PS 32-202 - Nutrient storage links past thermal exposure to current performance in phytoplankton populations

Abstract: The ecology of organisms depends strongly on temperature and resources and resolving the nature of these dependencies is critical to developing a deep and predictive understanding of ecology. The aim of this project was to present a temperature-dependent Droop model that allows a potential mechanism for explaining phenotypic memory in freshwater green algae. This Droop model allows explicitly considering the consequences of uptake-limited versus assimilated-limited processes that occur at various environmental temperatures. To evaluate features of his model, we generated patterns of phenotypic memory on the patterns of growth rates observed by four different species of green algae in response to temperature perturbations. Populations of Chlamydomonas reinhardtii, Auxenochlorella protothecoides, Cryptomonas ovata, and Chlorella vulgaris were acclimated to 9 temperatures ranging from 14.8 and 39.9°C for a period of two weeks. Following this initial acclimation, we performed crosses among thermal environments (5 unique treatments and 1 control where the perturbed temperature matches the previous environment). For each temperature for each cross, we included three replicates (N=162 per species), ultimately averaging across replicates to estimate growth rate over 36 hours. We also compiled existing temperature-specific growth rates from past and current environments for the cyanobacteria Microcystis aeruginosa and the diatom Phaeodactylum tricornutum.

Our results indicate that the temperature-dependent Droop model accurately anticipates the growth rate of all available phytoplankton species in novel thermal conditions. The model accurately described the relationship between acclimation temperature and the experimental environment (corresponding to the cross temperature described above) that we saw in our data. For this data, R2 values between measured and anticipated values ranged from 0.68 to 0.93 depending on the species. One of the mechanisms that drive the agreement between theory and observations is that nutrient storage quotas are a temperature-dependent process that is affected by acclimation. The model suggests general constraints on the shape of performance in response to previous temperature perturbations – notably, previous exposure to cool temperatures boosts performance at warmer temperatures, as cold acclimation yields excess quotas that fuels growth during subsequent warm exposure. This model thus contextualizes further why cold-acclimated species are better suited to survive in a wider range of temperatures than hot-acclimated populations. Given the taxonomic range of phytoplankton taxa represented in this study, this understanding may be helpful to make more accurate predictions on how phytoplankton population dynamics will be affected by temperature perturbations amidst global climate change.