Priority planning area identification of Xiaoxing’anling National Park based on multi-dimensional comprehensive evaluation

Objective  Addressing the issues of an unsystematic evaluation system and the challenges in quantifying ecological significance and management feasibility within National Park spatial planning, this study takes the candidate region of the Xiaoxing’anling National Park as a case study to construct a multi-dimensional comprehensive evaluation framework and identify priority planning areas. The objective is to advance the systematization of National Park spatial planning and offer insights for the establishment of China’s national park system.

Method By constructing a three-dimensional evaluation system encompassing national representativeness, ecological importance, and management feasibility, this study integrated GIS, MaxEnt, Fragstats, CASA, and InVEST models to conduct multi-level indicator evaluation and spatial analysis. The combined weighting method of AHP and entropy weight was adopted to determine indicator weights. As a result, priority planning areas were identified in the Xiaoxing’anling study area, which featured extensive suitable habitats for representative species, prominent landscape representativeness, high ecological integrity and authenticity, as well as considerable management feasibility.

Result (1) The weights of the criterion layer ranked as follows: national representativeness (0.434) > ecological importance (0.316) > management feasibility (0.250). (2) In terms of national representativeness, suitable habitats for representative species in the study area were mainly concentrated in the south-central part, coinciding with the distribution of high-level landscapes. (3) In terms of ecological importance, the ecological pattern–process–services generally exhibited a spatial differentiation pattern of high values in the central region and low values in the peripheral areas, which was largely consistent with the authenticity assessment results. (4) In terms of management feasibility, the study area featured low population density, and high concentration of protected areas in the central and southeastern parts, indicating favorable conditions for management and public service infrastructure. (5) The comprehensive evaluation indicated that the optimal planning areas within the candidate region of the Xiaoxing’anling National Park accounted for approximately 14.05% of the total study area, and the suboptimal planning areas accounted for approximately 10.88%. The priority planning areas were mainly distributed in Yichun City and the southern part of Xunke County, Heihe City.

Conclusion National representativeness played a dominant role in the identification of priority planning areas in the Xiaoxing’anling National Park, and the priority planning areas exhibited a significant spatial clustering pattern. The multi-dimensional comprehensive evaluation framework constructed in this study provides a quantitative basis and technical support for the scientific identification and spatial optimization of the candidate region of the Xiaoxing’anling National Park, and offers valuable reference for the planning and management of other national park candidate regions.