Ecology | Evolutionary Biology | Published in PNAS, October 2025
Trinity College Dublin | University of Granada | CNRS France | University College Dublin
From the bacteria dividing in a hot spring in Yellowstone to the great white shark patrolling the California coast. From the sprinting cheetah on the Serengeti to the moss growing on a Scottish hillside. From the cell cultures in a laboratory incubator to the plankton blooming in the Arctic Ocean.
Every single one of these living things, separated by billions of years of evolution, living in wildly different habitats, built from radically different body plans, operating across a span of sizes from a single cell to fifty tonnes of whale, obeys the same mathematical law when it comes to temperature.
The law in one line
Performance rises with warmth, reaches a peak, and then collapses sharply when temperature gets too high.
Performance rises with warmth. Reaches a peak. Then falls off a cliff.
Not approximately. Not loosely. Precisely. When you normalize the data, when you adjust for each organism’s own optimal temperature and performance peak, the curves from thousands of different species collapse onto a single line, the same line, the same shape, described by the same equation.
Scientists at Trinity College Dublin, working with collaborators in Spain, France, and Ireland, have published what may be one of the most sweeping empirical demonstrations in the history of biology. Across 30,000 performance measurements from 2,710 experiments spanning 2,700 species across seven kingdoms and 39 phyla, they found one curve to rule them all.
They call it the Universal Thermal Performance Curve, or UTPC.
And they say it shackles evolution. No species studied so far has escaped it.
What a Universal Law in Biology Even Means
Physics has universal laws. The law of gravity. The laws of thermodynamics. These are mathematical relationships that hold everywhere, without exception, regardless of context. A rock dropped on Earth and a rock dropped on Mars both accelerate toward the ground in a manner precisely described by the same equations.
Biology has almost never been like this. Life is messy. Evolution is opportunistic. The history of biological research is full of patterns that seem universal until someone finds an exception. General rules exist, and some of them are genuinely powerful. The relationship between an animal’s metabolic rate and its body size follows a predictable mathematical scaling, for example. But biology has not had laws in the way physics has laws. There are too many organisms, too many environments, too many evolutionary solutions to the same problem.
The UTPC is a challenge to that assumption. Not a definitive refutation, the authors are careful about their language, but a serious, data-rich, mathematically grounded challenge.
Why this is extraordinary
In biology, universal patterns usually break somewhere. The UTPC appears across bacteria, plants, reptiles, fish, insects, and more.
“Across thousands of species and almost all groups of life including bacteria, plants, reptiles, fish and insects,” said Professor Andrew Jackson, co-author and Professor of Zoology at Trinity’s School of Natural Sciences, “the shape of the curve that describes how performance changes with temperature is very similar.”
Very similar. Across every kingdom of life. From the simplest single-celled bacterium to the most complex vertebrate.
That is not a modest claim.
The Data Behind the Claim
To understand what makes this finding extraordinary, you first need to understand how much data went into it and where it came from.
Biologists have been measuring how temperature affects biological performance for over a century. A lizard running on a treadmill at different temperatures. Bacteria dividing faster or slower as the incubator gets warmer. A plant’s photosynthesis rate at different ambient temperatures. A fish’s swimming speed in water of different temperatures. A shark’s metabolic rate as the ocean heats up.
Each of these measurements produces what is called a thermal performance curve, or TPC: a graph with temperature on the horizontal axis and some measure of biological performance on the vertical axis. These curves have been published by the thousands across the scientific literature, each one telling the story of one species, one trait, one set of experimental conditions.
Dataset scale
Around 30,000 performance measurements from 2,710 experiments, 2,700 species, seven kingdoms, and 39 phyla.
For this study, the Trinity College Dublin team, led by Professor Nicholas Payne and Professor Andrew Jackson, compiled what is likely the largest such dataset ever assembled for this purpose: approximately 30,000 performance measurements derived from seven kingdoms, 39 phyla, and 2,710 separate experiments. The data span almost every major branch of the animal and plant world. Performance is represented by diverse rates including metabolism, individual growth, foraging intensity, voluntary activity, and population growth.
Bacteria and plankton. Trees and insects. Fish, reptiles, birds, and mammals. Sharks swimming in the ocean. Lizards running on treadmills. Cell division rates in bacteria. Growth rates in crop plants. All of it.
Then the team applied a mathematical normalization: they rescaled each curve so that each organism’s own optimal temperature, the temperature at which it performs best, became the reference point. They rescaled each curve’s peak performance to a common value. And they asked: when you strip away the differences in absolute temperature and absolute performance, does the shape of the curve remain the same across all these different organisms?
It did. Remarkably, almost perfectly. When the data were normalized relative to each organism’s own optimal temperature and peak performance, the entire dataset collapsed onto a single curve.
Biological performance across the tree of life collapses onto the Universal Thermal Performance Curve.
What the Curve Actually Looks Like
The UTPC has a distinctive and asymmetric shape that is worth describing precisely, because its asymmetry is one of its most important features.
On the left side of the curve, below the optimal temperature, performance rises gradually and exponentially with increasing warmth. An organism operating at 5 degrees below its optimum performs considerably worse than at its optimum, but not catastrophically so. There is a gentle, steady slope upward.
