A Spatial Approach for Modeling Amphibian Road-Kills: Comparison of Regression Techniques

• Tipo: Artigo em Revista Científica Internacional
• Data: 2021

Autores

Sousa Guedes, D (Autor) Outra; Franch, M (Autor) Outra; sillero, n (Autor) FCUP

Revista

Título: ISPRS International Journal of Geo-Information

Vol. 10

Página Final: 343

Editora: MDPI

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00T-Z9Q

DOI: 10.3390/ijgi10050343

Abstract (EN): Road networks are the main source of mortality for many species. Amphibians, which are in global decline, are the most road-killed fauna group, due to their activity patterns and preferred habitats. Many different methodologies have been applied in modeling the relationship between environment and road-kills events, such as logistic regression. Here, we compared the performance of five regression techniques to relate amphibians' road-kill frequency to environmental variables. For this, we surveyed three country roads in northern Portugal in search of road-killed amphibians. To explain the presence of road-kills, we selected a set of environmental variables important for the presence of amphibians and the occurrence of road-kills. We compared the performances of five modeling techniques: (i) generalized linear models, (ii) generalized additive models, (iii) random forest, (iv) boosted regression trees, and (v) geographically weighted regression. The boosted regression trees and geographically weighted regression techniques performed the best, with a percentage of deviance explained between 61.8% and 76.6% and between 55.3% and 66.7%, respectively. Moreover, the geographically weighted regression showed a great advantage over the other techniques, as it allows mapping local parameter coefficients as well as local model performance (pseudo-R-2). The results suggest that geographically weighted regression is a useful tool for road-kill modeling, as well as to better visualize and map the spatial variability of the models.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 13