Two ecological frameworks have been used to explain multitrophic interactions, but rarely in combination: (i) ecological stoichiometry (ES), explaining consumption rates in response to consumers' demand and prey's nutrient content; and (ii) metabolic theory of ecology (MTE), proposing that temperature and body mass affect metabolic rates, growth and consumption rates. Here we combined both, ES and MTE to investigate interactive effects of phytoplankton prey stoichiometry, temperature and zooplankton consumer body mass on consumer grazing rates and production in a microcosm experiment. A simple model integrating parameters from both frameworks was used to predict interactive effects of temperature and nutrient conditions on consumer performance. Overall, model predictions reflected experimental patterns well: consumer grazing rates and production increased with temperature, as could be expected based on MTE. With decreasing algal food quality, grazing rates increased due to compensatory feeding, while consumer growth rates and final biovolume decreased. Nutrient effects on consumer biovolume increased with increasing temperature, while nutrient effects on grazing rates decreased. Highly interactive effects of temperature and nutrient supply indicate that combining the frameworks of ES and MTE is highly important to enhance our ability to predict ecosystem functioning in the context of global change.

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The metaecosystem framework has been proposed to conceptualize the interactive effects of dispersal and resource flows on the structure and functioning of communities in a heterogeneous environment. Here, we model a two-patch metaecosystem where two species with a trade-off in resource requirements compete for two limiting resources-generalizing the so-called gradostat experimental setup. We study the competition outcome in dependence of resource heterogeneity and between-patch diffusion for different combinations of resource supply ratios. Our numerical simulations show that community composition and local and regional diversity are determined by the interplay of resource heterogeneity, resource supply stoichiometry, and diffusion rate. High resource heterogeneity increases regional diversity, with species coexisting due to spatial segregation, whereas low resource heterogeneity favors local diversity, as species coexist mainly by local resource partitioning. Regional diversity averaged across a gradient of resource ratios decreases monotonically with diffusion rate, while local diversity follows a unimodal dependency. However, these dependencies become bimodal for high resource heterogeneity because various bistable states occur at intermediate diffusion rates. We identify three kinds of bistable states with species priority effect: (i) bistability between the dominance of one or the other competitor, (ii) bistability between one species dominance or species coexistence, and (iii) two alternative coexistence regimes differing in species-relative abundances. Most bistable states appear at high resource levels when biomass fluxes strongly interact with resource fluxes. Our analysis provides new insights for the potential effects of metaecosystem dynamics on biodiversity patterns.

We develop a trait-based model founded on the hypothesis that biological systems evolve and organize to maximize entropy production by dissipating chemical and electromagnetic free energy over longer time scales than abiotic processes by implementing temporal strategies. A marine food web consisting of phytoplankton, bacteria, and consumer functional groups is used to explore how temporal strategies, or the lack thereof, change entropy production in a shallow pond that receives a continuous flow of reduced organic carbon plus inorganic nitrogen and illumination from solar radiation with diel and seasonal dynamics. Results show that a temporal strategy that employs an explicit circadian clock produces more entropy than a passive strategy that uses internal carbon storage or a balanced growth strategy that requires phytoplankton to grow with fixed stoichiometry. When the community is forced to operate at high specific growth rates near 2 d−1, the optimization-guided model selects for phytoplankton ecotypes that exhibit complementary for winter versus summer environmental conditions to increase entropy production. We also present a new type of trait-based modeling where trait values are determined by maximizing entropy production rather than by random selection.

Light, essential for photosynthesis, is present in two periodic cycles in nature: seasonal and diel. Although seasonality of light is typically resolved in ocean ecosystem and biogeochemistry models because of its significance for seasonal succession and biogeography of phytoplankton, the diel light cycle is generally not resolved. Here we use a three-dimensional global ocean model and compare high temporal resolution simulations with and without diel light cycles. The model simulates 15 phytoplankton types of different cell size, encompassing two broad ecological strategies: small cells with high nutrient affinity (gleaners) and larger cells with high maximal growth rate (opportunists). Both are grazed by zooplankton and limited by nitrogen, phosphorus and iron. Simulations show that diel cycles of light induce diel cycles in phytoplankton populations and limiting nutrients in the global ocean. Diel nutrient cycles are associated with higher concentration of limiting nutrients by up to 200% at low latitudes (-40 to 40), a process that increases opportunists biomass by up to 50%. Size classes with the highest maximal growth rates from both gleaner and opportunist groups are favored the most by diel light cycles. This mechanism weakens as latitude increases because the effects of the seasonal cycle dominate over those of the diel cycle. The present work shows that resource competition under diel light cycles has a significant impact on phytoplankton biogeography, indicating the necessity of resolving diel processes in global ocean models.