Multi-temporal Ecological Network Dataset and Resilience Simulation Code for the Three Gorges Reservoir Area

This dataset presents a comprehensive spatiotemporal analysis of ecological network resilience in the Three Gorges Reservoir Area (TGRA) at three key time points: 2001 (pre-dam operation), 2012 (after initial impoundment), and 2023 (reflecting long-term operational adjustments and ecological restoration efforts). The data content includes fundamental geographic information layers (TGRA boundary, Digital Elevation Model (DEM)), and derived ecological network components (ecological source areas, ecological corridors, and ecological stepping stones). Furthermore, the dataset provides a quantitative assessment of ecological network resilience using four core metrics: Average Clustering Coefficient (ACC), Average Number of Independent Paths (ANIP), Network Efficiency, and Relative Size of the Largest Connected Component (RS-LCC). To further enhance the dataset's utility, MATLAB code for simulating various disturbance scenarios (such as random attacks and targeted attacks) is included to evaluate the network's dynamic robustness.

This analysis is expected to reveal significant temporal changes in the ecological network structure and resilience of the Three Gorges Reservoir Area. Preliminary results may indicate a decline in network resilience after dam impoundment, reflecting the profound impact of this large-scale hydraulic project on the ecological environment. The 2023 data, however, may show signs of stabilization or partial recovery in certain aspects of network resilience, which could be attributed to ongoing ecological restoration initiatives and revised operational policies. This dataset is of significant value for understanding the long-term ecological consequences of large infrastructure development, guiding future conservation strategies, and providing an empirical basis for evaluating the effectiveness of environmental management policies in highly modified riverine landscapes. It serves as a valuable resource for researchers in landscape ecology, conservation biology, environmental management, and complex network theory, facilitating further analysis, modeling, and comparative studies.