could be quite different using other climate and niche models, we believe that the overall projections and trends will be similar with the present resources at hand. For more precise modelling of future distribution trends for Arabica, mapping and modelling work should incorporate actual (remaining) vegetation, as opposed to a potential vegetation [56], although these data are not presently available. These mapping data would be used to ‘clip’ suitable remaining habitat for Arabica from the models, and provide more accurate estimates for loss of suitable bioclimatic space. More detailed ecological data (subcanopy temperatures, soil/water balance, soil type, humidity, evapotranspiration) is also required. Collecting these data across the entire natural range of Arabica is possible, although a focused approach using selected sites is more realistic. On-the-ground monitoring of stress (e.g. seedling recruitment, flower bud and fruit development, leaf yellowing, leaf drop, and pests and disease) for selected populations (as identified here) over suitable time intervals, will be necessary to fully ground-truth the validity and scaling (e.g. categorization of bioclimatic scoring in terms of morbidity and mortality) of our modelling. There is also a requirement to conduct surveys in areas that have high and low predictions for the presence of Arabica (and suitable remaining vegetation) but presently lacking records of occurrence; ideally presence and absence of populations would be accurately recorded in a systematic manner. Finally, as new climate change models are developed, and existing ones refined, there will be a need to re-analyze the existing data, with greater temporal (e.g. 10 year intervals) and spatial resolution, possibly using some sort of consensus approach. References 1. 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Climate Change and Indigenous Arabica Coffee Acknowledgments We are extremely grateful to the following organizations and researchers for providing the climate data used in this study: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), for making the downscaled datasets available, Robert J. Hijmans (now at University of California, Davis), Susan Cameron, and Juan Parra, at the Museum of Vertebrate Zoology, University of California, Berkeley, in collaboration with Peter Jones and Andrew Jarvis (CIAT), and Karen Richardson (Rainforest CRC) of the WorldClim website (BIOCLIM dataset). We thank Hanna Batchelor (University of York) for assistance with geo-referencing and error correcting of locality records, and Ib Friis (Natural History Museum of Denmark) and Sebsebe Demissew (University of Addis Ababa) for sharing their considerable knowledge of Ethiopian vegetation. We would also like to thank Robert J. 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