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Article

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

1
Centro de Investigação em Ciências Geo-Espaciais (CICGE), Faculdade de Ciências da Universidade do Porto, Alameda do Monte da Virgem, 4430-146 Vila Nova de Gaia, Portugal
2
PECAT Research Group, Departament de Ciències Ambientals, Universitat de Girona, 17003 Girona, Spain
*
Author to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2021, 10(5), 343; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050343
Received: 15 April 2021 / Revised: 14 May 2021 / Accepted: 16 May 2021 / Published: 18 May 2021
(This article belongs to the Special Issue Application of GIS for Biodiversity Research)
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-R2). 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. View Full-Text
Keywords: ecological niche modeling; geographically weighted regression; logistic regression; road ecology; spatial regression; wildlife-vehicle collision ecological niche modeling; geographically weighted regression; logistic regression; road ecology; spatial regression; wildlife-vehicle collision
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MDPI and ACS Style

Sousa-Guedes, D.; Franch, M.; Sillero, N. A Spatial Approach for Modeling Amphibian Road-Kills: Comparison of Regression Techniques. ISPRS Int. J. Geo-Inf. 2021, 10, 343. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050343

AMA Style

Sousa-Guedes D, Franch M, Sillero N. A Spatial Approach for Modeling Amphibian Road-Kills: Comparison of Regression Techniques. ISPRS International Journal of Geo-Information. 2021; 10(5):343. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050343

Chicago/Turabian Style

Sousa-Guedes, Diana, Marc Franch, and Neftalí Sillero. 2021. "A Spatial Approach for Modeling Amphibian Road-Kills: Comparison of Regression Techniques" ISPRS International Journal of Geo-Information 10, no. 5: 343. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi10050343

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