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

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Title A climate of uncertainty: accounting for error in climate variables for species distribution models
Names Stoklosa, Jakub (creator)
Daly, Christopher (creator)
Foster, Scott D. (creator)
Ashcroft, Michael B. (creator)
Warton, David I. (creator)
Date Issued 2015-04 (iso8601)
Note This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by John Wiley & Sons Ltd on behalf of the British Ecological Society. The published article can be found at: http://onlinelibrary.wiley.com/journal/10.1111/%28ISSN%292041-210X.
Abstract 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.
Genre Article
Access Condition http://creativecommons.org/licenses/by-nc-nd/3.0/us/
Topic Climate maps
Identifier 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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