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Real versus Artificial Variation in the Thermal Sensitivity of Biological Traits

Whether the thermal sensitivity of an organism's traits follows the simple Boltzmann-Arrhenius model remains a contentious issue that centers around consideration of its operational temperature range and whether the sensitivity corresponds to one or a few underlying rate-limiting enzymes. Resolving this issue is crucial, because mechanistic models for temperature dependence of traits are required to predict the biological effects of climate change. Here, by combining theory with data on 1,085 thermal responses from a wide range of traits and organisms, we show that substantial variation in thermal sensitivity (activation energy) estimates can arise simply because of variation in the range of measured temperatures. Furthermore, when thermal responses deviate systematically from the Boltzmann-Arrhenius model, variation in measured temperature ranges across studies can bias estimated activation energy distributions toward higher mean, median, variance, and skewness. Remarkably, this bias alone can yield activation energies that encompass the range expected from biochemical reactions (from ~0.2 to 1.2 eV), making it difficult to establish whether a single activation energy appropriately captures thermal sensitivity. We provide guidelines and a simple equation for partially correcting for such artifacts. Our results have important implications for understanding the mechanistic basis of thermal responses of biological traits and for accurately modeling effects of variation in thermal sensitivity on responses of individuals, populations, and ecological communities to changing climatic temperatures.
- Christopher Newport University United States
- National Great Rivers Research and Education Center United States
- Department of Life Sciences Imperial College London United Kingdom
- Santa Fe Institute United States
- Department of Life Sciences Imperial College London United Kingdom
sampling, METABOLIC THEORY, Climate Change, Environmental Sciences & Ecology, 612, thermal sensitivity, Bacterial Physiological Phenomena, Models, Biological, Affordable and Clean Energy, traits, Species Specificity, Models, ACCLIMATION, ARRHENIUS PLOTS, Animals, RATES, Plant Physiological Phenomena, Evolutionary Biology, Science & Technology, CLIMATE-CHANGE, Ecology, thermal physiology, Fungi, Temperature, temperature, UNIVERSAL TEMPERATURE-DEPENDENCE, GROWTH-RATE, Biological Sciences, 06 Biological Sciences, Biological, Biological sciences, SIZE, Phenotype, activation energy, Phytoplankton, BIODIVERSITY, Energy Metabolism, Life Sciences & Biomedicine, RESPONSES
sampling, METABOLIC THEORY, Climate Change, Environmental Sciences & Ecology, 612, thermal sensitivity, Bacterial Physiological Phenomena, Models, Biological, Affordable and Clean Energy, traits, Species Specificity, Models, ACCLIMATION, ARRHENIUS PLOTS, Animals, RATES, Plant Physiological Phenomena, Evolutionary Biology, Science & Technology, CLIMATE-CHANGE, Ecology, thermal physiology, Fungi, Temperature, temperature, UNIVERSAL TEMPERATURE-DEPENDENCE, GROWTH-RATE, Biological Sciences, 06 Biological Sciences, Biological, Biological sciences, SIZE, Phenotype, activation energy, Phytoplankton, BIODIVERSITY, Energy Metabolism, Life Sciences & Biomedicine, RESPONSES
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).68 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
