Multi-Scenario Simulation of the Production-Living-Ecological Spaces in Sichuan Province Based on the PLUS Model and Assessment of Its Ecological and Environmental Effects

Research investigates the transformations in production–living–ecological spaces (PLES) across diverse scenarios and their ecological effects, with the aim of offering advice for environmental preservation and long-term growth in Sichuan Province. Utilizing the PLUS model, we simulated the PLES configuration in Sichuan Province for the year 2030 and subsequently evaluated its ecological impacts using an ecological effect assessment model. The findings reveal that: (1) population and GDP are key drivers of the expansion of Industrial-Production Spaces (IMPS), Urban-Living Spaces (ULS), and Rural-Living Spaces (RLS), whereas altitude has a crucial influence on shaping the expansion of Agricultural-Production Spaces (APS), Forest-Ecological Spaces (FES), Grassland-Ecological Spaces (GES), Water-Ecological Spaces (WES), and Other-Ecological Spaces (OES); (2) significant changes in PLES are observed in Sichuan Province by 2030 across four scenarios, with notable distinctions between the production priority scenario and the other three; (3) variations in ecological quality exist among the four scenarios concerning PLES; (4) the reasons behind better or worse ecological conditions differ across scenarios. The research demonstrates that the PLUS model can effectively simulate PLES in Sichuan Province under multiple scenarios for 2030, offering various potential development pathways and their corresponding ecological effects, thereby aiding in the selection of optimal development pathways.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2024-11-26
DOI
https://doi.org/10.3390/su162310322
Citations
2
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.57
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Multi-Scenario Simulation of the Production-Living-Ecological Spaces in Sichuan Province Based on the PLUS Model and Assessment of Its Ecological and Environmental Effects

Kun Zeng, Yu Fu, Julin Li, Youhan Wang et al.
2 citations
Sustainability
Land Use and Ecosystem Services
0.57
article

Multi-Scenario Simulation of the Production-Living-Ecological Spaces in Sichuan Province Based on the PLUS Model and Assessment of Its Ecological and Environmental Effects

Kun Zeng, Yu Fu, Julin Li, Youhan Wang, Liangsong Wang, Qian Li
article en
2 citations

Abstract

Research investigates the transformations in production–living–ecological spaces (PLES) across diverse scenarios and their ecological effects, with the aim of offering advice for environmental preservation and long-term growth in Sichuan Province. Utilizing the PLUS model, we simulated the PLES configuration in Sichuan Province for the year 2030 and subsequently evaluated its ecological impacts using an ecological effect assessment model. The findings reveal that: (1) population and GDP are key drivers of the expansion of Industrial-Production Spaces (IMPS), Urban-Living Spaces (ULS), and Rural-Living Spaces (RLS), whereas altitude has a crucial influence on shaping the expansion of Agricultural-Production Spaces (APS), Forest-Ecological Spaces (FES), Grassland-Ecological Spaces (GES), Water-Ecological Spaces (WES), and Other-Ecological Spaces (OES); (2) significant changes in PLES are observed in Sichuan Province by 2030 across four scenarios, with notable distinctions between the production priority scenario and the other three; (3) variations in ecological quality exist among the four scenarios concerning PLES; (4) the reasons behind better or worse ecological conditions differ across scenarios. The research demonstrates that the PLUS model can effectively simulate PLES in Sichuan Province under multiple scenarios for 2030, offering various potential development pathways and their corresponding ecological effects, thereby aiding in the selection of optimal development pathways.

SustainabilityVol. 16(23)
China West Normal University (CN), Guilin University of Technology (CN)
Openalex Percentile: Top 32%
Land Use and Ecosystem Services
0.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.