Temperature-nutrient interactions exacerbate sensitivity to warming in phytoplankton.

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, Topt , is a saturating function of nutrient concentration. We find strong support for this prediction in experiments with a marine diatom, Thalassiosira pseudonana: Topt decreases by 3-6 °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.

A three-way trade-off maintains functional diversity under variable resource supply.

The resources that organisms depend on often fluctuate over time, and a variety of common traits are thought to be adaptations to variable resource supply. To understand the trait structure of communities, it is necessary to understand the functional trade-offs that determine what trait combinations are possible and which species can persist and coexist in a given environment. We compare traits across phytoplankton species in order to test for proposed trade-offs between maximum growth rate, equilibrium competitive ability for phosphorus (P), and ability to store P. We find evidence for a three-way trade-off between these traits, and we use empirical trait covariation to parameterize a mechanistic model of competition under pulsed P supply. The model shows that different strategies are favored under different conditions of nutrient supply regime, productivity, and mortality. Furthermore, multiple strategies typically coexist, and the range of traits that persist in the model is similar to the range of traits found in real species. These results suggest that mechanistic models informed by empirical trait variation, in combination with data on the trait structure of natural communities, will play an important role in uncovering the mechanisms that underlie the diversity and structure of ecological communities.

Ecological specialization and trade affect the outcome of negotiations in mutualism.

By definition, mutualisms involve the exchange of goods or services between partners. It has been shown that mutualism can grade into parasitism, but even when exchange is mutually beneficial, a conflict of interest remains because each partner benefits from reaping more benefits at a lower cost. Metaphorically, the partners negotiate the conditions of trade, the outcome of which will determine the net benefit to each partner. Each partner can adjust its allocation to self-provisioning while negotiating the ratio at which benefits are exchanged. To understand how these two features of trade affect mutualisms, we used the example of the plant-arbuscular mycorrhizal mutualism and modeled uptake and trade of two resources, phosphorus and carbon. In most contexts, the fungus specialized on phosphorus uptake while the plant took up both phosphorus and carbon. However, when phosphorus was abundant and light was scarce, the plant specialized, taking up only carbon and relying on trade for phosphorus. Resource availability was the most important factor determining specialization and the outcome of negotiation and trade, but other aspects of the context were also important. These results suggest experiments to link these two key features of trade with environmental conditions to determine the outcome of mutualism.

Evidence for a three-way trade-off between nitrogen and phosphorus competitive abilities and cell size in phytoplankton.

Trade-offs among functional traits are essential for explaining community structure and species coexistence. While two-way trade-offs have been investigated in many systems, higher-dimensional trade-offs remain largely hypothetical. Here we demonstrate a three-way trade-off between cell size and competitive abilities for nitrogen and phosphorus in marine and freshwater phytoplankton. At a given cell size, competitive abilities for N and P are negatively correlated, but as cell size increases, competitive ability decreases for both nutrients. The relative importance of the two trade-off axes appears to be environment dependent, suggesting different selective pressures: freshwater phytoplankton separate more along the N vs. P competition axis, and marine phytoplankton separate more along the nutrient competition vs. cell size axis. Our results demonstrate the multidimensional nature of key trade-offs among traits and suggest that such trade-offs may drive species interactions and structure ecological communities.

The vertical distribution of phytoplankton in stratified water columns.

What determines the vertical distribution of phytoplankton in different aquatic environments remains an open question. To address this question, we develop a model to explore how phytoplankton respond through growth and movement to opposing resource gradients and different mixing conditions. We assume stratification creates a well-mixed surface layer on top of a poorly mixed deep layer and nutrients are supplied from multiple depth-dependent sources. Intraspecific competition leads to a unique strategic equilibrium for phytoplankton, which allows us to classify the distinct vertical distributions that can exist. Biomass can occur as a benthic layer (BL), a deep chlorophyll maximum (DCM), or in the mixed layer (ML), or as a combination of BL+ML or DCM+ML. The ML biomass can be limited by nutrients, light, or both. We predict how the vertical distribution, relative resource limitation, and biomass of phytoplankton will change across environmental gradients. We parameterized our model to represent potentially light and phosphorus limited freshwater lakes, but the model is applicable to a broad range of vertically stratified systems. Increasing nutrient input from the sediments or to the mixed layer increases light limitation, shifts phytoplankton towards the surface, and increases total biomass. Increasing background light attenuation increases light limitation, shifts the phytoplankton towards the surface, and generally decreases total biomass. Increasing mixed layer depth increases, decreases, or has no effect on light limitation and total biomass. Our model is able to replicate the diverse vertical distributions observed in nature and explain what underlying mechanisms drive these distributions.

Optimal nitrogen-to-phosphorus stoichiometry of phytoplankton.

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.