ALBERT

Description: We present a systematic study of the differences generated by coupling the same ecological–biogeochemical model to a 1°, coarse-resolution, and 1∕6°, eddy-permitting, global ocean circulation model to (a) biogeochemistry (e.g., primary production) and (b) phytoplankton community structure. Surprisingly, we find that the modeled phytoplankton community is largely unchanged, with the same phenotypes dominating in both cases. Conversely, there are large regional and seasonal variations in primary production, phytoplankton and zooplankton biomass. In the subtropics, mixed layer depths (MLDs) are, on average, deeper in the eddy-permitting model, resulting in higher nutrient supply driving increases in primary production and phytoplankton biomass. In the higher latitudes, differences in winter mixed layer depths, the timing of the onset of the spring bloom and vertical nutrient supply result in lower primary production in the eddy-permitting model. Counterintuitively, this does not drive a decrease in phytoplankton biomass but results in lower zooplankton biomass. We explain these similarities and differences in the model using the framework of resource competition theory, and find that they are the consequence of changes in the regional and seasonal nutrient supply and light environment, mediated by differences in the modeled mixed layer depths. Although previous work has suggested that complex models may respond chaotically and unpredictably to changes in forcing, we find that our model responds in a predictable way to different ocean circulation forcing, despite its complexity. The use of frameworks, such as resource competition theory, provides a tractable way to explore the differences and similarities that occur. As this model has many similarities to other widely used biogeochemical models that also resolve multiple phytoplankton phenotypes, this study provides important insights into how the results of running these models under different physical conditions might be more easily understood.

Description: 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.

Description: Regional and idealized modeling studies have shown that increasing the physical resolution of biogeochemical models to include mesoscale and submesoscale dynamics can result in both increases and decreases in phytoplankton biomass and primary production, as well as changes in phytoplankton community structure. Here we present a systematic study of the differences generated by coupling the same ecological-biogeochemical model to a 1°, coarse-resolution, and 1/6°, eddy-permitting, global ocean circulation model. Surprisingly, we find that the modeled phytoplankton community is largely unchanged, with the same phenotypes dominating in both cases. Conversely, there are large regional variations in integrated primary production, phytoplankton and zooplankton biomass. In the subtropics, mixed layer depths are, on average, deeper in the eddy-permitting model, resulting in higher nutrient supply driving increases in primary production and phytoplankton biomass. In the higher latitudes, deeper spring mixed layer depths in the eddy-permitting model result in increased light limitation during the spring bloom. Counter-intuitively, this does not drive a decrease in phytoplankton biomass, but is reflected in decreased primary production and zooplankton biomass. We explain these similarities and differences in the model using the framework of resource competition theory, and find that they are the consequence of changes in the regional and seasonal nutrient supply and light environment, mediated by differences in the modeled mixed layer depths. Although previous work has suggested that complex models may respond chaotically and unpredictably to changes in forcing, we find that our model responds in a predictable way to different ocean circulation forcing, despite its complexity.

Description: 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.