Modeling what we sample and sampling what we model: challenges for zooplankton model assessment
Everett, JD and Baird, ME and Buchanan, P and Bulman, C and Davies, C and Downie, R and Griffiths, C and Heneghan, R and Kloser, RJ and Laiolo, L and Lara-Lopez, A and Lozano-Montes, H and Matear, RJ and McEnnulty, F and Robson, B and Rochester, W and Skerratt, J and Smith, JA and Strzelecki, J and Suthers, IM and Swadling, KM and van Ruth, P and Richardson, AJ, Modeling what we sample and sampling what we model: challenges for zooplankton model assessment, Frontiers in Marine Science, 4 Article 77. ISSN 2296-7745 (2017) [Refereed Article]
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 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.