Thermal performance across levels of biological organization

Thermal performance curves are widely used to describe how ambient temperature impacts different attributes of ectothermic organisms, from protein function to life-history traits, and to predict the potential effects of global warming on ecological systems. Nonetheless, from an analytical standpoint, they remain primarily heuristic and few attempts have been made to develop a formal framework to characterize these curves and disentangle which factors contribute to their variation. Here we employ a nonlinear regression approach to assess if they vary systematically in shape depending on the performance proxy of choice. We compare curves at contrasting levels of organization, namely photosynthetic rates in plants ( n = 43), running speeds in lizards ( n = 51) and intrinsic rates of population increase in insects ( n = 47), and show with discriminant analyses that differences lie in a single dimension accounting for 99.1% of the variation, resulting in 75.8% of classification accuracy. Differences revolve primarily around the thermal range for elevated performance (greater than or equal to 50% of maximum performance), which is broader for photosynthetic rates (median of 26.4°C), intermediate for running speeds (19.5°C) and narrower for intrinsic rates of increase (12.5°C). We contend, confounding taxonomic factors aside, that these differences reflect contrasting levels of biological organization, and hypothesize that the thermal range for elevated performance should decrease at higher organization levels. In this scenario, instantaneous or short-term measures of performance may grossly overestimate the thermal safety margins for population growth and reproduction. Taken together, our analyses suggest that descriptors of the curve are highly correlated and respond in tandem, potentially resulting in systematic variation in shape across organization levels. Future studies should take into consideration this potential bias, address if it constitutes a general pattern and, if so, explain why and how it emerges. This article is part of the theme issue 'Physiological diversity, biodiversity patterns and global climate change: testing key hypotheses involving temperature and oxygen'.