Abstract
Climate change vulnerability assessments are commonly used to identify species at risk from global climate change, but the wide range of methodologies available makes it difficult for end users, such as conservation practitioners or policy makers, to decide which method to use as a basis for decision-making. Here, we compare the outputs of 12 such climate change vulnerability assessment methodologies, using both real and simulated species, and we test the methods using historic data for British birds and butterflies (i.e., using historical data to assign risks, and more recent data for validation). Our results highlight considerable inconsistencies in species risk assignment across all the approaches considered and suggest the majority of the frameworks are poor predictors of risk under climate change – two methods performed worse than random. Methods that incorporated historic trend data were the only ones to have any validity at predicting distributional trends in subsequent time periods.