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      On the sensitivity of plankton ecosystem models to the formulation of zooplankton grazing

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      1 , * , 1 , 2
      PLoS ONE
      Public Library of Science

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          Abstract

          Model representations of plankton structure and dynamics have consequences for a broad spectrum of ocean processes. Here we focus on the representation of zooplankton and their grazing dynamics in such models. It remains unclear whether phytoplankton community composition, growth rates, and spatial patterns in plankton ecosystem models are especially sensitive to the specific means of representing zooplankton grazing. We conduct a series of numerical experiments that explicitly address this question. We focus our study on the form of the functional response to changes in prey density, including the formulation of a grazing refuge. We use a contemporary biogeochemical model based on continuum size-structured organization, including phytoplankton diversity, coupled to a physical model of the California Current System. This region is of particular interest because it exhibits strong spatial gradients. We find that small changes in grazing refuge formulation across a range of plausible functional forms drive fundamental differences in spatial patterns of plankton concentrations, species richness, pathways of grazing fluxes, and underlying seasonal cycles. An explicit grazing refuge, with refuge prey concentration dependent on grazers’ body size, using allometric scaling, is likely to provide more coherent plankton ecosystem dynamics compared to classic formulations or size-independent threshold refugia. We recommend that future plankton ecosystem models pay particular attention to the grazing formulation and implement a threshold refuge incorporating size-dependence, and we call for a new suite of experimental grazing studies.

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          Primary production required to sustain global fisheries

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            Emergent biogeography of microbial communities in a model ocean.

            A marine ecosystem model seeded with many phytoplankton types, whose physiological traits were randomly assigned from ranges defined by field and laboratory data, generated an emergent community structure and biogeography consistent with observed global phytoplankton distributions. The modeled organisms included types analogous to the marine cyanobacterium Prochlorococcus. Their emergent global distributions and physiological properties simultaneously correspond to observations. This flexible representation of community structure can be used to explore relations between ecosystems, biogeochemical cycles, and climate change.
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              The role of functional traits and trade-offs in structuring phytoplankton communities: scaling from cellular to ecosystem level.

              Trait-based approaches to community structure are increasingly used in terrestrial ecology. We show that such an approach, augmented by a mechanistic analysis of trade-offs among functional traits, can be successfully used to explain community composition of marine phytoplankton along environmental gradients. Our analysis of literature on major functional traits in phytoplankton, such as parameters of nutrient-dependent growth and uptake, reveals physiological trade-offs in species abilities to acquire and utilize resources. These trade-offs, arising from fundamental relations such as cellular scaling laws and enzyme kinetics, define contrasting ecological strategies of nutrient acquisition. Major groups of marine eukaryotic phytoplankton have adopted distinct strategies with associated traits. These diverse strategies of nutrient utilization can explain the distribution patterns of major functional groups and size classes along nutrient availability gradients.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ValidationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                25 May 2021
                2021
                : 16
                : 5
                : e0252033
                Affiliations
                [1 ] Laboratoire des Sciences de l’Environnement Marin (LEMAR), Université de Brest, Ifremer, IRD, IUEM, Brest, France
                [2 ] Scripps Institution of Oceanography, University of California, San Diego, La Jolla, California, United States of America
                Stockholm University, SWEDEN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-6233-0377
                Article
                PONE-D-21-04981
                10.1371/journal.pone.0252033
                8148333
                34033649
                e2b82571-47b2-4f87-bf70-b1e77abae427
                © 2021 Chenillat et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 February 2021
                : 8 May 2021
                Page count
                Figures: 7, Tables: 1, Pages: 27
                Funding
                Funded by: ANR
                Award ID: ANR-10-LABX-19-01
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100011264, FP7 People: Marie-Curie Actions;
                Award ID: PRESTIGE-2015-3-0017
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000936, Gordon and Betty Moore Foundation;
                Award ID: GBMF3576
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: 1637632
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000936, Gordon and Betty Moore Foundation;
                Award ID: GBMF5479
                Award Recipient :
                This work was supported by four grants: (1) F.C. received a LabexMer grant ANR-10-LABX-19-01 ( www.labexmer.eu), (2) F.C. received a the PRESTIGE-2015-3-0017 grant from the People Programme (Marie Curie Actions - PRESTIGE program coordinated - by Campus France via the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement n. PCOFUND-GA-2013-609102) ( www.campusfrance.org); (3) M.D.O. received support from the Gordon and Betty Moore Foundation (Grant id GBMF3576 and GBMF5479) ( www.moore.org) (4) M.D.O. received a U.S. NSF grants to the California Current Ecosystem LTER site (#1637632) ( www.nsf.gov/) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Psychology
                Behavior
                Animal Behavior
                Grazing
                Social Sciences
                Psychology
                Behavior
                Animal Behavior
                Grazing
                Biology and Life Sciences
                Zoology
                Animal Behavior
                Grazing
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Plankton
                Zooplankton
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Plankton
                Zooplankton
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Algae
                Phytoplankton
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Plankton
                Phytoplankton
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Plankton
                Phytoplankton
                Biology and Life Sciences
                Ecology
                Community Ecology
                Trophic Interactions
                Predation
                Ecology and Environmental Sciences
                Ecology
                Community Ecology
                Trophic Interactions
                Predation
                Biology and Life Sciences
                Organisms
                Eukaryota
                Animals
                Invertebrates
                Plankton
                Biology and Life Sciences
                Zoology
                Animals
                Invertebrates
                Plankton
                Biology and Life Sciences
                Computational Biology
                Ecosystem Modeling
                Biology and Life Sciences
                Ecology
                Ecosystems
                Ecosystem Modeling
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Ecosystem Modeling
                Biology and Life Sciences
                Ecology
                Ecological Metrics
                Biomass
                Ecology and Environmental Sciences
                Ecology
                Ecological Metrics
                Biomass
                Biology and Life Sciences
                Ecology
                Ecosystems
                Ecology and Environmental Sciences
                Ecology
                Ecosystems
                Custom metadata
                All model data files are available from the figshare database (accession number https://doi.org/10.6084/m9.figshare.12696422.v1). All observation data files are available online: oceaninformatics.ucsd.edu/datazoo.

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