Abstract
Numerous disorderly expansions of impervious surfaces have resulted from the ongoing urbanization process, eroding the ecological security pattern and exacerbating ecological risks, subsequently leading to a progressive deterioration in its integrity. The tension between the expansion of ecological space and urban spatial expansion is becoming increasingly acute. Exploring the connection between ecological risks in urban landscapes is important for effectively managing regional ecological risks and optimizing patterns of regional ecological security. However, previous studies focus on selecting ecological sources in an ecological network and ignore how ecological resilience is impacted by factors such as species diversity, ecological structure complexity, etc. Based on remote sensing images of Liaoning Province in 2000, 2010, and 2020, the study used the landscape core index as the main indicator of ecological risk assessment, constructed a landscape ecological risk assessment model, and analyzed the spatiotemporal evolution of landscape ecological risk over the past 20 years. The impact of landscape ecological risk on ecological resistance was further explored, and the landscape ecological risk results in 2020 were used as one of the resistance factors to construct a multi-indicator comprehensive resistance surface. After identifying important ecological sources, an ecological network based on the minimum cumulative resistance model (MCR) was constructed, the optimal path connecting important ecological source areas was determined, and the distribution pattern characteristics of the internal ecological network in Liaoning Province were revealed. The findings indicate a general shift in ecological risks from high to low, following a distribution pattern of “high in the east and low in the west”. Additionally, the study identified 8 ecological sources and established 28 ecological corridors, spanning a total length of roughly 8160 km. This study aims to furnish a scientific foundation for developing an ecological security pattern network and optimizing the landscape pattern within Liaoning Province.
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