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An assessment framework for improving protected areas based on morphological spatial pattern analysis and graph-based indicators

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Abstract Zoning protected areas is essential for ecological protection and environmental management. However, the protected areas generated via bottom-up processes depend highly on the attitudes of local authorities. Moreover, the… Click to show full abstract

Abstract Zoning protected areas is essential for ecological protection and environmental management. However, the protected areas generated via bottom-up processes depend highly on the attitudes of local authorities. Moreover, the performance of protected areas will inevitably be weakened by human activities if there exists an inconsistency between protection and land development. To reveal and solve these problems through top-down approaches, a novel framework for the improvement of protected areas (ERL) is presented in this study. First, the ecological conditions of both the previously-established ERL and land use status quo were assessed through morphological spatial pattern analysis (MSPA) and a set of graph-based indicators (e.g., connectivity indices). Second, the low-quality parts of the ERL were improved based on a comparison with the observed land use condition. The results indicated that the ecologically important areas that were excluded from the previously-established ERL can be effectively identified by the combination of MSPA and graph-based indicators. The percentages of high-quality components moderately increased after the improvement. Specifically, low-level core patches can be upgraded by incorporating the ecologically important pixels that were previously neglected. Moreover, many low-quality small islets can be enhanced to better serve the function of temporary habitats. In summary, these results are expected to provide practical guidance for ecological conservation planning and management. More importantly, our proposed zoning framework can be further generalized to the analysis in many other fast-growing regions.

Keywords: based indicators; spatial pattern; protected areas; graph based; framework; morphological spatial

Journal Title: Ecological Indicators
Year Published: 2021

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