2025/10/22 by Jean‐François Arnoldi, Andrew L. Jackson, Ignacio Peralta‐Maraver +1 · 1 voice · 27 citations
Biochemistry, Genetics and Molecular Biology · Environmental Science · #Climate change #Context (archaeology) #Exponential function #Exponential growth #Insect and Arachnid Ecology and Behavior #Physiological and biochemical adaptations #Population #Scaling #Species Distribution and Climate Change #Thermal
paper · doi:10.1073/pnas.2513099122
published in Proceedings of the National Academy of Sciences 122(43), e2513099122 (National Academy of Sciences)
openalex publication_date 2025/10/22 · openalex created_date 2025/10/24 · openalex updated_date 2026/07/29
Temperature has strong impacts on all biological and ecological processes, and thermal performance curves (TPCs) have been employed recurrently to assess them. TPCs almost always take a particular asymmetric shape across the biological hierarchy, with many different competing mechanisms and models doing a similarly good job of trying to explain the TPC phenomenon. Here, we reveal that the ubiquitous exponential scaling of biological processes with temperature creates a mechanistic tendency for TPC data and models to collapse onto a single curve (which we call the Universal TPC, UTPC), explaining mathematically why biological systems respond to temperature in such a consistent way. We illustrate that many seemingly different TPCs actually approximate rescaled versions of the same curve, even when thermal performance estimates vary widely across organisms, systems, and contexts. We demonstrate remarkable UTPC collapse across the tree of life, with diverse datasets spanning microbes to vertebrates, and individual physiology to population growth. UTPC phenomena also provide a strong theoretical basis for predicting performance of warm-adapted organisms will be more sensitive to- and less tolerant of- temperature fluctuations; an important consideration in the context of climate change.