A climate of uncertainty: accounting for error in climate variables for species distribution models

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  • 1. Spatial climate variables are routinely used in species distribution models (SDMs) without accounting for the fact that they have been predicted with uncertainty, which can lead to biased estimates, erroneous inference and poor performances when predicting to new settings – for example under climate change scenarios. 2. We show how information on uncertainty associated with spatial climate variables can be obtained from climate data models. We then explain different types of uncertainty (i.e. classical and Berkson error) and use two statistical methods that incorporate uncertainty in climate variables into SDMs by means of (i) hierarchical modelling and (ii) simulation–extrapolation. 3. We used simulation to study the consequences of failure to account for measurement error. When uncertainty in explanatory variables was not accounted for, we found that coefficient estimates were biased and the SDM had a loss of statistical power. Further, this bias led to biased predictions when projecting change in distribution under climate change scenarios. The proposed errors-in-variables methods were less sensitive to these issues. 4. We also fit the proposed models to real data (presence/absence data on the Carolina wren, Thryothorus ludovicianus), as a function of temperature variables. 5. The proposed framework allows for many possible extensions and improvements to SDMs. If information on the uncertainty of spatial climate variables is available to researchers, we recommend the following: (i) first identify the type of uncertainty; (ii) consider whether any spatial autocorrelation or independence assumptions are required; and (iii) attempt to incorporate the uncertainty into the SDM through established statistical methods and their extensions.
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  • Keywords: Measurement error, Errors-in-variables, Hierarchical statistical models, Climate maps, SIMEX, Prediction error, PRISM
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  • Stoklosa, J., Daly, C., Foster, S. D., Ashcroft, M. B., & Warton, D. I. (2015). A climate of uncertainty: accounting for error in climate variables for species distribution models. Methods in Ecology and Evolution, 6(4), 412-423. doi:10.1111/2041-210X.12217
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  • 6
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  • 4
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  • This project is a product of QUEST (Quantifying Uncertainty in Ecosystem Studies) Research Coordination Network (, which is funded by the US National Science Foundation. JS and DIW work was supported by the Australian Research Council Discovery Project (project no. DP0985886, DP130102131), and DIW was supported by Future Fellow (project no. FT120100501). SDF was supported by Marine Biodiversity Hub, a collaborative partnership supported through funding from the Australian Government’s National Environmental Research Programme (NERP). NERP Marine Biodiversity Hub partners include the Institute for Marine and Antarctic Studies, University of Tasmania; CSIRO Wealth from Oceans National Flagship, Geoscience Australia, Australian Institute of Marine Science, Museum Victoria, Charles Darwin University and the University of Western Australia.



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