A spatial approach for modeling amphibian road-kills: comparison of regression techniques.

Sousa-Guedes, D., Franch, M. y Sillero, N. A spatial approach for modeling amphibian road-kills: comparison of regression techniques. International Journal of Geo-Information. [s.l.]: MDPI. 2021, Vol. 10, Num. 5, pag. 343. DOI 10.3390/ijgi10050343

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.

Datos y Recursos

Metadatos
Descargar
DCAT-AP/NTI-RISP

Información básica
Tipo de recurso Texto
Fecha de creación 17-09-2024
Fecha de última modificación 17-09-2024
Mostrar histórico de cambios
Identificador de los metadatos 57a4efe2-3169-5d08-ad6d-63f14ca27f54
Idioma de los metadatos Español
Temáticas (NTI-RISP)
Categoría del conjunto de alto valor (HVD)
Categoría temática ISO 19115 biota
Identificador alternativo
URI de palabras clave
Codificación UTF-8
Información espacial
Identificador INSPIRE ESPMITECOIEPNBFRAGM732
Temas INSPIRE
Identificador geográfico España
Sistema de Referencia de Coordenadas
Tipo de representación espacial
Extensión espacial
"{\"type\": \"Polygon\", \"coordinates\": [[[-18.16, 27.64], [4.32, 27.64], [4.32, 43.79], [-18.16, 43.79], [-18.16, 27.64]]]}"
Resolución espacial del dataset (m)
Procedencia
Declaración de linaje
Perfil de Metadatos
Conformidad
Conjunto de datos de origen
Frecuencia de actualización
Fuentes
  1. International Journal of Geo-Information. Vol. 10
  2. Num. 5
  3. pag. 343
Propósito
Pasos del proceso
Cobertura temporal (Inicio)
Cobertura temporal (Fin)
Notas sobre la versión
Versión
Vigencia del conjunto de datos
Parte responsable
Nombre del autor Sousa-Guedes, D., Franch, M. y Sillero, N.
Nombre del mantenedor
Identificador del autor
Email del autor
Web del autor
Identificador del mantenedor
Email del mantenedor
Web del mantenedor