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Model-based uncertainty in species range prediction

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Abstract Aim 

Many attempts to predict the potential range of species rely on environmental niche (or ‘bioclimate envelope’) modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions, identify key reasons why model output may differ and discuss the implications that model uncertainty has for policy-guiding applications. Location 

The Western Cape of South Africa. Methods 

We applied nine of the most widely used modelling techniques to model potential distributions under current and predicted future climate for four species (including two subspecies) of Proteaceae. Each model was built using an identical set of five input variables and distribution data for 3996 sampled sites. We compare model predictions by testing agreement between observed and simulated distributions for the present day (using the area under the receiver operating characteristic curve (AUC) and kappa statistics) and by assessing consistency in predictions of range size changes under future climate (using cluster analysis). Results 

Our analyses show significant differences between predictions from different models, with predicted changes in range size by 2030 differing in both magnitude and direction (e.g. from 92% loss to 322% gain). We explain differences with reference to two characteristics of the modelling techniques: data input requirements (presence/absence vs. presence-only approaches) and assumptions made by each algorithm when extrapolating beyond the range of data used to build the model. The effects of these factors should be carefully considered when using this modelling approach to predict species ranges. Main conclusions 

We highlight an important source of uncertainty in assessments of the impacts of climate change on biodiversity and emphasize that model predictions should be interpreted in policy-guiding applications along with a full appreciation of uncertainty.
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Keywords: Bioclimate envelope modelling; Cape Flora; Proteaceae; South Africa; biodiversity; climate change; conservation biogeography; distribution modelling; environmental niche modelling; species biodiversity

Document Type: Research Article

Affiliations: 1: Laboratoire d'Ecologie Alpine UMR CNRS 5553 BP53, Grenoble Cedex 9, France 2: Instituto de Biología, Universidad Nacional Autónoma de México, Ciudad Universitaria, Mexico City, Mexico 3: Centre Tecnolòlogic Forestal de Catalunya, Pujada del Seminari s/n, Solsona, Catalunya, Spain 4: Environment Department, University of York, Heslington, York 5: UNEP World Conservation Monitoring Centre, Cambridge, UK 6: Unidade de Macroecologia e Conservação, Universidade de Évora, Estrada dos Leões, Évora, Portugal 7: Centre for the Study of Environmental Change and Sustainability, University of Edinburgh, Edinburgh, UK

Publication date: October 1, 2006

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