Description: Aim Develop a biogeographical classification of phytoplankton size distributions for the Atlantic Ocean and predict the global phytoplankton size composition based on prevailing environmental conditions. Location Atlantic Ocean and Global Ocean Methods Using phytoplankton size composition data, nutrient concentrations (nitrite+nitrate, phosphate, and silicate), irradiance, temperature and zooplankton abundances of the Atlantic Meridional Transect programme, we derived and tested an environmental classification method of phytoplankton size distribution with a k-means clustering technique. We then used principal component and Dirichlet multivariate regression analyses to disentangle the relative influence of different environmental conditions on the phytoplankton size composition. Subsequently, we evaluated different probabilisitic models and selected the most parsimonious one to estimate the global phytoplankton size distributions in the world oceans based on global climatology data of the World Ocean Atlas 2009. Results Based only on prevailing environmental conditions and without a priori knowledge concerning, for example, the position of oceanic fronts, the primary productivity, the distribution of organisms or any geographical information, our classification method captures the size structures of phytoplankton communities across the Atlantic. We find a strong influence of temperature and nitrite+nitrate concentration on the prevalence of the different size classes, and we present evidence that both factors may act independently on structuring phytoplankton communities. While at low nitrite+nitrate concentrations temperature has a major structuring impact, at high nitrite+nitrate concentrations its influence is reduced. Finally, we show that the global distribution of phytoplankton community size structure can be predicted by a probabilistic model based only on temperature and nitrite+nitrate. Main conclusion The global distribution of phytoplankton community size structure can be predicted with good approximation using a parsimonious probabilistic model forced by only temperature and nitrite+nitrate data.

Description: It is expected that climate change will have significant impacts on ecosystems. Most model projections agree that the ocean will experience stronger stratification and less nutrient supply from deep waters. These changes will likely affect marine phytoplankton communities and will thus impact on the higher trophic levels of the oceanic food web. The potential consequences of future climate change on marine microbial communities can be investigated and predicted only with the help of mathematical models. Here we present the application of a model that describes aggregate properties of marine phytoplankton communities and captures the effects of a changing environment on their composition and adaptive capacity. Specifically, the model describes the phytoplankton community in terms of total biomass, mean cell size, and functional diversity. The model is applied to two contrasting regions of the Atlantic Ocean (tropical and temperate) and is tested under two emission scenarios: SRES A2 or “business as usual” and SRES B1 or “local utopia.” We find that all three macroecological properties will decline during the next century in both regions, although this effect will be more pronounced in the temperate region. Being consistent with previous model predictions, our results show that a simple trait-based modeling framework represents a valuable tool for investigating how phytoplankton communities may reorganize under a changing climate.