Habitat Quality Evolution and Multi-Scenario Simulation Based on Land Use Change in the Jialing River Basin

Xiong Duan (), Bin Chen (), Tianxiang Zhang, Yuqi Guan and Kun Zeng
Additional contact information
Xiong Duan: Sichuan Provincial Engineering Laboratory of Monitoring and Control for Soil Erosion in Dry Valley, School of Geographical Sciences, China West Normal University, Nanchong 637009, China
Bin Chen: School of Geography and Environment, Liaocheng University, Liaochen 252000, China
Tianxiang Zhang: Zhejiang Zhixing Surveying and Mapping Geographic Information Co., Ltd., Hangzhou 311199, China
Yuqi Guan: Sichuan Provincial Engineering Laboratory of Monitoring and Control for Soil Erosion in Dry Valley, School of Geographical Sciences, China West Normal University, Nanchong 637009, China
Kun Zeng: Sichuan Provincial Engineering Laboratory of Monitoring and Control for Soil Erosion in Dry Valley, School of Geographical Sciences, China West Normal University, Nanchong 637009, China

Sustainability, 2024, vol. 16, issue 16, 1-23

Abstract: The Jialing River watershed has seen substantial changes in habitat quality and land use throughout the last 20 years. It is yet unknown, however, how the habitat quality will react to these changes in land use. In this work, multi-scenario simulations for 2030 were carried out using the PLUS and InVEST models, and the land use changes and habitat quality evolution in the Jialing River basin from 2000 to 2020 were evaluated. In this study, the following facts were determined: (1) The study area’s southern region is mainly farmland, whereas the northern part is predominantly forestland. The most significant changes were a decrease of 1.46% in the grassland and an increase of 1.07% in the construction land. (2) The northern area typically has greater habitat quality than the southern region, at habitat quality indices of 0.5401, 0.5338, and 0.5084 for the year 2000, the year 2010, and the year 2020, respectively, demonstrating a pattern of steady decline. (3) Converting farmland to forestland can successfully increase habitat quality, but the conversion of grassland and forestland to farmland is the primary cause of the decline of habitat quality. (4) Global Moran’s indices of −0.7809, −0.7537, and −0.6376 for 2000, 2010, and 2020, respectively, were found in the correlation study between habitat quality and land use intensity, showing a high negative link. The local indicators of spatial association (LISA) maps indicated that the northern region had high land use intensity with low habitat quality, while the southern region had low land use intensity with low habitat quality. (5) The outcomes of the multi-scenario simulations show that, except under the ecological conservation scenario (0.5123) where habitat quality improved, there was a certain degree of deterioration under the business-as-usual (0.4381), farmland conservation (0.4941), and sustainable development (0.4909) scenarios. For future sustainable development, strict control of the encroachment on farmland and forestland is recommended, alongside the adoption of proactive measures to improve habitat quality.

Keywords: Jialing River Basin; habitat quality; land use change; PLUS–InVEST; multi-scenario simulations (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/16/16/6968/pdf (application/pdf)
https://www.mdpi.com/2071-1050/16/16/6968/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:16:y:2024:i:16:p:6968-:d:1456133

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().