Spatial insurance against a heatwave differs between trophic levels in experimental aquatic communities.

Climate change-related heatwaves are major threats to biodiversity and ecosystem functioning. However, our current understanding of the mechanisms governing community resistance to and recovery from extreme temperature events is still rudimentary. The spatial insurance hypothesis postulates that diverse regional species pools can buffer ecosystem functioning against local disturbances through the immigration of better-adapted taxa. Yet, experimental evidence for such predictions from multi-trophic communities and pulse-type disturbances, like heatwaves, is largely missing. We performed an experimental mesocosm study to test whether species dispersal from natural lakes prior to a simulated heatwave could increase the resistance and recovery of plankton communities. As the buffering effect of dispersal may differ among trophic groups, we independently manipulated the dispersal of organisms from lower (phytoplankton) and higher (zooplankton) trophic levels. The experimental heatwave suppressed total community biomass by having a strong negative effect on zooplankton biomass, probably due to a heat-induced increase in metabolic costs, resulting in weaker top-down control on phytoplankton. While zooplankton dispersal did not alleviate the negative heatwave effects on zooplankton biomass, phytoplankton dispersal enhanced biomass recovery at the level of primary producers, providing partial evidence for spatial insurance. The differential responses to dispersal may be linked to the much larger regional species pool of phytoplankton than of zooplankton. Our results suggest high recovery capacity of community biomass independent of dispersal. However, community composition and trophic structure remained altered due to the heatwave, implying longer-lasting changes in ecosystem functioning.

Phytoplankton Temporal Strategies Increase Entropy Production in a Marine Food Web Model.

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.

Unifying ecological stoichiometry and metabolic theory to predict production and trophic transfer in a marine planktonic food web.

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.