Advancing Watershed Sustainability: A Multi-Scenario Approach to Ecological Security Pattern Optimization in the Liaohe River Basin, China
Year: 2026
Type: article
Abstract: During urbanization, human activities have induced significant transformations in land use, leading to a huge imbalance in economic growth and nature development, posing severe threats to ecosystems. How to construct a stable and continuous ecological security pattern (ESP) in vulnerable areas like the Liaohe River Basin in Liaoning section has become a crucial challenge for regional management while facing the constraints of habitat fragmentation and the loss of landscape connectivity on sustainable development. Most research on ESP mainly relies on current situation or single scenario predictions, this study developed a “current assessment-future prediction-pattern optimization” framework. By simulating and comparing four distinct policy-oriented scenarios for 2030—Natural Development (ND), Cropland Protection (CP), Ecological Protection (EP), and Ecosystem-Service-Importance-Based Sustainable Development (ESIS)—this study aims to: (1) reveal the differentiated impacts of various policy orientations on future land use patterns; (2) compare the spatial evolution of ecological sources, resistance surfaces, ecological corridors, and key nodes between 2020 and under each 2030 scenario; and (3) synthesize an optimized ESP. This ESP is designed to balance economic and ecological needs, ultimately providing a scientific basis for watershed management. Furthermore, based on the simulation results, we propose a spatially explicit and adaptive management strategy termed the “one ribbon, two zones” pattern to guide the implementation of the optimized ESP within the basin.
Source: Sustainability
DOI: 10.3390/su18042092
Institutions: Dalian Ocean University, Ministry of Natural Resources
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Award: G7838779747
OpenAlex ID: W7130517799
