How complex should models be? Comparing correlative and mechanistic range dynamics models
Global Change Biology
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Criticism has been levelled at climate-change induced forecasts of species range shifts that do not account explicitly for complex population dynamics. The relative importance of such dynamics under climate change is, however, undetermined because direct tests comparing the performance of demographic models versus simpler ecological niche models are still lacking owing to difficulties in evaluating forecasts using real-world data. We provide the first comparison of the skill of coupled ecological-niche-population models and ecological niche models in predicting documented shifts in the ranges of 20 British breeding bird species across a 40-year period. Forecasts from models calibrated with data centred on 1970 were evaluated using data centred on 2010. We found that more complex coupled ecological-niche-population models (that account for dispersal and metapopulation dynamics) tend to have higher predictive accuracy in forecasting species range shifts than structurally simpler models that only account for variation in climate. However, these better forecasts are achieved only if ecological responses to climate change are simulated without static snapshots of historic land use, taken at a single point in time. In contrast, including both static land use and dynamic climate variables in simpler ecological niche models improves forecasts of observed range shifts. Despite being less skilful at predicting range changes at the grid cell level, ecological niche models do as well, or better, than more complex models at predicting the magnitude of relative change in range size. Therefore, ecological niche models can provide a reasonable first approximation of the magnitude of species’ potential range shifts, especially when more detailed data are lacking on dispersal dynamics, demographic processes underpinning population performance, and change in land cover.
The Australian Research Council supported D.A.F, C.B. and B.W.B (FT140101192, DP1096427, FT100100200, respectively). M.B.A and D.N. acknowledge support from the Foundation for Science and Technology (PTDC/AAG-GLO/0463/2014 and CIBIO - UID/BIA/50027/2013 (POCI-01-0145-FEDER-006821) and the Danish NSF. We thank T. Blackburn and C. Şekercioğlu for expert advice and the regional organisers, validators and volunteers responsible for the occurrence data used in this study.
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