From methodological divides to planning priorities: a goal-scale framework for selecting connectivity methods in ecological network planning

Connectivity assessment is central to ecological network construction, yet different methods generate distinct forms of planning evidence, and guidance for selecting them according to the planning question remains limited. To address this gap, this study develops a planning-oriented goal–scale framework for connectivity method selection and illustrates its planning relevance through a comparative analysis in Shenzhen, China. A shared ecological source system was derived using morphological spatial pattern analysis (MSPA), and two analytical pathways were compared: minimum cumulative resistance (MCR)-based cost connectivity and graph-theoretic connectivity represented by the integral index of connectivity (IIC) and probability of connectivity (PC). The cost-connectivity pathway identified accessible ecological service patches and low-resistance corridors, mainly in eastern and southeastern mountain areas and reservoir-associated ecological spaces. IIC/PC emphasized mountain-reservoir backbones, central structural patches, and bridge-like links supporting network coherence. Coupling coordination analysis showed substantial divergence: antagonistic areas accounted for 60.82% of patches and 44.73% of corridors, while high-level coupling coordination areas accounted for 5.22% and 8.04%, respectively. High-coordination areas were concentrated in ecological anchors where cost accessibility and structural importance coincided. Geographical detector analysis showed that patch-level differentiation was mainly associated with land class, distance to the urban core, road density, and point-of-interest (POI) density, whereas corridor-level differentiation was weakly associated with individual urban-context variables. The findings indicate that MCR and IIC/PC provide complementary but non-interchangeable evidence: graph-theoretic indices foreground network structural prioritization, whereas cost connectivity provides spatially explicit evidence for corridor routing and implementation-oriented intervention.