4.5 Article

Transferability of environmental favourability models in geographic space: The case of the Iberian desman (Galemys pyrenaicus) in Portugal and Spain

期刊

ECOLOGICAL MODELLING
卷 220, 期 5, 页码 747-754

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecolmodel.2008.12.004

关键词

Distribution modelling; Favourability function; Generalized linear models (GLM); Iberian Peninsula; Model extrapolation

类别

资金

  1. Ministerio de Educacion y Ciencia, Spain [CGL2006-09567/BOS]
  2. FEDER
  3. Portuguese Fundacao para a Ciencia e a Tecnologia [SFRH/BD/4601/2001, SFRH/BPD/40387/2007]
  4. Fundação para a Ciência e a Tecnologia [SFRH/BD/4601/2001, SFRH/BPD/40387/2007] Funding Source: FCT

向作者/读者索取更多资源

Transferring distribution models between different geographical areas may be problematic, as the performance of models outside their original scope is hard to predict. A modelling procedure is needed that gets the gist of the environmental descriptors of a distribution area, without either overfitting to the training data or overestimating the species' distribution potential. We tested the transferability power of the favourability function, a generalized linear model, on the distribution of the Iberian desman (Galemys pyrenaicus) in the Iberian territories of Portugal and Spain. We also tested the effects of two of the main potential constraints on model transferability: the analysed ranges of the predictor variables, and the completeness of the species distribution data. We modelled 10 km x 10 km presence/absence data from Portugal and Spain separately, extrapolated each model to the other country, and compared predictions with observations. The Spanish model, despite arguably containing more false absences, showed good predictive ability in Portugal. The Portuguese model, whose predictors ranged between only a subset of the values observed in Spain, overestimated desman distribution when transferred. We discuss possible reasons for this differential model behaviour, and highlight the importance of this kind of models for prediction and conservation applications. (C) 2008 Elsevier B.V. All rights reserved.

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