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...
| Main Authors: | , , , , |
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| Format: | Dataset |
| Language: | unknown |
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2018
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| Online Access: | https://zenodo.org/record/4978994 https://doi.org/10.5061/dryad.4f98t |
| Summary: | 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. processed CMIP5 SST projectionsThis file has projected annual mean Sea Surface Temperature (SST) averaged over the time period 1981-2100. Data are taken from 15 CMIP5 climate models under two emission scenarios, RCP 4.5 and RCP 8.5. Where possible, multiple realisations of a climate model are included, as well ... |
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