Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty
Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its thr...
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ftdryad:oai:v1.datadryad.org:10255/dryad.160225 2023-05-15T13:57:22+02:00 Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty Freer, Jennifer J. Partridge, Julian C. Tarling, Geraint A. Collins, Martin A. Genner, Martin J. Southern Ocean 2017-11-14T14:24:00Z http://hdl.handle.net/10255/dryad.160225 https://doi.org/10.5061/dryad.4f98t unknown doi:10.5061/dryad.4f98t/1 doi:10.1007/s00227-017-3239-1 doi:10.5061/dryad.4f98t Freer JJ, Partridge JC, Tarling GA, Collins MA, Genner MJ (2018) Predicting ecological responses in a changing ocean: the effects of future climate uncertainty. Marine Biology 165: 7. http://hdl.handle.net/10255/dryad.160225 climate change climate model IPCC projection sea surface temperature species distribution modelling uncertainty Article 2017 ftdryad https://doi.org/10.5061/dryad.4f98t https://doi.org/10.5061/dryad.4f98t/1 https://doi.org/10.1007/s00227-017-3239-1 2020-01-01T15:58:30Z Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica. Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies. Article in Journal/Newspaper Antarc* Antarctica Southern Ocean Dryad Digital Repository (Duke University) Southern Ocean |
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Dryad Digital Repository (Duke University) |
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topic |
climate change climate model IPCC projection sea surface temperature species distribution modelling uncertainty |
spellingShingle |
climate change climate model IPCC projection sea surface temperature species distribution modelling uncertainty Freer, Jennifer J. Partridge, Julian C. Tarling, Geraint A. Collins, Martin A. Genner, Martin J. Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty |
topic_facet |
climate change climate model IPCC projection sea surface temperature species distribution modelling uncertainty |
description |
Predicting how species will respond to climate change is a growing field in marine ecology, yet knowledge of how to incorporate the uncertainty from future climate data into these predictions remains a significant challenge. To help overcome it, this review separates climate uncertainty into its three components (scenario uncertainty, model uncertainty, and internal model variability) and identifies four criteria that constitute a thorough interpretation of an ecological response to climate change in relation to these parts (awareness, access, incorporation, communication). Through a literature review, the extent to which the marine ecology community has addressed these criteria in their predictions was assessed. Despite a high awareness of climate uncertainty, articles favoured the most severe emission scenario, and only a subset of climate models were used as input into ecological analyses. In the case of sea surface temperature, these models can have projections unrepresentative against a larger ensemble mean. Moreover, 91% of studies failed to incorporate the internal variability of a climate model into results. We explored the influence that the choice of emission scenario, climate model, and model realisation can have when predicting the future distribution of the pelagic fish, Electrona antarctica. Future distributions were highly influenced by the choice of climate model, and in some cases, internal variability was important in determining the direction and severity of the distribution change. Increased clarity and availability of processed climate data would facilitate more comprehensive explorations of climate uncertainty, and increase in the quality and standard of marine prediction studies. |
format |
Article in Journal/Newspaper |
author |
Freer, Jennifer J. Partridge, Julian C. Tarling, Geraint A. Collins, Martin A. Genner, Martin J. |
author_facet |
Freer, Jennifer J. Partridge, Julian C. Tarling, Geraint A. Collins, Martin A. Genner, Martin J. |
author_sort |
Freer, Jennifer J. |
title |
Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty |
title_short |
Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty |
title_full |
Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty |
title_fullStr |
Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty |
title_full_unstemmed |
Data from: Predicting ecological responses in a changing ocean: the effects of future climate uncertainty |
title_sort |
data from: predicting ecological responses in a changing ocean: the effects of future climate uncertainty |
publishDate |
2017 |
url |
http://hdl.handle.net/10255/dryad.160225 https://doi.org/10.5061/dryad.4f98t |
op_coverage |
Southern Ocean |
geographic |
Southern Ocean |
geographic_facet |
Southern Ocean |
genre |
Antarc* Antarctica Southern Ocean |
genre_facet |
Antarc* Antarctica Southern Ocean |
op_relation |
doi:10.5061/dryad.4f98t/1 doi:10.1007/s00227-017-3239-1 doi:10.5061/dryad.4f98t Freer JJ, Partridge JC, Tarling GA, Collins MA, Genner MJ (2018) Predicting ecological responses in a changing ocean: the effects of future climate uncertainty. Marine Biology 165: 7. http://hdl.handle.net/10255/dryad.160225 |
op_doi |
https://doi.org/10.5061/dryad.4f98t https://doi.org/10.5061/dryad.4f98t/1 https://doi.org/10.1007/s00227-017-3239-1 |
_version_ |
1766265048047550464 |