Spatially explicit drivers of habitat degradation in coastal megacities based on MGWR-GCCM --evidence from Fuzhou, China.

Rapid urbanization often intensifies landscape fragmentation and reduces habitat quality in metropolitan areas, necessitating an understanding of their interaction mechanisms. There has been a predominant focus on correlational analyses in existing research examining changes in landscape patterns and habitat quality, while causality between the two has received considerably less attention. Using Multi-scale Geographically Weighted Regression (MGWR) and Geographical Convergent Cross Mapping (GCCM), we elucidated spatially heterogeneous and causal mechanisms linking landscape pattern evolution to habitat quality dynamics in southeast China's coastal Fuzhou metropolitan area. It is demonstrated that: (1) From 2000 to 2022, habitat quality in the study area declined by 5 %, degradation worsened by 24 %, and landscape fragmentation intensified, with clear spatial differences: high fragmentation along the coast and stable quality inland. (2) Most landscape pattern indexes (LSPI) were significantly correlated with the current status of habitat quality, but only the Largest Patch Index (LPI) showed a clear unidirectional causal effect with habitat quality (ρ = 0.38). (3) LPI variation weakly drived habitat degradation (ρ = 0.25), while other indexes correlated with degradation but lack direct causality. (4) Interspersion-Juxtaposition Index (IJI) and Number of Patches (NP) exhibited unidirectional causal effects on changes in habitat quality from 2000 to 2022, with ρ = 0.3 for IJI and ρ = 0.22 for NP, while LPI and other key indexes showed correlations only. It revealed the causal relationships between landscape pattern evolution and habitat quality dynamics, and identified key drivers responsible for habitat degradation, which would provide operational guidance for ecological restoration in rapidly developing metropolitan areas.