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Updated: Aug 29, 2026

Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Published on: July 4, 2007
Integrating ecological benefits and expansion probability into the re-naturalization spatial selection framework: A
Chengji Shu1, Baolong Han1, Xiaobiao Zhang1
1State Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China.
Abstract:
The coupled effects of socio-economic and natural complex factors, both in time and space, collectively shape diverse ecosystem patterns, with different ecosystems exhibiting differentiated expansion probabilities in space. However, existing spatial selection frameworks for ecological restoration give limited consideration to this. Taking Beijing as an example, this study integrated ecosystem services value (ESV) assessment and land use expansion probability simulation to propose a framework for determining re-naturalization pathways aimed at enhancing natural benefits, intended to guide spatial selection in ecological restoration practices. The results showed that, over the past 20 years, the expansion of construction land has primarily encroached upon cropland. At the same time, historical ecological restoration projects have contributed to the recovery of forest, shrub, and wetland areas by 2.70%, 73.86%, and 9.9%, respectively. Terrain factors (such as DEM and slope) significantly influence the spatial expansion probabilities of various ecosystems. The overall ESV of the city has decreased by 2.84% over the past 20 years, with wetlands exhibiting the highest average ESV of 83.47 CNY/m2. Furthermore, the ESV supply capacity of shrubland, grassland, and wetlands has significantly increased, while the ESV supply capacity of forests and construction land has declined. Based on the principle of enhancing average ESV and expansion probabilities, this study identified 18 re-naturalization pathways with significant spatial differences and highlights the spatially extreme importance regions for each pathway. This framework provided spatial decision support for ecological restoration that combines the ecosystem services enhancement with socio-economic-natural coupling mechanisms.
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