Evolution of bird habitat quality driving mechanisms and ecological network weights

• Published in: Global ecology and conservation Vol. 46; p. e02618
• Main Authors: Xie, Jing, Xie, Binggeng, Zhou, Kaichun, Li, Junhan, Xiao, Jianyong, Liu, Changchang, Zhang, Xuemao
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.10.2023; Elsevier
• Subjects: anthropogenic activities; Bird habitat quality; birds; Changsha-Zhuzhou-Xiangtan urban agglomeration; Driving mechanisms; Ecological network; ecological restoration; evolution; habitat fragmentation; habitats; Interaction force; landscapes; metropolitan areas; normalized difference vegetation index; regression analysis; spatial variation; PARA_MN; GWR; Driving mechanisms; Interaction force; CLP; NLD; ELP; CONTAG; DEM; NDVI; Changsha-Zhuzhou-Xiangtan urban agglomeration; POP; MSPA; ENN_MN; dPC; CZXUA; HQb; Bird habitat quality; Ecological network; SHDI; MCR
• ISSN: 2351-9894; 2351-9894
• DOI: 10.1016/j.gecco.2023.e02618

In large urban agglomerations with fragmented landscapes, the relationship between habitat quality driving mechanisms and county ecological network weights has not yet been revealed. This study investigated the metropolitan area of Changsha-Zhuzhou-Xiangtan urban agglomeration (CZXUA), focusing on birds, and modified the habitat quality model with Normalised Difference Vegetation Index (NDVI), to explore the contribution of factors to the spatial heterogeneity of bird habitat quality (HQb) and the driving force at global and local scales. Ecological networks were identified based on appropriate distance thresholds, and county weight was calculated based on the gravity model. The results showed that: (1) at the global scale, the contribution of human disturbance to the spatial heterogeneity of HQb continued to increase, up to 73 %. All factors showed non-linear driving effects. The global fit of landscape pattern factors was low, suggesting local linear regression relationships. Mosaic filling-induced habitat quality improvement depends on the trade-offs between the patch spacing and the penetration degree of different patches. (2) Ecological network showed source degradation, corridor fragmentation, and out-migration over time. The interaction between Xiangtan County and Lukou District decreased from 1,357,145 to 896,077, while the interaction between Xiangtan and Changsha County increased slightly from 99,035 to 107,641. Landscape fragmentation was the direct cause of the decrease in weight, while source geocentric transfer was the indirect cause. (3) Habitat quality can be an explicit indicator, while ecological network weight was a constantly fluctuating implicit indicator. A county may acquire ecological sources from more degraded neighbouring counties and become a new ecological network hub. It is important to evaluate the changes in the weighting of the counties at a large scale, so as to determine their vulnerability as habitat spaces and the likelihood of being threatened by the factors affecting them, and to avoid neglecting the ecological network benefits due to the fragmentation of county habitats. These findings could provide suggestions for ecological restoration and connectivity strategies in urban agglomerations. [Display omitted] •Habitats of birds were used in combination with NDVI to modify Habitat Quality model.•Drivers had nonlinear effects on bird habitat quality at the global scale.•Ecological networks based on appropriate distance thresholds were identified.•Bird habitat quality and fluctuating ecological network weights may be trade-offs.