Analysis of Spatial and Temporal Variations in Ecosystem Service Functions and Drivers in Anxi County Based on the InVEST Model

Wen Li, Jianwei Geng, Jingling Bao, Wenxiong Lin, Zeyan Wu and Shuisheng Fan ()
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Wen Li: Anxi College of Tea Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Jianwei Geng: College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Jingling Bao: Multifunctional Agricultural Application Research Institute, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Wenxiong Lin: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Zeyan Wu: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Shuisheng Fan: Multifunctional Agricultural Application Research Institute, Fujian Agriculture and Forestry University, Fuzhou 350002, China

Sustainability, 2023, vol. 15, issue 13, 1-16

Abstract: Background: Exploring the spatial and temporal evolution patterns of regional ecosystem service functions and their main drivers can provide effective support for formulating regional ecological conservation policies and coordinating sustainable economic–ecological development. Methods: This study quantifies the service functions of the water production, soil conservation, carbon storage, habitat quality, and net primary productivity (NPP) in the study area based on the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and the Carnegie–Ames–Stanford Approach (CASA) model and constructs a comprehensive index for ecosystem services (CES) based on the analytic hierarchy process (AHP) to reflect the total supply of various ecosystem services spatially and explore the main driving mechanisms of their spatial variation. The main driving mechanisms of the spatial variation were investigated. Results: (1) Water production in the study area from 2010 to 2020 showed a trend of increasing before decreasing, soil retention showed a trend of continuously decreasing, carbon storage and biotope quality showed a trend of decreasing before increasing, and the NPP showed a trend of continuously increasing. (2) The mean CES of the study area from 2010 to 2020 (0.5398, 0.5763, 0.5456) showed a trend of increasing before decreasing. The improvement areas were mainly concentrated in the western, southwestern, and northeastern parts of the study area, and the degraded areas were mainly distributed in the southeast and northwest. (3) The fit of the geographically weighted regression (GWR) was higher than that of the ordinary least squares (OLS) in all the periods, and the main driving factors affecting the spatial variation in the CES were the NDVI and tea plantation area (T-Area). Conclusion: This study constructed the CES model, explored the regional CES spatiotemporal evolution pattern and its main driving mechanism, and provided a reference basis for promoting the high-quality development of specialized tea regions.

Keywords: ecosystem service functions; InVEST model; CASA model; driving forces (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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