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.
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