Quantifying impacts of climate and land use changes on ecosystem services from statistic perspective

Quantitatively analyzing the impacts of climate and land use changes on ecosystem services has drawn increasing attention over the past decade. However, the assessment approach in the existing studies highly depended on scenarios and modeling, which is unable to distinguish the influences of different land use types and different climate characteristics and to quantify the absolute influence levels of multiple driving factors. Here, we adopted the partial correlation analysis for quantifying relationships between ecosystem services and the seemingly unrelated regression model for assessing impacts of climate and land use changes on ecosystem services. Taking Hainan Tibetan Autonomous Prefecture of Qinghai Province in China from 2000 to 2019 as a case study, we focused on four ecosystem services including material provisioning, climate regulation, water regulation, and soil protection and five driving factors including precipitation, temperature, cropland area, forest area, and grassland area. The results identified the positively dominant driving factor of precipitation on material provisioning, water regulation, and soil protection, and the negatively dominant driving factor of cropland area on material provisioning, climate regulation, and water regulation. The synergy relationships were found between material provisioning and climate regulation, between climate regulation and water regulation, and between water regulation and soil protection, while the trade-off relationships were found between material provisioning and water regulation, and between material provisioning and soil protection. These findings support local policymaking, suggesting that management of climate-related risks and land use plan with a restriction on cropland expansion are expected.