Abstract

Ecological environmental security in karst areas is an issue of global concern. Identifying the ecological landscape security pattern (ELSP) is key to promoting environmental protection and alleviating the land development and utilization impacts. Ecological sources (ESs) and ecological corridors (ECs) are important bases for constructing an ELSP. We used five influencing factors (land use type, digital elevation model (DEM), rocky desertification degree, normalized difference vegetation index (NDVI) and slope) to obtain the distribution of the importance and sensitivity values of ecosystem services in Guanling County, Guizhou Province. The probability of the connectivity index (PC) was calculated, and the ES was extracted by combining the importance of ecosystem services, ecological sensitivity, and landscape connectivity. According to the topographic and geomorphological characteristics of Guanling County, seven indicators of elevation, slope, landscape type, degree of stone desertification, distance from rivers, distance from settlements, and distance from roads were selected as resistance factors for the outward expansion of the ESs to calculate the comprehensive resistance surface of Guanling County. Based on the gravity model, an interaction matrix between 10 ESs was constructed, and the magnitude of the interaction forces between the source sites was quantitatively evaluated to distinguish the important ECs and general ECs. The study showed that the total length of the ECs in Guanling County was 509.78 km, and the core area of Guanling County was large, accounting for 65.73% of the ecological landscape area. By assessing the importance of ecosystem services, ecological sensitivity, and landscape connectivity, 10 ES and 45 EC were obtained based on ArcGIS10.8, which constituted the landscape security pattern of Guanling County by ESs and ECs. Suggestions were proposed for a planning layout that will benefit the ecological restoration of Guanling County and environmental protection of the karst region according to the study area characteristics.

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