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| 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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