Trait-based approaches are increasingly used in ecology. Phytoplankton communities, with a rich history as model systems in community ecology, are ideally suited for applying and further developing these concepts. Here we summarize the essential components of trait-based approaches and review their historical and potential application to illuminating phytoplankton community ecology. Major ecological axes relevant to phytoplankton include light and nutrient acquisition and use, natural enemy interactions, morphological variation, temperature sensitivity, and modes of reproduction. Trade-offs between these traits play key roles in determining community structure. Freshwater and marine environments may select for a different suite of traits owing to their different physical and chemical properties. We describe mathematical techniques for integrating traits into measures of growth and fitness and predicting how community structure varies along environmental gradients. Finally, we outline challenges and future directions for the application of trait-based approaches to phytoplankton ecology.

Trait-based approaches to community structure are increasingly used in terrestrial ecology. We show that such an approach, augmented by a mechanistic analysis of trade-offs among functional traits, can be successfully used to explain community composition of marine phytoplankton along environmental gradients. Our analysis of literature on major functional traits in phytoplankton, such as parameters of nutrient-dependent growth and uptake, reveals physiological trade-offs in species abilities to acquire and utilize resources. These trade-offs, arising from fundamental relations such as cellular scaling laws and enzyme kinetics, define contrasting ecological strategies of nutrient acquisition. Major groups of marine eukaryotic phytoplankton have adopted distinct strategies with associated traits. These diverse strategies of nutrient utilization can explain the distribution patterns of major functional groups and size classes along nutrient availability gradients.

Rising ocean temperatures will alter the productivity and composition of marine phytoplankton communities, thereby affecting global biogeochemical cycles. Predicting the effects of future ocean warming on biogeochemical cycles depends critically on understanding how existing global temperature variation affects phytoplankton. Here we show that variation in phytoplankton temperature optima over 150 degrees of latitude is well explained by a gradient in mean ocean temperature. An eco-evolutionary model predicts a similar relationship, suggesting that this pattern is the result of evolutionary adaptation. Using mechanistic species distribution models, we find that rising temperatures this century will cause poleward shifts in species' thermal niches and a sharp decline in tropical phytoplankton diversity in the absence of an evolutionary response.

Redfield noted the similarity between the average nitrogen-to-phosphorus ratio in plankton (N:P = 16 by atoms) and in deep oceanic waters (N:P = 15; refs 1, 2). He argued that this was neither a coincidence, nor the result of the plankton adapting to the oceanic stoichiometry, but rather that phytoplankton adjust the N:P stoichiometry of the ocean to meet their requirements through nitrogen fixation, an idea supported by recent modelling studies. But what determines the N:P requirements of phytoplankton? Here we use a stoichiometrically explicit model of phytoplankton physiology and resource competition to derive from first principles the optimal phytoplankton stoichiometry under diverse ecological scenarios. Competitive equilibrium favours greater allocation to P-poor resource-acquisition machinery and therefore a higher N:P ratio; exponential growth favours greater allocation to P-rich assembly machinery and therefore a lower N:P ratio. P-limited environments favour slightly less allocation to assembly than N-limited or light-limited environments. The model predicts that optimal N:P ratios will vary from 8.2 to 45.0, depending on the ecological conditions. Our results show that the canonical Redfield N:P ratio of 16 is not a universal biochemical optimum, but instead represents an average of species-specific N:P ratios.

Nutrient utilization traits can be used to link the ecophysiology of phytoplankton to population dynamic models and the structure of communities across environmental gradients. Here we analyze a comprehensive literature compilation of four traits: maximum nutrient uptake rate; the half‐saturation constant for nutrient uptake; the minimum subsistence quota, measured for nitrate and phosphate; and maximum growth rate. We also use these traits to analyze two composite traits, uptake affinity and scaled uptake affinity. All traits tend to increase with cell volume, except for scaled uptake affinity and maximum growth rate, which tend to decline with cell volume. Most scaling relationships are the same for freshwater and marine species, although important differences exist. Most traits differ on average between major taxa, but between‐taxon variation is nearly always due to between‐taxon variation in volume. There is some evidence for between‐trait correlations that could constrain trait evolution, but these correlations are difficult to disentangle from correlation driven by cell volume. These results should enhance the parameterization of models that use size or taxonomic group to structure physiological variation in phytoplankton communities.

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Phytoplankton often face the dilemma of living in contrasting gradients of two essential resources: light that is supplied from above and nutrients that are often supplied from below. In poorly mixed water columns, algae can be heterogeneously distributed, with thin layers of biomass found on the surface, at depth, or on the sediment surface. Here, we show that these patterns can result from intraspecific competition for light and nutrients. First, we present numerical solutions of a reaction-diffusion-taxis model of phytoplankton, nutrients, and light. We argue that motile phytoplankton can form a thin layer under poorly mixed conditions. We then analyze a related game theoretical model that treats the depth of a thin layer of phytoplankton as the strategy. The evolutionarily stable strategy is the depth at which the phytoplankton are equally limited by both resources, as long as the layer is restricted to the water column. The layer becomes shallower with an increase in the nutrient supply and deeper with an increase in the light supply. For low nutrient levels, low background attenuation, and shallow water columns, a benthic layer occurs; for intermediate nutrient levels in deep water columns, a deep chlorophyll maximum occurs; and for high nutrient levels, a surface scum occurs. These general patterns are in agreement with field observations. Thus, this model can explain many patterns of algal distribution found in poorly mixed aquatic ecosystems.

“It takes a village to finish (marine) science these days” Paraphrased from Curtis Huttenhower (the Human Microbiome project) The rapidity and complexity of climate change and its potential effects on ocean biota are challenging how ocean scientists conduct research. One way in which we can begin to better tackle these challenges is to conduct community-wide scientific studies. This study provides physiological datasets fundamental to understanding functional responses of phytoplankton growth rates to temperature. While physiological experiments are not new, our experiments were conducted in many laboratories using agreed upon protocols and 25 strains of eukaryotic and prokaryotic phytoplankton isolated across a wide range of marine environments from polar to tropical, and from nearshore waters to the open ocean. This community-wide approach provides both comprehensive and internally consistent datasets produced over considerably shorter time scales than conventional individual and often uncoordinated lab efforts. Such datasets can be used to parameterise global ocean model projections of environmental change and to provide initial insights into the magnitude of regional biogeographic change in ocean biota in the coming decades. Here, we compare our datasets with a compilation of literature data on phytoplankton growth responses to temperature. A comparison with prior published data suggests that the optimal temperatures of individual species and, to a lesser degree, thermal niches were similar across studies. However, a comparison of the maximum growth rate across studies revealed significant departures between this and previously collected datasets, which may be due to differences in the cultured isolates, temporal changes in the clonal isolates in cultures, and/or differences in culture conditions. Such methodological differences mean that using particular trait measurements from the prior literature might introduce unknown errors and bias into modelling projections. Using our community-wide approach we can reduce such protocol-driven variability in culture studies, and can begin to address more complex issues such as the effect of multiple environmental drivers on ocean biota.