Region-specific meteorological patterns in valuing ecosystem regulation services for ecosystem management: A Beijing case study

Traditional ecological conditions indicators struggle to meet the demands of diverse ecosystem management. Ecosystem regulation services value (RSV) quantifies the monetized overall ecosystem benefits and conditions, having more intuitive and broader application prospects. However, the spatiotemporal fluctuations of actual meteorological conditions (AMC) significantly impact the objectivity and accuracy of RSV in characterizing ecosystem conditions. Sliding average meteorological conditions (SMC) often reduce the kurtosis of meteorological data, making them unsuitable for assessing ecosystem services to extreme meteorological conditions. This study used Beijing as a case study to propose the concept of comparable meteorological conditions (CMC) and determination method, then evaluated RSV from 2000 to 2020 under AMC, SMC, and CMC. Furthermore, this study compared RSV under different meteorological conditions with traditional ecological quantification indicator, Ecosystem Quality Index (EQI), and conducted spatiotemporal reliability verification using linear regression model (LR), geographically weighted regression model (GWR) and trend scoring methods. The results showed that the CMC for temperature, precipitation, evaporation, wind speed, and air humidity were 2004, 2020, 1994, 2009, and 2007, respectively. The spatial-temporal variation of CMC-based RSV exhibited smaller magnitude, better aligning with the stability of ecosystem. Spatial correlation between CMC-based RSV and EQI was significantly higher than that of AMC (LR: 1.51% to 5.44%; GWR: 0.90% to 1.39%) and SMC (LR: 1.64% to 5.40%; GWR: 0.97% to 1.34%). Temporal trend score between CMC-based RSV and EQI is 6.18% and 6.02% higher than under AMC and SMC, respectively. These results indicated that CMC provides a more scientific data basis for management-oriented RSV assessments.