Temperature-dependence of resource requirements in phytoplankton. A Meta-Analysis.

Resource requirements determine species competition and shape community dynamics. Under climate change, changes in resource availability will often coincide with warming; thus, understanding how temperature affects resource requirements is crucial for predicting future ecosystems. Tests of Tilman’s Resource Competition Theory have demonstrated that minimum resource-requirements, or R*s, are good predictors of the outcome of resource competition in phytoplankton. In our study, we collected data from 71 experimental studies on phytoplankton, encompassing 133 species, to investigate whether general rules exist regarding how temperature modulates resource requirements in phytoplankton. For the resources light, nitrogen and phosphorus, we estimated parameters of the Monod curve, which describes how growth rates vary as a function of resource availability: the maximum specific growth rate (µmax), half-saturation constant (Ks), and R*. We fit the Monod curves using Bayesian methods, and tested how these parameters respond to rising temperature. We further compared these parameters across taxonomic groups, and tested how they varywith cell size. All three parameters varied in response to a temperature increase, but the direction of the response to temperature varied between the parameters. The parameters R* and Ks most often followed a U-shaped or negative response to temperature (depending on the resource type), while µmax most often showed a unimodal or positive relationship to temperature. We also describe important taxonomic and size-based differences in Monod parameters. Specifically, across all species µmax varied unimodally, the half-saturation constant increased linearly, and R* showed a U-shaped response to cell size. Our results demonstrate that resource use and requirements are highly temperature-dependent and that considering both drivers together, temperature and resources, is fundamental to explaining phytoplankton dynamics. Our results represent the most comprehensive data compilation of temperature-dependent resource requirements to-date, and such data compilations may enable mechanistic predictions of how plankton communities may respond to climate changein the future.