Impact of Spatial Variability in Zooplankton Grazing Rates on Carbon Export Flux
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Impact of Spatial Variability in Zooplankton Grazing Rates on Carbon Export Flux

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https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2023GB008085
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Creative Commons 'BY' version 4.0 license
Abstract

Abstract: The biological carbon pump is a key controller of how much carbon is stored within the global ocean. This pathway is influenced by food web interactions between zooplankton and their prey. In global biogeochemical models, Holling Type functional responses are frequently used to represent grazing interactions. How these responses are parameterized greatly influences biomass and subsequent carbon export estimates. The half‐saturation constant, or k value, is central to the Holling functional response. Empirical studies show k can vary over three orders of magnitude, however, this variation is poorly represented in global models. This study derives zooplankton grazing dynamics from remote sensing products of phytoplankton biomass, resulting in global distribution maps of the grazing parameter k. The impact of these spatially varying k values on model skill and carbon export flux estimates is then considered. This study finds large spatial variation in k values across the global ocean, with distinct distributions for micro‐ and mesozooplankton. High half‐saturation constants, which drive slower grazing, are generally associated with areas of high productivity. Grazing rate parameterization is found to be critical in reproducing satellite‐derived distributions of small phytoplankton biomass, highlighting the importance of top‐down drivers for this size class. Spatially varying grazing dynamics decrease mean total carbon export by >17% compared to globally homogeneous dynamics, with increases in fecal pellet export and decreases in export from algal aggregates. This study highlights the importance of grazing dynamics to both community structure and carbon export, with implications for modeling marine carbon sequestration under future climate scenarios.

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