the inappropriate afforestation that inadequately takes into account local conditions. Our analysis highlights the great heterogeneity in the effectiveness of large‐scale ERPs for vegetation restoration across a broad regional scale. Large‐scale ERPs should be implemented in a coordinated manner and be tailored to local conditions.