Species distribution models (SDM) are widely used in ecology, biogeography and conservation. Here, we modelled the distribution of roe deer (Capreolus capreolus) in mainland Spain in order to i) determine its macro-ecological requirements, ii) assess the favourability for this species and iii) explore the model usefulness as an index of the species relative abundance. Our results showed that roe deer distribution can be explained by predictors related with topography, climate, lithology, geography and human activity. Climate was the more relevant factor, followed by human activity, topography, spatial location and lithology. The model accurately predicted the species probability of occurrence and also, but weakly, the species’ relative abundance

Artículos de divulgación

Centro de Vigilancia Sanitaria Veterinaria (VISAVET). Universidad Complutense

English

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Species distribution models (SDM) are widely used in ecology, biogeography and conservation. Here, we modelled the distribution of roe deer (Capreolus capreolus) in mainland Spain in order to i) determine its macro-ecological requirements, ii) assess the favourability for this species and iii) explore the model usefulness as an index of the species relative abundance. Our results showed that roe deer distribution can be explained by predictors related with topography, climate, lithology, geography and human activity. Climate was the more relevant factor, followed by human activity, topography, spatial location and lithology. The model accurately predicted the species probability of occurrence and also, but weakly, the species’ relative abundance

Publicado un nuevo artículo de divulgación en Pirineos. Revista de Ecología de Montaña

30 de diciembre de 2011

Acevedo P., Real R. y Gortazar C.

Species distribution models (SDM) are widely used in ecology, biogeography and conservation. Here, we modelled the distribution of roe deer (Capreolus capreolus) in mainland Spain in order to i) determine its macro-ecological requirements, ii) assess the favourability for this species and iii) explore the model usefulness as an index of the species relative abundance. Our results showed that roe deer distribution can be explained by predictors related with topography, climate, lithology, geography and human activity. Climate was the more relevant factor, followed by human activity, topography, spatial location and lithology. The model accurately predicted the species probability of occurrence and also, but weakly, the species’ relative abundance

Participantes:

	Departamento de Biología Animal. Facultad de Ciencias. Universidad de Málaga (UMA).
	Instituto de Investigación en Recursos Cinegéticos (IREC). Consejo Superior de Investigaciones Científicas (CSIC). Universidad de Castilla La Mancha (UCLM). Gobierno de Castilla-La Mancha (JCCM).

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