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dc.contributor.authorEverett, Jason D.
dc.contributor.authorBaird, Mark E.
dc.contributor.authorBuchanan, Pearse
dc.contributor.authorBulman, Cathy
dc.contributor.authorDavies, Claire
dc.contributor.authorDownie, Ryan
dc.contributor.authorGriffiths, Chris
dc.contributor.authorHeneghan, Ryan
dc.contributor.authorKloser, Rudy J.
dc.contributor.authorLaiolo, Leonardo
dc.contributor.authorLara-Lopez, Ana
dc.contributor.authorLozano-Montes, Hector
dc.contributor.authorMatear, Richard J.
dc.contributor.authorMcEnnulty, Felicity
dc.contributor.authorRobson, Barbara
dc.contributor.authorRochester, Wayne
dc.contributor.authorSkerratt, Jenny
dc.contributor.authorSmith, James A.
dc.contributor.authorStrzelecki, Joanna
dc.contributor.authorSuthers, Iain M.
dc.contributor.authorSwadling, Kerrie M.
dc.contributor.authorvan Ruth, Paul
dc.contributor.authorRichardson, Anthony J.
dc.date.accessioned2018-07-07T21:24:25Z
dc.date.available2018-07-07T21:24:25Z
dc.date.issued2017
dc.identifier.citationEverett Jason D.; Baird Mark E.; Buchanan Pearse, et al (2017) Modeling What We Sample and Sampling What We Model: Challenges for Zooplankton Model Assessment. Frontiers in Marine Science, 4;77, 19pp. DOI:10.3389/fmars.2017.00077.en_US
dc.identifier.urihttp://hdl.handle.net/11329/467
dc.identifier.urihttp://dx.doi.org/10.25607/OBP-51
dc.description.abstractZooplankton are the intermediate trophic level between phytoplankton and fish, and are an important component of carbon and nutrient cycles, accounting for a large proportion of the energy transfer to pelagic fishes and the deep ocean. Given zooplankton’s importance, models need to adequately represent zooplankton dynamics. A major obstacle, though, is the lack of model assessment. Here we try and stimulate the assessment of zooplankton in models by filling three gaps. The first is that many zooplankton observationalists are unfamiliar with the biogeochemical, ecosystem, and size-based and individual-based models that have zooplankton functional groups, so we describe their primary uses and how each typically represents zooplankton. The second gap is that many modelers are unaware of the zooplankton data that are available, and are unaccustomed to the different zooplankton sampling systems, so we describe the main sampling platforms and discuss their strengths and weaknesses for model assessment. Filling these gaps in our understanding of models and observations provides the necessary context to address the last gap – a blueprint for model assessment of zooplankton. We detail two ways that zooplankton biomass/abundance observations can be used to assess models: data wrangling that transforms observations to be more similar to model output; and observation models that transform model outputs to be more like observations. We hope that this review will encourage greater assessment of zooplankton in models and ultimately improve the representation of their dynamics.en_US
dc.language.isoenen_US
dc.rightsAttribution 4.0*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subject.otherZooplanktonen_US
dc.subject.otherModellingen_US
dc.subject.otherContinuous plankton recorderen_US
dc.subject.otherEcosystem modelsen_US
dc.subject.otherNet samplingen_US
dc.titleModeling What We Sample and Sampling What We Model: Challenges for Zooplankton Model Assessment.en_US
dc.typeJournal Contributionen_US
dc.description.refereedRefereeden_US
dc.format.pagerange19pp.en_US
dc.identifier.doihhttps://doi.org/10.3389/fmars.2017.00077
dc.subject.parameterDisciplineParameter Discipline::Biological oceanographyen_US
dc.subject.instrumentTypeInstrument Type Vocabulary::plankton recordersen_US
dc.subject.instrumentTypeInstrument Type Vocabulary::plankton countersen_US
dc.bibliographicCitation.titleFrontiers in Marine Scienceen_US
dc.bibliographicCitation.volume4en_US
dc.bibliographicCitation.issueArticle 77
dc.description.eovZooplankton biomass and diversityen_US
dc.description.bptypeGuideen_US
dc.description.frontiers2016-08-03


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Attribution 4.0
Except where otherwise noted, this item's license is described as Attribution 4.0