Poster Presentation: Coarse-resolution data overestimates species range shifts in response to climate change.
Dr Ilya Maclean, Miss Brittany Trew
1University Of Exeter, Penryn, United Kingdom
Abstract:
Over the last two decades bioclimate models have been widely used to predict distribution shifts in response to climate change. For many species, places with suitable climate are predicted to lie outside their current range, implying catastrophic consequences for life on earth. To date, however, climate change has been implicated as a major cause of the extinction of just a few species. Mounting evidence from palaeoecology provides a compelling explanation for this discrepancy. Many species survived periods of rapid climate change in microrefugia: locations with suitable microclimate that would be missed entirely by coarse-scale bioclimate models. However, research in this emerging field has been hampered by a limited ability to model climates at sufficiently fine resolution. Here we present models that can be applied to provide accurate fine-grained, multidecadal estimates of climate change based on the physical processes that influence microclimate. We apply the models to project historic distributions of 321 plant species and forward to the present day and compare the results to those obtained using coarse-resolution data. We show that the results of bioclimate models are fundamentally linked to the grid cell resolution of the data used to drive them. Models that rely on coarse-resolution data predict major range shifts, whereas fine-scale models predict localised patterns of change that more closely match observed distribution changes. In consequence, species translocations and the redesign of protected area networks to accommodate large-scale range shifts may be less effective than focusing on protecting populations of species within their existing geographic range.
Biography:
Current PhD candidate at the University of Exeter. Investigating fynbos species persistence in a changing climate through fine-scale microclimate modelling.