Evolution of habitat quality and multi-scenario simulation in the Giant Panda National Park

Abstract

Following the establishment of China's first national parks in October 2021, the national park system has evolved as part of a broader global commitment to ecological conservation. The Giant Panda National Park (GPNP), as a flagship park, faces pressing challenges related to biodiversity protection and land use conflicts. This study integrates the InVEST and PLUS models to assess spatiotemporal changes in habitat quality (HQ) from 2000 to 2020 and simulate future HQ trends under three land-use scenarios—natural development, ecological protection, and cultivated land protection—for the year 2030. Land use data from 2000, 2010, and 2020 were used to quantify HQ changes, and four landscape pattern metrics (Patch Density, LPI, Cohesion Index, and LSI) were incorporated to analyze spatial ecological processes. Results show that: (1) Forestland expanded while grassland declined over the 20-year period, with a concurrent increase in construction and unused land. (2) HQ exhibited a shift toward lower-quality zones, particularly in the Minshan and Qionglai–Daxiangling regions. (3) Predicted HQ indices in 2030 under the three scenarios are 0.5305 (NDS), 0.5317 (EPS), and 0.5297 (CLPS), with the ecological protection scenario yielding the most improvement due to increased vegetation cover. (4) Landscape metrics revealed increased fragmentation, edge complexity, and reduced connectivity of forest patches, suggesting structural habitat degradation despite forest area growth (5) Land use change and natural factors (e.g., precipitation, elevation). were identified as dominant drivers of HQ variation. This study highlights the importance of combining HQ modeling with spatial landscape analysis to better capture habitat dynamics. The findings provide a scientific basis for habitat management and policy formulation in the context of national park conservation.