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Two endemic plant species in the Mediterranean island of Cyprus, Crocuscyprius and Ophrys kotschyi, were used as a case study. We have coupled climatechange scenarios, and land use change models with species distribution models.Future land use scenarios were modelled by initially calculating the rate ofcurrent land use changes between two time snapshots (2000 and 2006) on theisland, and based on these transition probabilities markov-chain cellularautomata were used to generate future land use changes for 2050. Climate changescenarios A1B, A2, B1 and B2A were derived from the IPCC reports. Speciesclimatic preferences were derived from their current distributions usingclassification trees while habitats preferences were derived from the Red DataBook of the Flora of Cyprus. A bioclimatic model for Crocus cyprius was builtusing mean temperature of wettest quarter, max temperature of warmest month andprecipitation seasonality, while for Ophrys kotchyi the bioclimatic model wasbuilt using precipitation of wettest month, mean temperature of warmestquarter, isothermality, precipitation of coldest quarter, and annualprecipitation. Sequentially, simulation scenarios were performed regardingfuture species distributions by accounting climate alone and both climate andland use changes. The distribution of the two species resulting from thebioclimatic models was then filtered by future land use changes, providing thespecies projected potential distribution. The species projected potentialdistribution varies depending on the type and scenario used, but many of bothspecies current sites/locations are projected to be outside their futurepotential distribution. Our results demonstrate the importance of includingboth land use and climatic changes in predictive species modeling.

Modelling the combined effects of land use and climatic changes:  coupling bioclimatic modelling with markov-chain cellular automata in a case  study in Cyprus