Optimization of landscape pattern in China Luojiang Xiaoxi basin based on landscape ecological risk assessment

• Published in: Ecological indicators Vol. 146; p. 109887
• Main Authors: Li, Shaokun, He, Wenxi, Wang, Lei, Zhang, Zhi, Chen, Xiaoqian, Lei, Tianci, Wang, Shaojun, Wang, Zhuangzhuang
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2023; Elsevier
• Subjects: Landscape ecological risk assessment; Landscape pattern optimization; Luojiang Xiaoxi Basin; Minimum cumulative resistance model; Spatial principal component analysis; Minimum cumulative resistance model; Landscape ecological risk assessment; Spatial principal component analysis; Luojiang Xiaoxi Basin; Landscape pattern optimization
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2023.109887

•10-meter high-precision raster elements are selected as the basic units for landscape ecological risk evaluation in the study area.•20 evaluation factors are selected from the three dimensions of the “natural environment-human society-landscape pattern” to establish the evaluation index system.•The comprehensive optimization scheme of landscape patterns in key areas can best synergize ecological services.•The selection of ecological source sites is based on four landscape pattern indices that indicate landscape connectivity and patch importance (LCP, LLC, PC, DI).•Optimizing landscape ecological units can improve the connectivity and stability of landscape patterns within the study area. Multi-source ecological risks have induced many ecological pollution problems that cannot be ignored and seriously threaten regional ecological security. Constructing and optimizing the landscape pattern is beneficial to improve watershed ecosystem services. In this study, an innovative method is proposed to construct and optimize the landscape pattern, which takes Luojiang-Small Creek watershed as an example. 10-meter high-precision raster elements are selected as the basic unit for landscape ecological risk evaluation, and 20 evaluation factors are selected from three dimensions of “natural environment-human society-landscape pattern” to establish the evaluation index system. The spatial principal component-redundancy analysis (SPCA-RDA) was used to comprehensively evaluate the landscape ecological risk in 2019, and the minimum cumulative resistance model (MCR) and gravity model were used to optimize the landscape pattern of the watershed. The results show (1) Human social and landscape pattern factors have a more significant influence on the integrated ecological risk, while natural factors, except for soil type and vegetation cover, have a weaker influence on the integrated ecological risk. (2) The overall landscape ecological risk is low, and the area of the mild landscape ecological risk zone is 259.89 km2, accounting for 81.68 % of the study area. According to the MCR model and gravity model, forest land with an area larger than 1 km2 and water bodies and grassland with an area larger than 0.01 km2 were identified as ecological source sites. (3) 17 potential ecological corridors were constructed, including 4 road-type corridors, 9 green belt-type corridors and 4 river-type corridors, with a total length of 68.72 km, and 22 potential ecological nodes were identified, including 8 A-type ecological nodes and 14 B-type ecological nodes. A comprehensive three-dimensional spatial ecological network of “ecological nodes-ecological corridors-ecological zones” was constructed, and the optimization effect of the landscape pattern in the study area was evaluated, and it was found that the optimized landscape pattern had significantly improved in terms of connectivity. The results of the study provide ecological protection and planning guidance for future risk prevention and control and landscape pattern optimization of the area with watershed as a unit.