Phytoplankton competition and resilience under fluctuating temperature.

Environmental variability is an inherent feature of natural systems which complicates predictions of species interactions. Primarily, the complexity in predicting the response of organisms to environmental fluctuations is in part because species' responses to abiotic factors are non-linear, even in stable conditions. Temperature exerts a major control over phytoplankton growth and physiology, yet the influence of thermal fluctuations on growth and competition dynamics is largely unknown.

Rare diseases and space health: optimizing synergies from scientific questions to care.

Knowledge transfer among research disciplines can lead to substantial research progress. At first glance, astronaut health and rare diseases may be seen as having little common ground for such an exchange. However, deleterious health conditions linked to human space exploration may well be considered as a narrow sub-category of rare diseases.

High predictability of direct competition between marine diatoms under different temperatures and nutrient states.

The distribution of marine phytoplankton will shift alongside changes in marine environments, leading to altered species frequencies and community composition. An understanding of the response of mixed populations to abiotic changes is required to adequately predict how environmental change may affect the future composition of phytoplankton communities. This study investigated the growth and competitive ability of two marine diatoms, and , along a temperature gradient (9-35°C) spanning the thermal niches of both species under both high-nitrogen nutrient-replete and low-nitrogen nutrient-limited conditions.

Predictable ecological response to rising CO of a community of marine phytoplankton.

Rising atmospheric CO and ocean acidification are fundamentally altering conditions for life of all marine organisms, including phytoplankton. Differences in CO related physiology between major phytoplankton taxa lead to differences in their ability to take up and utilize CO . These differences may cause predictable shifts in the composition of marine phytoplankton communities in response to rising atmospheric CO .

Predictions of response to temperature are contingent on model choice and data quality.

The equations used to account for the temperature dependence of biological processes, including growth and metabolic rates, are the foundations of our predictions of how global biogeochemistry and biogeography change in response to global climate change. We review and test the use of 12 equations used to model the temperature dependence of biological processes across the full range of their temperature response, including supra- and suboptimal temperatures. We focus on fitting these equations to thermal response curves for phytoplankton growth but also tested the equations on a variety of traits across a wide diversity of organisms.