Uncertain species distribution: From interpolation to extrapolation

Low-Choy, Samantha, Murray, Justine, & van Klinken, Rieks (2012) Uncertain species distribution: From interpolation to extrapolation. Milestone Report provided to RIRDC, Brisbane, Australia.


Species distribution models (SDMs) are considered to exemplify Pattern rather than Process based models of a species' response to its environment. Hence when used to map species distribution, the purpose of SDMs can be viewed as interpolation, since species response is measured at a few sites in the study region, and the aim is to interpolate species response at intermediate sites. Increasingly, however, SDMs are also being used to also extrapolate species-environment relationships beyond the limits of the study region as represented by the training data.

Regardless of whether SDMs are to be used for interpolation or extrapolation, the debate over how to implement SDMs focusses on evaluating the quality of the SDM, both ecologically and mathematically. This paper proposes a framework that includes useful tools previously employed to address uncertainty in habitat modelling. Together with existing frameworks for addressing uncertainty more generally when modelling, we then outline how these existing tools help inform development of a broader framework for addressing uncertainty, specifically when building habitat models. As discussed earlier we focus on extrapolation rather than interpolation, where the emphasis on predictive performance is diluted by the concerns for robustness and ecological relevance. We are cognisant of the dangers of excessively propagating uncertainty. Thus, although the framework provides a smorgasbord of approaches, it is intended that the exact menu selected for a particular application, is small in size and targets the most important sources of uncertainty. We conclude with some guidance on a strategic approach to identifying these important sources of uncertainty. Whilst various aspects of uncertainty in SDMs have previously been addressed, either as the main aim of a study or as a necessary element of constructing SDMs, this is the first paper to provide a more holistic view.

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ID Code: 85671
Item Type: Report
Refereed: No
Keywords: species distribution models, uncertainty, extrapolation, statistical modelling, sources of uncertainty
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Applied Statistics (010401)
Australian and New Zealand Standard Research Classification > BIOLOGICAL SCIENCES (060000) > ECOLOGY (060200) > Ecology not elsewhere classified (060299)
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
  • CRCNPB/CRC90143
Copyright Owner: Copyright 2012 by Samantha J. Low-Choy, Justine Murray and Rieks van Klinken
Copyright Statement: All rights reserved. This book or any portion thereof may not be reproduced or used in any manner whatsoever without the express written permission of the authors except for the use of brief quotations in a book review.
Deposited On: 19 Jul 2015 23:17
Last Modified: 24 Jul 2015 20:10

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