A tool for simulating and communicating uncertainty when modelling species distributions under future climates
Abstract Tools for exploring and communicating the impact of uncertainty on spatial prediction are urgently needed, particularly when projecting species distributions to future conditions. We provide a tool for simulating uncertainty, focusing on uncertainty due to data quality. We illustrate the us...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-12-01
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| Series: | Ecology and Evolution |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/ece3.1319 |
| _version_ | 1797742145588690944 |
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| author | Susan F. Gould Nicholas J. Beeton Rebecca M. B. Harris Michael F. Hutchinson Alex M. Lechner Luciana L. Porfirio Brendan G. Mackey |
| author_facet | Susan F. Gould Nicholas J. Beeton Rebecca M. B. Harris Michael F. Hutchinson Alex M. Lechner Luciana L. Porfirio Brendan G. Mackey |
| author_sort | Susan F. Gould |
| collection | DOAJ |
| description | Abstract Tools for exploring and communicating the impact of uncertainty on spatial prediction are urgently needed, particularly when projecting species distributions to future conditions. 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. 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. 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. |
| first_indexed | 2024-03-12T14:36:47Z |
| format | Article |
| id | doaj.art-ffcff5e8e580479cbf386b6bba18e6db |
| institution | Directory Open Access Journal |
| issn | 2045-7758 |
| language | English |
| last_indexed | 2024-03-12T14:36:47Z |
| publishDate | 2014-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj.art-ffcff5e8e580479cbf386b6bba18e6db2023-08-17T06:29:15ZengWileyEcology and Evolution2045-77582014-12-014244798481110.1002/ece3.1319A tool for simulating and communicating uncertainty when modelling species distributions under future climatesSusan F. Gould0Nicholas J. Beeton1Rebecca M. B. Harris2Michael F. Hutchinson3Alex M. Lechner4Luciana L. Porfirio5Brendan G. Mackey6Griffith Climate Change Response Program Griffith University Southport Queensland AustraliaSchool of Biological Sciences University of Tasmania Hobart Tasmania AustraliaAntarctic Climate and Ecosystems CRC Hobart Tasmania AustraliaAustralian National University Canberra Australian Capital Territory AustraliaUniversity of Tasmania Hobart Tasmania AustraliaAustralian National University Canberra Australian Capital Territory AustraliaGriffith University Southport Queensland AustraliaAbstract Tools for exploring and communicating the impact of uncertainty on spatial prediction are urgently needed, particularly when projecting species distributions to future conditions. 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. 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. 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.https://doi.org/10.1002/ece3.1319Climate changeMaxEntmeasurement errorsimulationspatial ecologyspatial prediction |
| spellingShingle | Susan F. Gould Nicholas J. Beeton Rebecca M. B. Harris Michael F. Hutchinson Alex M. Lechner Luciana L. Porfirio Brendan G. Mackey A tool for simulating and communicating uncertainty when modelling species distributions under future climates Ecology and Evolution Climate change MaxEnt measurement error simulation spatial ecology spatial prediction |
| title | A tool for simulating and communicating uncertainty when modelling species distributions under future climates |
| title_full | A tool for simulating and communicating uncertainty when modelling species distributions under future climates |
| title_fullStr | A tool for simulating and communicating uncertainty when modelling species distributions under future climates |
| title_full_unstemmed | A tool for simulating and communicating uncertainty when modelling species distributions under future climates |
| title_short | A tool for simulating and communicating uncertainty when modelling species distributions under future climates |
| title_sort | tool for simulating and communicating uncertainty when modelling species distributions under future climates |
| topic | Climate change MaxEnt measurement error simulation spatial ecology spatial prediction |
| url | https://doi.org/10.1002/ece3.1319 |
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