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Investigating uncertainties in zooplankton composition shifts under climate change scenarios in the Mediterranean Sea

Benedetti, F., Guilhaumon, F., Adloff, F. and Ayata, S.-D. (2018) Investigating uncertainties in zooplankton composition shifts under climate change scenarios in the Mediterranean Sea. Ecography, 41 (2). pp. 345-360. ISSN 09067590

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To link to this item DOI: 10.1111/ecog.02434

Abstract/Summary

Ensemble niche modelling has become a common framework to predict changes in assemblages composition under climate change scenarios. The amount of uncertainty generated by the different components of this framework has rarely been assessed. In the marine realm forecasts have usually focused on taxa representing the top of the marine food‐web, thus overlooking their basal component: the plankton. Calibrating environmental niche models at the global scale, we modelled the habitat suitability of 106 copepod species and estimated the dissimilarity between present and future zooplanktonic assemblages in the surface Mediterranean Sea. We identified the patterns (species replacement versus nestedness) driving the predicted dissimilarity, and quantified the relative contributions of different uncertainty sources: environmental niche models, greenhouse gas emission scenarios, circulation model configurations and species prevalence. Our results confirm that the choice of the niche modelling method is the greatest source of uncertainty in habitat suitability projections. Presence‐only and presence–absence methods provided different visions of the niches, which subsequently lead to different future scenarios of biodiversity changes. Nestedness with decline in species richness is the pattern driving dissimilarity between present and future copepod assemblages. Our projections contrast with those reported for higher trophic levels, suggesting that different components of the pelagic food‐web may respond discordantly to future climatic changes.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:70732
Publisher:Wiley

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