Composite logistic regression models simulating the potential effect of global climate change on forests dynamics in the southern Iberian Peninsula identify Holm oak [ Quercus ilex subsp. ballota (Desf.) Samp.] and Aleppo pine ( Pinus halepensis Mill.) as the chief beneficiaries of the anticipated environmental shifts, whereas other oak species and conifers suffer a decline. The ten most important tree species (five oaks and five conifers) in Southern Spain were selected for the study. The study area, corresponding to the region of Andalusia, is located in an interesting position between Central European and North African climates. The territory also exhibits the most extreme patterns of rainfall in the Iberian Peninsula. This study aims to model the potential distribution of the ten species in response to climate change, in several time periods, including the present and two future twenty-first century dates. The potential distributions within the different scenarios were simulated using logistic regression techniques based on a set of 19 climate variables from the WorldClim 1.4 project. The scenarios were drawn from the RCP 2.6 and 6.0 in the CCSM4 Global Circulation Model. The resolution of the output maps was 30 arc-seconds. The simulation predicted increased distribution areas for Q. ilex and P. halepensis under the four future scenarios as compared to present. The eight remaining taxa suffered a severe retraction in potential distribution. Global climate change is likely to have a significant impact on forest dynamics in southern Spain. Only two species would benefit to the detriment of the others. Logistic Regression is identified as a robust method for carrying out management and conservation programmes.
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