• Wildlife Crossing Structures (WCS) restore connectivity across road networks. • WCS are costly, so prioritizing installation at the most effective sites is key. • A robust multi-species framework was developed to rank WCS locations. • Corridor mapping and prioritization identified suitable road segments for WCS. • This approach supports data-driven decisions to effectively mitigate fragmentation. Habitat fragmentation drives biodiversity loss, and roads intensify it by acting as barriers that disrupt wildlife movement. Wildlife crossing structures (WCS) are commonly used to mitigate these barriers, but their effectiveness depends on appropriate design and careful placement along the road network. Location prioritization methods often rely on animal tracking, road crossing or roadkill data that demand substantial budgets and long monitoring periods, limiting their use at large scales. We developed a multi-species methodology for prioritizing WCS locations at a national scale and demonstrate its use for 20 focal species in Israel across 6,992 km of roads. We modelled habitat suitability to delineate core habitats and calculate resistance surfaces, identifying movement corridors using a least-cost method. We assigned corridor prioritization values based on core habitat characteristics including patch size, habitat quality, and protection status. We then ranked potential crossing locations along 100 m road segments by aggregating multi-species corridor prioritization values, accounting for relative movement cost and road orientation. A sensitivity analysis revealed that the method is robust to most parameters, except for minimal core width. Altogether, we identified 167 high-priority WCS locations but found that all existing wildlife overpasses in Israel do not alight with them. Yet 68.2% of these potential WCS locations intersect with corridors that were mapped based on expert opinion. Our methodology for prioritizing WCS locations across regional-scale road networks, which incorporates multiple focal species and established connectivity analysis tools, may improve decision making for effective road mitigation by complementing expert-based inferences with data-based insights.
Denneboom et al. (Sun,) studied this question.