Spatiotemporal Changes in Ecosystem Services Value and Its Driving Factors in the Karst Region of China

Liu Yang and Hongzan Jiao
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Liu Yang: College of Architecture and Urban Planning, Guizhou University, Guiyang 550025, China
Hongzan Jiao: Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China

Sustainability, 2022, vol. 14, issue 11, 1-21

Abstract: Over the last few decades, most regional ecosystem services (ESs) have significantly deteriorated, primarily driven by an increase in human dominance over the natural environment. Creating an assessment framework of ESs and identifying its driving factors at the regional scale is challenging for researchers, administrators, and policy-makers. In this study, we attempt to quantify the economic value of ESs (ESV) in Guizhou Province from 2000 to 2018, one of the most prominent areas of karst landforms in China. We identified the major factors affecting ESs using the geographical detector (GD) model. Then, we conducted a multiscale geographically weighted regression (MGWR) analysis to examine the spatial differentiation of the causal effects of both natural and anthropogenic factors on ESs. Our results demonstrate the following: (1) the total ESV of Guizhou Province was approximately USD 81,764.32 million in 2000, USD 82,411.06 million in 2010, and USD 82,065.31 million in 2018, and the increase of USD 300.99 million from 2000 to 2018 was the result of the remarkable conversion from cultivated land to forestland; (2) significantly considerable differentiation existed in the spatial distribution of ESV at the county level, with a higher value in the eastern region and a lower value in the western region; (3) among the driving factors, population density had a more significant effect on the spatial differentiation of ESV than did natural factors; and (4) agricultural output value was the dominant factor influencing the ESV during the study period, with a significantly positive correlation, whereas per capita GDP and population density had significantly negative impacts on ESV, according to the effective performance of the MGWR model that evaluated the spatial heterogeneity in geospatial relationships between the driving factors of ESV. Our findings can provide notable guidance to land administrators and policy-makers for effective land resource conservation and management plans, thereby improving regional sustainability.

Keywords: ecosystem services value; driving factors; geographical detector model; multiscale geographically weighted regression; karst areas (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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