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

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  • Barbosa, A. Márcia
  • Real, Raimundo
  • Mario Vargas, J.

Abstract

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 10km×10km 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.

Suggested Citation

  • Barbosa, A. Márcia & Real, Raimundo & Mario Vargas, J., 2009. "Transferability of environmental favourability models in geographic space: The case of the Iberian desman (Galemys pyrenaicus) in Portugal and Spain," Ecological Modelling, Elsevier, vol. 220(5), pages 747-754.
  • Handle: RePEc:eee:ecomod:v:220:y:2009:i:5:p:747-754
    DOI: 10.1016/j.ecolmodel.2008.12.004
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    References listed on IDEAS

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    1. Eric Post & Mads C. Forchhammer, 2002. "Synchronization of animal population dynamics by large-scale climate," Nature, Nature, vol. 420(6912), pages 168-171, November.
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    Cited by:

    1. Mestre, Frederico & Pita, Ricardo & Paupério, Joana & Martins, Filipa M.S. & Alves, Paulo Célio & Mira, António & Beja, Pedro, 2015. "Combining distribution modelling and non-invasive genetics to improve range shift forecasting," Ecological Modelling, Elsevier, vol. 297(C), pages 171-179.
    2. Acevedo, Pelayo & González-Quirós, Pablo & Prieto, José M. & Etherington, Thomas R. & Gortázar, Christian & Balseiro, Ana, 2014. "Generalizing and transferring spatial models: A case study to predict Eurasian badger abundance in Atlantic Spain," Ecological Modelling, Elsevier, vol. 275(C), pages 1-8.
    3. Marchetto, Elisa & Da Re, Daniele & Tordoni, Enrico & Bazzichetto, Manuele & Zannini, Piero & Celebrin, Simone & Chieffallo, Ludovico & Malavasi, Marco & Rocchini, Duccio, 2023. "Testing the effect of sample prevalence and sampling methods on probability- and favourability-based SDMs," Ecological Modelling, Elsevier, vol. 477(C).
    4. Zhu, Gengping & Fan, Jingyu & Peterson, A. Townsend, 2021. "Cautions in weighting individual ecological niche models in ensemble forecasting," Ecological Modelling, Elsevier, vol. 448(C).
    5. Acevedo, Pelayo & Real, Raimundo, 2011. "Biogeographical differences between the two Capra pyrenaica subspecies, C. p. victoriae and C. p. hispanica, inhabiting the Iberian Peninsula: Implications for conservation," Ecological Modelling, Elsevier, vol. 222(3), pages 814-823.
    6. Guarino, Ernestino de Souza Gomes & Barbosa, Ana Márcia & Waechter, Jorge Luiz, 2012. "Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams," Ecological Modelling, Elsevier, vol. 230(C), pages 22-33.

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