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Abstract Climate change is projected to modify the physical and chemical environment of the ocean, but the quantitative impact on the distribution of phytoplankton groups is unclear. Most Earth System Models (ESMs) predict future declines of phytoplankton in low latitude waters, contradicting observations showing that picophytoplankton can reach high abundance in warm waters. Here, we used a historic and three climate scenarios along with quantitative niche models to projectProchlorococcus,Synechococcus, and picoeukaryotic phytoplankton distributions for the year 2100. First, we found global responses with up to 50% and 9% increase forProchlorococcusandSynechococcusabundances, respectively, and 8% decrease for picoeukaryotic phytoplankton. All groups increased in abundance at low latitude, andSynechococcusand picoeukaryotic phytoplankton showed bands of decreases and increases in mid‐ and high‐latitudes, respectively.Prochlorococcustemporal trends were consistent among ESMs and increased with the strength of the scenario, whileSynechococcusand picoeukaryotic phytoplankton showed mixed results. Second, we evaluated sources of uncertainty associated to future projections. The anthropogenic uncertainty, associated to climate scenarios, increased with time and was relevant forProchlorococcus. The environmental and biological uncertainty, associated to ESMs and niche models, respectively, represented the largest fraction but differed among lineages. Quantifying uncertainties is key because the predicted differences in the future distribution and abundance can have large‐scale consequences on ocean ecosystem functioning.
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Characterizing uncertainty in climate impact projections: a case study with seven marine species on the North American continental shelf
Abstract Projections of climate change impacts on living resources are being conducted frequently, and the goal is often to inform policy. Species projections will be more useful if uncertainty is effectively quantified. However, few studies have comprehensively characterized the projection uncertainty arising from greenhouse gas scenarios, Earth system models (ESMs), and both structural and parameter uncertainty in species distribution modelling. Here, we conducted 8964 unique 21st century projections for shifts in suitable habitat for seven economically important marine species including American lobster, Pacific halibut, Pacific ocean perch, and summer flounder. For all species, both the ESM used to simulate future temperatures and the niche modelling approach used to represent species distributions were important sources of uncertainty, while variation associated with parameter values in niche models was minor. Greenhouse gas emissions scenario contributed to uncertainty for projections at the century scale. The characteristics of projection uncertainty differed among species and also varied spatially, which underscores the need for improved multi-model approaches with a suite of ESMs and niche models forming the basis for uncertainty around projected impacts. Ensemble projections show the potential for major shifts in future distributions. Therefore, rigorous future projections are important for informing climate adaptation efforts.
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- PAR ID:
- 10373929
- Editor(s):
- Travers-Trolet, Morgane
- Date Published:
- Journal Name:
- ICES Journal of Marine Science
- Volume:
- 77
- Issue:
- 6
- ISSN:
- 1054-3139
- Page Range / eLocation ID:
- 2118 to 2133
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Species distribution modelling (SDM), also called environmental or ecological niche modelling, has developed over the last 30 years as a widely used tool used in core areas of biogeography including historical biogeography, studies of diversity patterns, studies of species ranges, ecoregional classification, conservation assessment and projecting future global change impacts. In the 50th anniversary year ofJournal of Biogeography, I reflect on developments in species distribution modelling, illustrate how embedded the methodology has become in all areas of biogeography and speculate on future directions in the field. Challenges to species distribution modelling raised in this journal in 2006 have been addressed to a significant degree. Those challenges are clarification of the niche concept; improved sample design for species occurrence data; model parameterization; predictor selection; assessing model performance and transferability; and integrating correlative and process models of species distributions. SDM is used, often in conjunction with other evidence, to understand past species range dynamics, identify patterns and drivers of biological diversity, identify drivers of species range limits, define and delineate ecoregions, estimate the distributions of biodiversity elements in relation to protected status and to prioritize conservation action, and to forecast species range shifts in response to climate change and other global change scenarios. Areas of progress in SDM that may become more widely accessible and useful tools in biogeography include genetically informed models and community distribution models.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/icesjms/fsaa103
