Landscape ecological risk projection based on the PLUS model under the localized shared socioeconomic pathways in the Fujian Delta region. (March 2022)

• Record Type: Journal Article
• Authors: Zhang, Shihe; Zhong, Quanlin; Cheng, Dongliang; Xu, Chaobin; Chang, Yunni; Lin, Yuying; Li, Baoyin
• Is Part Of: Ecological indicators. Volume 136(2022)
• Publication Date: 2022-03
• Subjects: Landscape ecological risk -- PLUS model -- Localized shared socioeconomic pathways -- Muti-scenario projection -- Fujian Delta region; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2022.108642
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Integration of SSPs scenarios in PLUS model was employed to project landscape ecological risk. Localized SSP1 was projected to have the minimal risk, while the largest in SSP4. The conversion of cropland to urban land was the key factor to increased risk. Abstract: Social-economic development and urbanization greatly modify landscape patterns and their associated ecological processes at regional scales, resulting in serious landscape ecological risk (LER). Effectively evaluating the LER is the basis for sustainable land use and development of regions. Because of the uncertainties in future socioeconomic development, precisely projecting future LER distribution is still challenging. To overcome this weakness, by using the Fujian Delta region as a case study, we employed patch-generating land use simulation (PLUS) model coupled with multiple linear regression and a Markov chain model to project the landscape patterns in 2050. The Shared Socioeconomic Pathways (SSPs) proposed by the Intergovernmental Panel on Climate Change (IPCC) were selected as the scenario framework. Thus, the spatiotemporal characteristics of the landscape pattern changes and LER from 2000 to 2020 and the projections for 2050 under different localized SSPs scenarios were explored. The results show that the cropland and water areas changed remarkably during 2000–2020. The PLUS model based on the couple of multiple linear regression and Markov chain model has higher prediction accuracy (FoM = 0.244) than that without the multiple linear regression (FoM = 0.146). The simulation results show that the urban land continued to expand westward and northward in 2050. Large amounts of cropland will be transformed into urban land in the eastern part. The conversion area is the largest under the SSP2 scenario, and the smallest area occurs under the SSP4 scenario. From 2000 to 2020, the LER exhibited the characteristics of an east–west polarized spatial distribution, and the LER gradually increased. The localized SSP4 scenario is projected to have the largest LER, and the smallest LER occurs under the SSP1 scenario. The conversions from cropland to urban land will lead to the most significant increases in LER, followed by the conversion of grassland to urban land.