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In the context of maintenance of biodiversity and ecological functions, microbial ecologists face the challenge of linking individual level variability in functional traits to larger scale ecosystem processes. Phytoplankton cell size and shape are key traits under selection by environmental filters and species interactions. Spatial differences in resource availability shape species diversity according to their use efficiency. Niche partitioning promotes plankton diversity. Here, we explore how size and shape enter the diversity game. How does taxonomic and morpho-functional community structure vary at different spatial scales? What are the potential drivers shaping the structure of phytoplankton communities? We explore these questions by looking at the individual level variability in taxonomic and morphological traits in a biogeographical snapshot of natural phytoplankton communities in coastal ecosystems around the globe. We found that taxonomic variability is mainly concentrated at local and regional levels, whereas shape and size variability are mainly concentrated at a local level, despite the environmental heterogeneity of ecosystems. Species diversity was more variable than trait diversity from local to global spatial scales. We suggest that structural organization of phytoplankton communities in coastal ecosystems may follow a hierarchical pattern of trait organization, where a different combination of multiple functional traits may represent effective strategies and promote success under given environmental conditions as a resolution of Hutchinson's paradox.

Quantifying how environmental factors control the growth of phytoplankton communities is essential for building a mechanistic understanding of global biogeochemical cycles and aquatic food web dynamics. The strong effects of temperature on population growth rate have inspired two frameworksthe Eppley curve and the metabolic theory of ecologythat produce different quantitative relationships and employ distinct statistical approaches. Reconciling these relationships is necessary to ensure the accuracy of ecosystem models. In this paper, we develop ways to compare these frameworks, overcoming their methodological differences. Then, analyzing an extensive dataset (> 4200 growth rate measurements), we find that increases in population growth rate with temperature are consistent with metabolic theory, and weaker than previous estimates of the Eppley curve. A 10 degrees C temperature increase will increase growth rates by a factor of 1.53, rather than 1.88 as in previous studies of the Eppley curve. Size and functional group membership are also critical. Population growth rates decrease with size, but much less strongly that metabolic theory predicts. The growth rates of different functional groups scale similarly with temperature, but some groups grow faster than others, independent of temperature. Our results reconcile the analytical methods of the Eppley curve and metabolic theory, demonstrate that metabolic theory's temperature-scaling predictions are more accurate, and provide new insights into the factors controlling phytoplankton growth. To avoid over-estimating the effects of temperature on primary productivity, the parameterization of ecosystem models should be revised.

Temperature and nutrients are fundamental, highly nonlinear drivers of biological processes, but we know little about how they interact to influence growth. This has hampered attempts to model population growth and competition in dynamic environments, which is critical in forecasting species distributions, as well as the diversity and productivity of communities. To address this, we propose a model of population growth that includes a new formulation of the temperature-nutrient interaction and test a novel prediction: that a species' optimum temperature for growth, T-opt, is a saturating function of nutrient concentration. We find strong support for this prediction in experiments with a marine diatom, Thalassiosira pseudonana: T-opt decreases by 3-6 degrees C at low nitrogen and phosphorus concentrations. This interaction implies that species are more vulnerable to hot, low-nutrient conditions than previous models accounted for. Consequently the interaction dramatically alters species' range limits in the ocean, projected based on current temperature and nitrate levels as well as those forecast for the future. Ranges are smaller not only than projections based on the individual variables, but also than those using a simpler model of temperature-nutrient interactions. Nutrient deprivation is therefore likely to exacerbate environmental warming's effects on communities.

Lake Baikal, Siberia, is the most biodiverse freshwater lake on Earth. However, despite decades of painstaking limnological research on Baikal, broad spatial data on nutrient (nitrogen (N), phosphorus (P), silica (Si)) concentrations and temperature are sparse, as is our understanding of the bottom-up factors that limit phytoplankton in the lake. Earlier studies have suggested both N and P as limiting nutrients in Baikal, but the evidence, mostly based on elemental ratios, is limited and somewhat conflicting. We present experimental evidence that N and P co-limit phytoplankton productivity in some areas of Baikal during summer, along with the results of a comprehensive spatial survey of surface temperature, nutrients and chlorophyll a (Chl a) in Lake Baikal that support the experimental finding of colimitation. Surface water incubations from two trophically contrasting locations revealed co-limitation by N and P, as well as a positive effect of temperature (fluorescence after 5 d was similar to 10% higher at 15 degrees C than at 10 degrees C). In a linear model of the survey data (26 sampling locations), N, P, and their interaction (N x P) were all significant predictors of Chl a concentration, indicating that either N or P (or both) may limit summer phytoplankton, depending on location. In contrast to the incubation experiments, temperature was not a significant predictor of Chl a concentration across the 26 sites we sampled. Lake Baikal is undergoing rapid warming and increased nutrient loading, which may boost phytoplankton productivity in the lake; however, the magnitude of this response will depend on ratios of soluble N and P inputs.