Combining climate with other influential factors for modelling the impact of climate change on species distribution

• DOI: 10.1007/s10584-010-0010-8
• Publication Date: 2011-02-07T14:53:54Z
• Authors: Ana Luz Márquez; Raimundo Real; Jesús Olivero; Alba Estrada
• Keywords: Akaike information criterion; Bayesian information criterion; Species distribution

We tested two approaches to forecast species distributions while balancing the impact of climate change against the inertia promoted by other influential factors that have been forecast as not changing. Given that mountain species are presumed to be more at risk due to climate warming, we selected an amphibian, a reptile, a bird, and a mammal species present in the Spanish mountains, to model their distributional response to climate change during this century. The climatic forecasts were made according to the general circulation models CGCM2 and ECHAM4 and to the A2 and B2 emission scenarios. We modelled the response of the species to spatial, topographic, human, and climatic variables separately. In our first approach, we compared each of these single-factor models using the Akaike Information Criterion, and produced a combined model weighting each factor (spatial, topographic, human, and climatic) according to Akaike weights. This procedure overestimated the best model, and the other factors were neglected in the combined model output. In our second approach, we produced a combined model using stepwise selection of the variables previously selected within each factor. In this way every factor was effectively represented in the combined explanatory model of the distributional response of the species to environmental conditions. This enabled the construction of models that combined climate with the other explanatory factors, to be later extrapolated to the future by replacing current climatic and human values with those expected from each emission and socio-economic scenario, while preserving spatial and topographic variables in the model.<br/>This work was partially financed by the Consejería de Innovación, Ciencia y Empresa, Junta de Andalucía, Spain (project P05-RNM-00935) and the Ministerio de Educación y Ciencia of Spain and FEDER (projects CGL2006-0956 and CGL2009-11316/BOS). A. Estrada has a postdoctoral contract jointly financed by the European Social Fund and by the Junta de Comunidades de Castilla-La Mancha (Spain), in the framework of the Operational Programme FSE 2007–2013.<br/>Peer Reviewed<br/>