Road Permeability Index: Evaluating the heterogeneous permeability of roads for wildlife crossing

Autor(es)

Assis, Julia C. ^{[1, 2]} ; Giacomini, Henrique C. ^[3] ; Ribeiro, Milton Cezar ^[2]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Energia & Ambiente, Programa Posgrad Ciencia Ambiental PROCAM, Ave Prof Luciano Gualberto 1-289, BR-05508900 Sao Paulo, SP - Brazil

^[2] Univ Estadual Paulista UNESP, Inst Biociencias, Dept Ecol, Spatial Ecol & Conservat Lab LEEC, Ave 24 A, 1515, BR-13506900 Rio Claro, SP - Brazil

^[3] Univ Toronto, Dept Ecol & Evolutionary Biol, Off RW 520B 25 Harbord St, Toronto, ON M5S 3G5 - Canada

• Tipo de documento: Artigo Científico
• Fonte: ECOLOGICAL INDICATORS; v. 99, p. 365-374, APR 2019.
• Citações Web of Science: 2

Resumo

Roads impede ecological flows through landscapes, mainly by acting as barriers to animal movement, reducing habitat connectivity and increasing animal mortality. Road permeability is not homogeneous, and animals perceive traffic and road structures differently. There is a lack of information about how species behave when they face a road. Expert knowledge is an alternative source of information when empirical data are not available. We propose the Road Permeability Index (RPI) as a formal method to incorporate expert knowledge into quantitative assessments of road permeability. We used a multi-taxon, expert-based approach that combines landscape structure and road infrastructure effects on fauna throughout landscapes. All codes are in R language, which are freely available at a GitHub repository. As a study case, we applied the RPI to 28 sampling sites along two highways in the north of Sao Paulo Metropolitan Region-Brazil. We used expert knowledge information on five taxa: primates, bats, medium-and large-sized terrestrial mammals, birds, and amphibians. We also propose a method to rank taxa according to their relative contribution to RPI, which enables prioritization in environmental impact assessments related to roads. For our study case, landscape and road attributes were both important for predicting road permeability, though landscape variables showed a slightly stronger average influence. RPI constitutes a replicable and easily adaptable alternative to evaluate road permeability, particularly in the absence of empirical data. RPI outcomes can inform road impact mitigation strategies and location. (AU)

• Processo FAPESP: 13/50421-2 - Novos métodos de amostragem e ferramentas estatísticas para pesquisa em biodiversidade: integrando ecologia de movimento com ecologia de população e comunidade
• Beneficiário: Milton Cezar Ribeiro
• Linha de fomento: Auxílio à Pesquisa - Regular