The impacts of linear infrastructure on terrestrial vertebrate populations: A trait-based approach.

Abstract

While linear infrastructures, such as roads and power lines, are vital to human development, they may also have negative impacts on wildlife populations up to several kilometres into the surrounding environment (infrastructure-effect zones, IEZs). However, species-specific IEZs are not available for the vast majority of species, hampering global assessments of infrastructure impacts on wildlife. Here, we synthesized 253 studies worldwide to quantify the magnitude and spatial extent of infrastructure impacts on the abundance of 792 vertebrate species. We also identified the extent to which species traits, infrastructure type and habitat modulate IEZs for vertebrate species. Our results reveal contrasting responses across taxa based on the local context and species traits. Carnivorous mammals were generally more abundant in the proximity of infrastructure. In turn, medium- to large-sized non-carnivorous mammals (>1kg) were less abundant near infrastructure across habitats, while their smaller counterparts were more abundant close to infrastructure in open habitats. Bird abundance was reduced near infrastructure with larger IEZs for non-carnivorous than for carnivorous species. Furthermore, birds experienced larger IEZs in closed (carnivores: ≈130 m, non-carnivores: >1km) compared to open habitats (carnivores: ≈70 m, non-carnivores: ≈470 m). Reptiles were more abundant near infrastructure in closed habitats but not in open habitats where abundances were reduced within an IEZ of ≈90 m. Finally, IEZs were relatively small in amphibians (<30 m). These results indicate that infrastructure impact assessments should differentiate IEZs across species and local contexts in order to capture the variety of responses to infrastructure. Our trait-based synthetic approach can be applied in large-scale assessments of the impacts of current and future infrastructure developments across multiple species, including those for which infrastructure responses are not known from empirical data.