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A tool for simulating and communicating uncertainty when modelling species distributions under future climates

Citation

Gould, SF and Beeton, NJ and Harris, RMB and Hutchinson, MF and Lechner, AM and Porfirio, LL and Mackey, BG, A tool for simulating and communicating uncertainty when modelling species distributions under future climates, Ecology and Evolution, 4, (24) pp. 4798-4811. ISSN 2045-7758 (2014) [Refereed Article]


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Copyright Statement

Copyright 2014 The Authors-Ecology and Evolution published by John Wiley & Sons Ltd. Licenced under Creative Commons Attribution 4.0 (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/

DOI: doi:10.1002/ece3.1319

Abstract

  1. Tools for exploring and communicating the impact of uncertainty on spatial prediction are urgently needed, particularly when projecting species distributions to future conditions.
  2. We provide a tool for simulating uncertainty, focusing on uncertainty due to data quality. We illustrate the use of the tool using a Tasmanian endemic species as a case study. Our simulations provide probabilistic, spatially explicit illustrations of the impact of uncertainty on model projections. We also illustrate differences in model projections using six different global climate models and two contrasting emissions scenarios.
  3. Our case study results illustrate how different sources of uncertainty have different impacts on model output and how the geographic distribution of uncertainty can vary.
  4. Synthesis and applications: We provide a conceptual framework for understanding sources of uncertainty based on a review of potential sources of uncertainty in species distribution modelling; a tool for simulating uncertainty in species distribution models; and protocols for dealing with uncertainty due to climate models and emissions scenarios. Our tool provides a step forward in understanding and communicating the impacts of uncertainty on species distribution models under future climates which will be particularly helpful for informing discussions between researchers, policy makers, and conservation practitioners.

Item Details

Item Type:Refereed Article
Keywords:climate change, MaxEnt, measurement error, simulation, spatial ecology, spatial prediction, species distribution model
Research Division:Biological Sciences
Research Group:Other Biological Sciences
Research Field:Global Change Biology
Objective Division:Environment
Objective Group:Climate and Climate Change
Objective Field:Climate Change Adaptation Measures
Author:Beeton, NJ (Dr Nicholas Beeton)
Author:Harris, RMB (Dr Rebecca Harris)
Author:Lechner, AM (Dr Alex Lechner)
ID Code:98569
Year Published:2014
Web of Science® Times Cited:14
Deposited By:Zoology
Deposited On:2015-02-19
Last Modified:2017-10-31
Downloads:97 View Download Statistics

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