The transferability of distribution models across regions: an amphibian case study


  • Flavio Zanini,

    1. Geographical Information Systems Laboratory, Swiss Federal Institute of Technology Lausanne (EPFL), CH-1015 Lausanne, Switzerland,
    2. Restoration Ecology Group, Swiss Federal Research Institute for Forest, Snow and Landscape (WSL), CH-1015 Lausanne, Switzerland,
    3. Drosera SA, Ch. de la Poudrière 36, CH-1950 Sion, Switzerland,
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  • Jérôme Pellet,

    Corresponding author
    1. Division of Conservation Biology, Institute of Ecology, Balzerstrasse 6, University of Bern, CH-3012 Bern, Switzerland,
    2. A. Maibach Sàrl, Ch. de la Poya 10, CP 99, CH-1610 Oron-la-Ville, Switzerland,
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  • Benedikt R. Schmidt

    1. Zoologisches Institut, Universität Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland,
    2. KARCH, Passage Maximilien-de-Meuron 6, CH-2000 Neuchâtel, Switzerland
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*Correspondence: Jérôme Pellet, E-mail:


Aim  Predicting species distribution is of fundamental importance for ecology and conservation. However, distribution models are usually established for only one region and it is unknown whether they can be transferred to other geographical regions. We studied the distribution of six amphibian species in five regions to address the question of whether the effect of landscape variables varied among regions. We analysed the effect of 10 variables extracted in six concentric buffers (from 100 m to 3 km) describing landscape composition around breeding ponds at different spatial scales. We used data on the occurrence of amphibian species in a total of 655 breeding ponds. We accounted for proximity to neighbouring populations by including a connectivity index to our models. We used logistic regression and information-theoretic model selection to evaluate candidate models for each species.

Location  Switzerland.

Results  The explained deviance of each species’ best models varied between 5% and 32%. Models that included interactions between a region and a landscape variable were always included in the most parsimonious models. For all species, models including region-by-landscape interactions had similar support (Akaike weights) as models that did not include interaction terms. The spatial scale at which landscape variables affected species distribution varied from 100 m to 1000 m, which was in agreement with several recent studies suggesting that land use far away from the ponds can affect pond occupancy.

Main conclusions  Different species are affected by different landscape variables at different spatial scales and these effects may vary geographically, resulting in a generally low transferability of distribution models across regions. We also found that connectivity seems generally more important than landscape variables. This suggests that metapopulation processes may play a more important role in species distribution than habitat characteristics.