Understanding the spatiotemporal dynamics and driving forces of ecosystem service values (ESVs) is essential for managing complex socioecological systems, particularly in biodiversity-rich mountainous protected areas. This study investigates the evolution and interactions of ESVs in the Qionglai–Daxiangling region (QDR) of China’s Giant Panda National Park (GPNP) from 1990 to 2020. Based on a revised equivalent factor method, we quantified ESV changes and analyzed trade-offs and synergies among provisioning, regulating, supporting, and cultural services. A Random Forest (RF) model integrated with SHapley Additive exPlanations (SHAP) was employed to assess the relative importance and interpretability of climatic, topographic, and socioeconomic drivers. The results show that elevation, wind speed, and sunshine duration are the most influential variables affecting ESVs. Notably, synergistic relationships among ecosystem services have increased over the past three decades, reflecting the impacts of national ecological restoration initiatives such as the Returning Farmland to Forest Program (RFFP). The SHAP-based analysis further revealed the complex, nonlinear contributions of both environmental and anthropogenic factors. This study provides an interpretable modeling framework for diagnosing ESV dynamics in protected mountainous landscapes. The findings offer practical insights for adaptive management and evidence-based policymaking in national parks under changing environmental and socioeconomic conditions. To better capture the anthropogenic influences on ecosystem functionality in mountainous regions, future studies should incorporate fine-scale land use data and broaden the socioeconomic indicator set to include variables such as ecological compensation and conservation enforcement levels.
Chen et al. (Mon,) studied this question.