The road towards wildlife friendlier infrastructure
Mitigation planning through landscape-level priority settings and species connectivity frameworks
Bibliographic Data
The current global road network expansion scenario poses a conflict of interest between Sustainable Development Goals of human well-being and biosphere, which could be mitigated through strengthening of the Environmental Impact Assessment (EIA) process. Here, we propose the integration in EIAs of a method focusing on landscape-level connectivity for wildlife, based on easily accessible satellite imagery and basic species data that need not be site-specific. This method identifies key locations along the (proposed) road for wildlife connectivity based on expert-based wildlife connectivity models, and specifies the type of measures needed through a behavioral response framework. We tested our proposed method with field data on four species through a single-species occupancy model followed by Bayesian occupancy modeling. We show that the expert-based model resulted in a conservative identification of key locations for mitigation interventions. Furthermore, we highlight how already required traffic bridges and culverts can be incorporated as part of the mitigation strategy. Our method permits incorporation of proactive mitigation measures in the road design to reduce the impact of roads on wildlife and their habitat, helping to limit the need for expensive post-hoc solutions. We present this method through a case-study from Guyana, South America
Civil engineering · Computer security · Environmental planning · Environmental resource management · Geography · Identification (biology · Key (lock · Occupancy · Process (computing · Wildlife · Wildlife corridor · Computer Science · Engineering · Environmental Science · Marine animal studies overview · Wildlife Ecology and Conservation · Wildlife-Road Interactions and Conservation · Ecology
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| Unique citing works | 5 |
|---|---|
| Citations per year | 2,5 |
| Citation span | 2024 - 2026 (3) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 4 |