Optimizing the ecological source area identification method and building ecological corridor using a genetic algorithm: A case study in Weihe River Basin, NW China

• Published in: Ecological informatics Vol. 80; p. 102519
• Main Authors: Wu, Xueting, Pan, Jinghu, Zhu, Xiuwei
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2024
• Subjects: Ecological corridors; Ecological security; Ecological source areas; Genetic algorithm; Graph theory method; Graph theory method; Ecological security; Ecological source areas; Genetic algorithm; Ecological corridors
• ISSN: 1574-9541
• DOI: 10.1016/j.ecoinf.2024.102519

The extraction of ecological corridors is influenced by the accuracy of ecological source area identification, which is a crucial component of ecological security construction. The ecological source areas of the Weihe River Basin (WRB) were comprehensively identified by analyzing the supply, demand, and ecological sensitivity of ecosystem services. Different initial populations were set using a genetic algorithm to determine the optimal source areas for the WRB. The minimum cumulative resistance model (MCR) was used to extract the ecological corridors, and then a comparison was made before and after. The results showed that the ecological source areas within the WRB covered approximately 43.362 × 103 km2 in 2020, accounting for 32.38% of the entire area. This included mainly forest, grassland, and a small amount of farmland, of which 89.3% of the ecological source areas were forest. Fifty optimal ecological source areas were obtained using a genetic algorithm, generating 122 ecological corridors with an overall length of 40.245 × 105 km that could disperse the entire WRB. By comparing the ecological source areas before and after optimization, the IIC value of the ecological source areas before optimization was 0.006, the PC value was 0.007, and the FN value was 0.10. The IIC, PC, and FN values of the optimized ecological source area were 0.08, 0.079, and 0.042, respectively. The overall connectivity of the optimal source identified by the genetic algorithm increased by 13.3 times, with a possible connectivity increase of 11.2 times and a 42% reduction in fragmentation. The applicability and reliability in identifying optimal ecological source areas genetic algorithm was high, offering a reliable idea for constructing regional ecological security. [Display omitted] •Genetic algorithm is introduced to identify the optimal ecological source areas.•Ecological source area and corridor before and after optimization were compared.•Fifty optimal ecological source regions were obtained using the genetic algorithm.•Overall connectivity of the optimal ecological source increased by 13.3 times.•The ecological source areas were distributed in high-sensitivity areas.