Abstract
To secure the enduring the long-term growth of ecosystem services, the city of Harbin in northeastern China must prioritize the optimization of its landscape pattern. However, there is a dearth of studies pertaining to the geospatial repercussions of landscape patterns on ecosystem services. This study examined the properties of spatio-temporal evolution of Harbin's landscape patterns from 2000 to 2020 and six essential ecosystem services: food supply, water yield, soil conservation, carbon storage, water purification, and habitat quality. It used the geographical detector (GD) to reveal the effects of landscape pattern changes on ecosystem services and the geographically weighted regression (GWR) model to map ecosystem services' responses to changes in landscape pattern heterogeneity. The results showed that from 2000 to 2020, the landscape types in Harbin tended to become richer, the spatial heterogeneity increased, and the degree of fragmentation decreased significantly. Water yield continued to increase, habitat quality slightly improved, soil conservation and carbon storage initially decreased and then increased, and water purification and food supply first increased and then decreased. Landscape pattern evolution had a substantial impact on ecosystem services. Landscape composition had a greater influence on ecosystem services than did landscape configuration in Harbin City, with the proportion of agricultural land, the proportion of woodland, the largest patch index, and the aggregation index having a greater effect on ecosystem services. A significant challenge in territorial spatial planning is how to develop distinct ecosystem services in a balanced fashion, because in the majority of cases, the effects of landscape patterns on individual services are different or even opposing. To optimize local landscape patterns and develop total ecosystem services in a balanced manner, policymakers can use the study's results, which emphasize the complex response of ecosystem services to changes in landscape patterns, to develop more accurate spatial planning strategies and plans.