Integrating MaxEnt and circuit theory to construct an ecological network framework for invasive plant management in...

With the continuous development of economic and trade globalization, the economic and ecological losses caused by invasive alien plants have become increasingly severe. Through ecological network analysis, clarifying the diffusion patterns and driving mechanisms of invasive plants can shift the governance strategy from passive eradication to proactive spatial intervention, thereby improving the efficiency of invasive plant control. This study takes the built-up area of Guiyang City as the research area. Based on conducted field botanical surveys data, the maximum entropy model(MaxEnt)was applied to predict the suitable habitats of invasive plants under current (1970-2000) and future (2050) climate scenarios. On this basis, the core diffusion source areas of invasive plants were identified. The Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) were combined to construct a comprehensive resistance surface, and the diffusion network of invasive plants was generated via circuit theory. The results show that: 1. GDP, nighttime light intensity, and NDVI are the key environmental factors determining the distribution of invasive plants in Guiyang City. Under the current climate pattern, invasive plants are mainly distributed in the central part of the built-up area with a fragmented distribution pattern. In future climate scenarios, the area of suitable habitats for invasive plants will expand significantly, presenting a continuous and carpet-like distribution pattern. 2. A total of 51 core diffusion source areas were identified in the study area, with a total area of 11.49 km², which are mainly distributed in an annular pattern around the central part of the built-up area. In addition, 128 diffusion corridors, 41 pitch point, and 30 barriers point were extracted in the study. This study constructs a risk identification framework for invasive plant diffusion based on the "source-corridor-node" triad, which provides a spatial decision-making basis for the precise management of invasive plants. It also elevates the thinking of invasive plant prevention and control from the local management of individual species to the construction of overall resilience of urban ecosystems, thereby providing theoretical support and practical paradigms for urban ecological security risk early warning and the optimal allocation of social resources.