Spatial heterogeneous relationship between ecosystem services and human disturbances: A case study in Chuandong, China.

Goal 15 of the UN Sustainable Development Goals (SDGs) has highlighted the importance of maintaining a sustainable relation between ecosystem services and human activities. Ecosystem services are heterogeneous across landscapes. However, how human activities, which cause disturbances to ecosystem services, relate to such heterogeneity has not been well studied and thus necessarily constraining our ability to manage ecosystems sustainably. Based on land use/land cover data, this study addressed the research gap by running two inter-related analyses on the datasets of the study area, i.e., Chuandong, China. The first analysis involves identifying distinctive heterogeneous units of ecosystem service values using Getis-Ord Gi⁎. The second analysis involves measuring the impacts of human disturbances on ecosystem service values and their variations over every five years between 1990 and 2015, using linear regression and spatial regression models. The result of the first analysis identified heterogeneous ecosystem service units of hot-spots, cold-spots, and random areas. The hot-spots mainly clustered in relative inaccessibility land at higher terrain gradients in the east of the study area. The cold-spots overlapped extensively with built-up areas and farmland at lower terrain gradients in the west of the study area. Random areas distributed mainly in the middle part of the study area. This heterogeneity also existed temporally. Ecosystem service values in the study area decreased from 1990 to 2000 but reversed the trend after 2000. The result of the second analysis revealed that the impacts of hot-spots, cold-spots, and random areas on the relationship between ecosystem service values and human disturbances vary. Specifically, there was a negatively linear relationship between ecosystem service values and the integrated indicator of human disturbances, which was the strongest in random areas, followed by cold-spots and hot-spots. In addition, spatial spillover effect is explicit in the relationship between ecosystem service values and three specific factors of human disturbances, i.e., terrain index, population, and gross domestic product. They varied significantly between units: the terrain index had a positive externality on ecosystem service values with cold-spots and random areas but negative externality with hot-spots; population imposed a more negative externality on ecosystem service values when in proximity to random areas than cold-spots and hot-spots; the externality between gross domestic product and ecosystem service values exhibited irregular inverse 'U' shape, which was below the 'X-axis' in cold-spots but throughout the 'X-axis' in hot-spots and random areas. The findings of this study have potential policy implications in improving ecosystem sustainability through harmonizing the environment and human activities.