Wildlife Corridor Optimization Using Spatial AI

Abstract

Wildlife corridors -- linear or stepping-stone habitat linkages connecting fragmented patches -- are a cornerstone of landscape-scale biodiversity conservation, yet their spatial design typically relies on expert judgement, least-cost path algorithms, or Circuitscape resistance models that fail to integrate multi-species movement data, temporal land-use dynamics, and socioeconomic feasibility simultaneously. This study developed and validated a spatial artificial intelligence framework -- CorridorAI -- integrating graph neural networks (GNNs), multi-objective evolutionary optimisation, and Bayesian habitat suitability modelling to design wildlife corridors that are simultaneously ecologically effective, land-use feasible, and cost-efficient. CorridorAI was applied to the fragmented Central European broadleaf forest landscape spanning Austria, Germany, and Switzerland (total area: 284,000 km2), optimising corridor networks for 24 focal species spanning mammals, birds, reptiles, and amphibians. Corridors designed by CorridorAI increased simulated species connectivity -- quantified as mean commute time between habitat patches in circuit-theoretic models -- by 61.4% relative to existing protected area networks, compared with 38.4% for conventional least-cost path corridors and 24.7% for random habitat additions of equivalent area. CorridorAI corridors also showed 28.4% lower implementation cost (estimated land acquisition and management cost in EUR/km) than least-cost corridors by prioritising agricultural land in social conservation easement schemes over requiring full land purchase. Multi-species corridor networks designed by CorridorAI captured 84.7% of single-species optimal corridors within a network covering 41.8% of the total area required for species-by-species optimal networks -- demonstrating substantial co-benefit efficiencies from integrated multi-species optimisation. The CorridorAI framework and trained models are released as open-source tools for application to other fragmented landscapes globally.