Evolution of rates, patterns, and driving forces of green eco-spaces in a subtropical hilly region

Baojing Wei; Wei Zou; Xijun Hu; Yezi Wang; Cunyou Chen; Jin Tang; Peng Kang; Haiqiang Gao; Jia Tang; Zhenzhen Pan

doi:10.1016/j.scitotenv.2024.172093

Evolution of rates, patterns, and driving forces of green eco-spaces in a subtropical hilly region

Sci Total Environ. 2024 May 20:926:172093. doi: 10.1016/j.scitotenv.2024.172093. Epub 2024 Mar 29.

Authors

Baojing Wei¹, Wei Zou², Xijun Hu³, Yezi Wang², Cunyou Chen², Jin Tang⁴, Peng Kang⁵, Haiqiang Gao⁵, Jia Tang², Zhenzhen Pan⁵

Affiliations

¹ College of Landscape Architecture, Hunan Provincial Big Data Engineering Technology Research Center of Natural Protected Areas Landscape Resources, Institute of Urban and Rural Landscape Ecology, Yuelushan Laboratory Variety Innovation Center, Central South University of Forestry and Technology (CSUFT), Changsha 410004, China; National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, College of Life and Environmental Sciences, CSUFT, Changsha, Hunan 410004, China.
² College of Landscape Architecture, Hunan Provincial Big Data Engineering Technology Research Center of Natural Protected Areas Landscape Resources, Institute of Urban and Rural Landscape Ecology, Yuelushan Laboratory Variety Innovation Center, Central South University of Forestry and Technology (CSUFT), Changsha 410004, China.
³ College of Landscape Architecture, Hunan Provincial Big Data Engineering Technology Research Center of Natural Protected Areas Landscape Resources, Institute of Urban and Rural Landscape Ecology, Yuelushan Laboratory Variety Innovation Center, Central South University of Forestry and Technology (CSUFT), Changsha 410004, China. Electronic address: t20040191@csuft.edu.cn.
⁴ Beijing Accurate Technology Co., Ltd., Beijing 100080, China.
⁵ National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, College of Life and Environmental Sciences, CSUFT, Changsha, Hunan 410004, China.

PMID: 38556019
DOI: 10.1016/j.scitotenv.2024.172093

Abstract

Monitoring ecological resource change in mountainous and hilly areas (MHAs) is vital for theoretical and practical advancements of ecological resource utilization and management in complex ecosystems. The factors driving structural and functional changes in green eco-spaces (GES) in these areas are complex and uncertain, with notable spatial scale effects. However, analyzing the multi-scale driving mechanisms of ecological and socioeconomic factors at a fine spatiotemporal scale presents significant challenges. To address these challenges, we analyzed dynamic changes in GES and eco-socio-economic development in Shanghang County, a typical mountainous region in southern China. We used multiple linear regression and multi-scale geographically weighted regression model to identify key factors driving GES changes and their multi-scale effects at both global and local levels. Over the past two decades, the GES area in the study area has exhibited a consistent pattern of decline, characterized by phases of gradual decline (2000-2005), sharp decline (2005-2009), slow decline (2009-2019). Key global factors driving GES changes included elevation (ELE), slope (SLOPE), population density (PD), distance to settlements (SETTLE), and distance to administrative centers (ADMIN). These factors exhibited significant spatial heterogeneity and multi-scale effects on GES changes. Specifically, SETTLE, PD, SLOPE, and ELE consistently drove GES changes at the local level, while ADMIN only showed significant localized effects during 2005-2009. The synergy between SETTLE and SLOPE had a considerable impact on GES changes, increasing over time, whereas ELE and PD demonstrated a consistent trade-off effect. These findings provide detailed spatiotemporal insights into the driving mechanisms of natural ecological resources, offering crucial guidance for environmental management, land source management, regional economic development, and biodiversity conservation in Shanghang and analogous subtropical hilly regions worldwide.

Keywords: Driving mechanism; Green eco-space; Multi-scale geographically weighted regression; Scale effect; Spatial heterogeneity; Subtropical hilly area.