Modeling what we sample and sampling what we model: Challenges for zooplankton model assessment
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(Published version)
Date
2017
Authors
Everett, J.D.
Baird, M.E.
Buchanan, P.
Bulman, C.
Davies, C.
Downie, R.
Griffiths, C.
Heneghan, R.
Kloser, R.J.
Laiolo, L.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
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Journal article
Citation
Frontiers in Marine Science, 2017; 4(MAR):77-1-77-19
Statement of Responsibility
Jason D. Everett, Mark E. Baird, Pearse Buchanan, Cathy Bulman, Claire Davies, Ryan Downie, Chris Griffiths, Ryan Heneghan, Rudy J. Kloser, Leonardo Laiolo, Ana Lara-Lopez, Hector Lozano-Montes, Richard J. Matear, Felicity McEnnulty, Barbara Robson, Wayne Rochester, Jenny Skerratt, James A. Smith, Joanna Strzelecki, Iain M. Suthers, Kerrie M. Swadling, Paul van Ruth and Anthony J. Richardson
Conference Name
Abstract
Zooplankton 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, 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 thatmanymodelers 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 ofmodels 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.
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Dissertation Note
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Published: 22 March 2017
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Copyright © 2017 Everett, Baird, Buchanan, Bulman, Davies, Downie, Griffiths, Heneghan, Kloser, Laiolo, Lara-Lopez, Lozano-Montes,Matear,McEnnulty, Robson, Rochester, Skerratt, Smith, Strzelecki, Suthers, Swadling, van Ruth and Richardson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.