Esteban Acevedo-Trejos

• Microscopic photoautotrophs play crucial roles in global marine ecosystems by influencing food-webs, nutrient cycles and Earth's climate. Therefore, investigating the mechanisms that drive phytoplankton communities in the ocean is a task of fundamental importance. Scientists use broad temporal and spatial observations together with numerical models to study the response of these marine microbial communities to different environmental conditions. However, many studies have been describing much of the ecological and environmental variation with methods deeply rooted in the observed natural complexity. This approach prevents us from obtaining valuable insights on the underlying mechanisms that determine the diversity and composition of phytoplankton communities. In the present thesis this issue was tackled by applying a simple framework based on three prominent perspectives in ecology, namely: macroecology, trait-based community ecology and complex adaptive systems. Specifically, here it is shown how the application of a coerced structure, based on the mentioned concepts, helps to identify large-scale biogeographic patterns of phytoplankton community size structure in the global ocean, and to mathematically describes with a size-based model the phytoplankton communities under modern and future environmental regimes. The first prominent result showed that the size structure of a phytoplankton community can be adequately described by a parsimonious probabilistic model of temperature and nutrients. Second, simulations based on present and future environmental conditions obtained with the size-based model suggested that the major mechanisms shaping the functional diversity and structure of marine microbial communities are nutrient availability and grazing pressure. The model was contrasted with observations of nutrient concentrations, phytoplankton biomass and community size distribution. In addition, the relevance of the top-down and bottom-up controls in reorganizing the phytoplankton communities where thoroughly tested with a number of sensitivity analyses. Overall this study contributed to the knowledge of marine phytoplankton ecology by proposing a new probabilistic approach to assess the biogeographic patterns of size structured microbial communities and their relationships with prevailing environmental conditions. In addition, this work provides a simple and consistent mechanistic description of marine phytoplankton communities, which links its total biomass, its community size structure and its functional diversity with changes in the environment. This contribution presents an advancement from classical approaches by describing the dynamics of a whole phytoplankton community by its aggregate properties.