Ecological Effects of PLES Transformation Along Topographic Gradients in the Yellow River Basin

As a crucial ecological security barrier in China, the Yellow River Basin faces pressing challenges in balancing human activities and environmental sustainability. This study introduces the production–living–ecological space (PLES) framework to analyze land transformation and its ecological consequences from 1995 to 2024. Using land use transfer matrices, landscape metrics, the InVEST model, and geographical detector analysis, we quantified the spatiotemporal evolution of PLES and its impacts on landscape patterns and habitat quality across topographic gradients. Results show that living space consistently expanded, primarily at the expense of production and ecological spaces, leading to increased landscape fragmentation and habitat degradation. These adverse effects were most severe in low-topographic areas, revealing a clear topographic gradient effect. Both natural and anthropogenic drivers jointly shaped the spatial heterogeneity of ecological impacts. The key contribution of this study lies in systematically coupling PLES transitions with topographic gradients, offering a spatially explicit perspective for understanding regional human–environment interactions. Our findings provide a scientific basis for designing differentiated ecological restoration and spatial governance strategies in the Yellow River Basin, supporting its sustainable development under China’s national strategic framework.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2025-12-13
DOI
https://doi.org/10.3390/su172411172
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ecological Effects of PLES Transformation Along Topographic Gradients in the Yellow River Basin

Song Wei-dong, Xinxin Fang
Sustainability
Land Use and Ecosystem Services
article

Ecological Effects of PLES Transformation Along Topographic Gradients in the Yellow River Basin

Song Wei-dong, Xinxin Fang
article en

Abstract

As a crucial ecological security barrier in China, the Yellow River Basin faces pressing challenges in balancing human activities and environmental sustainability. This study introduces the production–living–ecological space (PLES) framework to analyze land transformation and its ecological consequences from 1995 to 2024. Using land use transfer matrices, landscape metrics, the InVEST model, and geographical detector analysis, we quantified the spatiotemporal evolution of PLES and its impacts on landscape patterns and habitat quality across topographic gradients. Results show that living space consistently expanded, primarily at the expense of production and ecological spaces, leading to increased landscape fragmentation and habitat degradation. These adverse effects were most severe in low-topographic areas, revealing a clear topographic gradient effect. Both natural and anthropogenic drivers jointly shaped the spatial heterogeneity of ecological impacts. The key contribution of this study lies in systematically coupling PLES transitions with topographic gradients, offering a spatially explicit perspective for understanding regional human–environment interactions. Our findings provide a scientific basis for designing differentiated ecological restoration and spatial governance strategies in the Yellow River Basin, supporting its sustainable development under China’s national strategic framework.

SustainabilityVol. 17(24)
Liaoning Technical University (CN)
Openalex Percentile: Top 62%
Land Use and Ecosystem Services
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.