Spatiotemporal changes of ecosystem services value by incorporating planning policies: A case of the Pearl River Delta, China

Chengjing Chen and Yihua Liu

Ecological Modelling, 2021, vol. 461, issue C

Abstract: Land use and land cover (LULC) changes significantly affect regional ecosystem services value (ESV). Exploring the changes of ESV is helpful for LULC structure adjustment and space optimization. This study proposed a methodological framework of ESV prediction for rapidly urbanization regions. In this framework, the ESV equivalent, Markov Chain, System Dynamic, Future Land Use Simulation model were coupled, and the drivers reflecting planning policies were integrated. The framework was applied to the Pearl River Delta (PRD). We found that the ESV of PRD would decrease marginally in five scenarios, exhibiting an inverted U-shaped of increasing northward along the Pearl River Estuary, and there would be a noteworthy value-loss area at the junction of Foshan–Zhongshan. Under the scenarios of high-speed rail and innovation platform planning, the LULC patterns could better balance the relationship of economic development and ESV reduction. And the agglomeration effects of ESV would be strengthened simultaneously, which is more conducive for the ecological security pattern construction. Future development of the region could refer to the LULC patterns of these two scenarios, but attention must be paid to the low-values cluster in the southwest of Huizhou, northwest and east of Guangzhou. It has been proved that the established framework is effective at the scale of urban agglomeration, and the empirical findings provide valuable insight for spatial and ecological planning in highly urbanized areas in developing countries.

Keywords: Land use simulation; Ecosystem service value; High-speed rail planning; Innovation platform; Pearl river delta (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:461:y:2021:i:c:s0304380021003252

DOI: 10.1016/j.ecolmodel.2021.109777

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