DOI: 10.1111/ddi.12634 BIODIVERSITY RESEARCH The need for large-scale distribution data to estimate regional changes in species richness under future climate change Nicolas Titeux1,2,3,4 | Dirk Maes5,6 | Toon Van Daele5 | Thierry Onkelinx5 | Risto K. Heikkinen7 | Helena Romo8 | Enrique García-Barros8 | Miguel L. Munguira6,8 | Wilfried Thuiller9 | Chris A. M. van Swaay6,10 | Oliver Schweiger3 | Josef Settele3,4,6 | Alexander Harpke3 | Martin Wiemers3,6 | Lluís Brotons1,2,11 | Miska Luoto12 1Forest Sciences Centre of Catalonia (CEMFOR-CTFC), InForest Joint Research Unit (CSIC-CTFC-CREAF), Solsona, Catalonia, Spain 2Centre de Recerca Ecològica i Aplicacions Forestals (CREAF), Cerdanyola del Vallés, Spain 3UFZ, Department of Community Ecology, Helmholtz Centre for Environmental Research, Halle, Germany 4iDiv, German Centre for Integrative Biodiversity Research, Halle-Jena-Leipzig, Leipzig, Germany 5Research Institute for Nature and Forest (INBO), Brussels, Belgium 6Butterfly Conservation Europe, Wageningen, the Netherlands 7Finnish Environment Institute, Natural Environment Centre, Helsinki, Finland 8Departamento de Biología, Edificio de Biología, Universidad Autónoma de Madrid, Madrid, Spain 9CNRS, Laboratoire d’Ecologie Alpine (LECA), University of Grenoble Alpes, Grenoble, France 10Dutch Butterfly Conservation, Wageningen, the Netherlands 11Consejo Superior de Investigaciones Científicas (CSIC), Cerdanyola del Vallés, Spain 12Department of Geosciences and Geography, University of Helsinki, Helsinki, Finland Correspondence Nicolas Titeux, Forest Sciences Centre of Abstract Catalonia, Solsona, Catalonia, Spain. Aim: Species distribution models built with geographically restricted data often fail to Email:
[email protected] capture the full range of conditions experienced by species across their entire distribu- Funding information tion area. Using such models to predict distribution shifts under future environmental European Commission Framework Programmes (FP6 and FP7) via the Integrated change may, therefore, produce biased projections.