Abstract. Biodiversity of phytoplankton is important for ecosystem stability and marine biogeochemistry. However, the large-scale patterns of diversity are not well understood and are often poorly characterized in terms of statistical relationships with factors such as latitude, temperature and productivity. Here we use ecological theory and a global trait-based ecosystem model to provide mechanistic understanding of patterns of phytoplankton diversity. Our study suggests that phytoplankton diversity across three dimensions of trait space (size, biogeochemical function and thermal tolerance) is controlled by disparate combinations of drivers: the supply rate of the limiting resource, the imbalance in different resource supplies relative to competing phytoplankton demands, size-selective grazing and transport by the moving ocean. Using sensitivity studies we show that each dimension of diversity is controlled by different drivers. Models including only one (or two) of the trait dimensions will have different patterns of diversity than one which incorporates another trait dimension. We use the results of our model exploration to infer the controls on the diversity patterns derived from field observations along meridional transects in the Atlantic and to explain why different taxa and size classes have differing patterns.

<p><strong>Abstract.</strong> Biodiversity of phytoplankton is important for ecosystem stability and marine biogeochemistry. However, the large scale patterns of diversity are not well understood, and are often poorly characterized in terms of statistical relationships with environmental factors (e.g. latitude, temperature, productivity). Here we use ecological theory and a global trait-based ecosystem model to provide mechanistic understanding of patterns of phytoplankton diversity. Our study suggests that phytoplankton diversity across three dimensions of trait space (size, biogeochemical function, and thermal tolerance) is controlled by a disparate combinations of drivers: the supply rate of the limiting resource, the imbalance in different resource supplies relative to competing phytoplanktons’ demands, size-selective grazing, and transport by the moving ocean. Using sensitivity studies we show that each dimension of diversity is controlled by different drivers. Models including only one (or two) of the trait dimensions will have different patterns of diversity than one which incorporates another trait dimension. We use the results of our theory/model exploration to infer the controls on the diversity patterns derived from field observations in meridional transects of the Atlantic and to explain why different taxa and size classes have differing patterns. These results suggest that it is unlikely that any single or even combination of environmental variables will be able to explain patterns of diversity.</p>

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The systematic change in a trait with size is a concise means of representing the diversity and organization of planktonic organisms. Using this simplifying principle, we investigated how interactions between trophic levels, resource concentration, and physiological rates structure the planktonic community. Specifically, we used 3 size-structured nutrient-phytoplankton-zooplankton models differing in their trophic interactions, ranging from herbivorous grazing on one size class to omnivorous grazing on multiple size classes. We parameterized our models based on an extensive review of the literature. The maximum phytoplankton growth, maximum microzooplankton grazing, and phytoplankton half-saturation constant were found to vary inversely with size, and the nutrient half-saturation constant scaled positively with size. We examined the emergent community structure in our models under 4 nutrient regimes: 10, 20, 25, and 30 μM total N. In all models under all nutrient conditions, the normalized biomass of both phytoplankton and microzooplankton decreased with increasing size. As nutrients were in creased, phytoplankton biomass was added to larger size classes with little change in the extant smaller size classes; for microzooplankton, spectra elongated and biomass was added to all size classes. The different grazing behaviors among models led to more subtle changes in the community structure. Overall, we found that phytoplankton are top-down controlled and microzooplankton are largely bottomup controlled. Sensitivity analyses showed that both phytoplankton and microzooplankton biomass vary strongly with the size-dependence of the maximum grazing rate. Therefore, this parameter must be known with the greatest accuracy, given its large influence on the emergent community spectra.

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