Strength of association between vegetation greenness and its drivers across China between 1982 and 2015: Regional differences and temporal variations

• Main Authors: Jiao, K. (Author), Li, D. (Author), Li, S. (Author), Liang, Z. (Author), Wang, H. (Author), Wei, F. (Author), Yan, S. (Author)
• Format: Article
• Language: English
• Published: Elsevier B.V. 2021
• Subjects: Anthropogenic factors; China; climate change; Climate change; Dominant factor; Geodetector method; GeoDetector method; greenspace; heterogeneity; human activity; Hydrothermal conditions; land cover; Land use; NDVI; Normalized difference vegetation index; Population statistics; Qinghai-Xizang Plateau; Quantitative attribution; Regional difference; Regional differences; spatiotemporal analysis; Strength of association; Sustainable development; Temporal dynamic; Temporal dynamics; temporal variation; Vegetation; Vegetation greenness; Wind; wind velocity
• Online Access: View Fulltext in Publisher

 Analysis focused on sub-regional differentiation of vegetation greenness and their dominant drivers are needed to properly develop targeted strategies for sustainable management. In this study, we took China as a case study area, and analyzed the spatiotemporal heterogeneity of vegetation greenness and its strength of association with both environmental (topographical factors and hydrothermal conditions) and anthropogenic factors (land use type and population density) across six eco-geographic regions during 1982–2015. The whole period was divided into two periods by the turning point of 1998, after which China has implemented numerous forest protection projects. The attribution results based on the Geodetector method show the followings: (1) In China, precipitation is the dominant factor in landscape variation of Normalized Difference Vegetation Index (NDVI) with a strength of association of 85%. Additionally, precipitation is also the dominant factor in arid and semi-arid regions, including Northern semiarid (NS) region, Northwestern arid (NWA) region and Qinghai-Tibet Plateau (QTP) region. The dominant factors differ across diverse eco-geographic regions; for example, slope dominates in sub-tropical/tropical humid (STH) and middle temperate humid/sub-humid (MTH) regions. (2) Generally, the strength of association between vegetation and temperature decreases across China over the past 34 years, meaning that the limiting effect of temperature on the NDVI is weakened, similarly, the controlling effect of water conditions is also weakened. In contrast, the spatial association between anthropogenic factors and NDVI is enhanced. (3) The temporal dynamics of strength of association between factors and the NDVI differ in diverse periods and regions; for example, the strength of association between wind speed and NDVI decreased during 1982–1998, but increased during 1999–2015 in temperate humid/sub-humid (WTH) region; however, decreasing trends were revealed in the QTP region in both periods. Our study highlights that variation of NDVI is mainly attributed to climate change and land cover change. Generally, the limiting impact of hydrothermal conditions on NDVI weakens, and the controlling effect of human activity increases over time. © 2021 The Authors