On the right side of the curve, above the optimal temperature, the story changes completely. Performance does not decline gradually in a mirror image of the ascent. It falls sharply. Far faster than it rose. The descent is steep, and it ends in physiological failure or death.
The dangerous side of the curve
Above the optimum, performance does not gently decline. It drops rapidly, which makes overheating biologically dangerous.
This asymmetry is not random variation. It is a consistent, mathematically describable feature of the curve across all 2,710 experiments in the dataset. The UTPC shows that as all organisms warm, performance slowly increases until they reach an optimum where performance is greatest, but then with further warming, performance quickly declines. The rapid decline above optimum temperatures means overheating can be dangerous, risking physiological failure or even death.
In practical terms, what this means is that the safe operating window for a living organism is not a symmetric range around its optimal temperature. Organisms can survive and function reasonably well at temperatures somewhat below their optimum. But above the optimum, the margin for error shrinks dramatically. A few degrees above the optimum can be as catastrophic as many degrees below it.
Think of it like driving near the edge of a cliff. You have plenty of room on your left. On the right, the drop is immediate.
Why Does This Curve Exist? The Biochemistry Underneath
A mathematical pattern this consistent and this universal has to have a mechanistic explanation. The curve is not an accident or a coincidence. Something in the fundamental chemistry of life is producing it.
The answer lies in two competing processes that operate inside every living cell, and in the physics of how molecular reactions respond to temperature.
The first process is straightforward: heat accelerates chemistry. At the molecular level, higher temperatures mean more kinetic energy, which means molecules collide more frequently and with more force, which means chemical reactions happen faster. This relationship is quantified by a 19th-century equation called the Arrhenius equation, which describes how the rate of a chemical reaction increases exponentially with temperature. In biology, where virtually every process depends on enzyme-catalyzed chemical reactions, this means that warming generally speeds things up: metabolism runs faster, muscles contract more quickly, cells divide more rapidly.
Biochemical reason
Heat speeds enzyme reactions up to a point. Beyond that point, heat damages the protein machinery itself.
This is the left side of the UTPC. The rising slope is the Arrhenius relationship playing out in biological tissues.
The second process is more complex and, ultimately, more limiting: heat also destroys biological molecules. Proteins are held in their three-dimensional shapes by weak chemical forces: hydrogen bonds, hydrophobic interactions, van der Waals forces. These forces are strong enough to maintain protein structure at moderate temperatures, but they are not infinitely strong. As temperature rises above a threshold, the thermal energy in the environment begins to overwhelm these forces. Proteins lose their precise three-dimensional structure, a process called denaturation. And an enzyme that has lost its shape has lost its function.
This is the right side of the UTPC. The sharp drop-off above the optimum temperature reflects the point at which thermal denaturation begins to outpace the benefit of accelerated reaction rates. The increase in enzymatic rates with temperature up to an optimum temperature is widely attributed to Arrhenius behavior, with the decrease in enzymatic rates above the optimum ascribed to protein denaturation and related processes.
The asymmetry of the curve, the fact that performance falls much faster above the optimum than it rises below it, reflects the asymmetry of these two processes. Warming up toward the optimum gives you more reaction speed. Warming above the optimum triggers structural collapse of the molecular machinery that makes life work. Collapse is faster than accumulation.
This biochemical explanation is not new. What is new is the demonstration that this same basic physics, enzymes accelerating up to an optimum and then denaturing above it, produces the same curve shape across the entire tree of life, from organisms whose optimal temperatures are below freezing to organisms that thrive in near-boiling water.
Why It Shackles Evolution
Here is the phrase from the Trinity College Dublin press release that made the post that brought you here go viral: the UTPC “shackles evolution.”
What does that actually mean in biological terms?
Evolution by natural selection is, among other things, the process by which organisms accumulate adaptations that allow them to function better in their environments. If a population of lizards lives in a warming environment, natural selection should, in principle, favor individuals whose enzymes work better at higher temperatures. Over generations, the population should evolve toward a higher optimal temperature.
This happens. It is documented. Species can and do evolve different optimal temperatures when they live in different thermal environments. Bacteria isolated from geothermal vents have higher optimal temperatures than bacteria from temperate soils. Arctic fish have cold-adapted enzymes. Tropical plants have higher thermal optima than alpine plants.
Evolution can shift the curve, but may not escape it
Species can evolve different optimal temperatures, but the same asymmetric curve shape appears to remain.
But the UTPC suggests that this evolutionary freedom has a ceiling. Species can slide along the temperature axis, shifting their optimal temperature up or down through evolution. What they cannot do, or at least what none of the 2,710 experiments in this dataset shows any species having done, is escape the shape of the curve. They cannot evolve a curve that does not decline sharply above the optimum. They cannot evolve a curve that rises more steeply than the Arrhenius relationship allows. The shape itself appears to be fixed.
The UTPC essentially shackles evolution, as no species seem to have broken free from the constraints it imposes on how temperature affects performance.
This matters because the shape constraint has consequences. The rapid decline above the optimum means that organisms living near their thermal maximum are vulnerable to even small temperature increases. They cannot simply adapt their way out of this asymmetric risk by evolving a flatter, more symmetric response curve. The biochemistry of proteins imposes a structural limit on what evolution can do.
Professor Jackson explained it this way: “Once things get too hot, performance tails off rapidly.” The implication he drew from this was pointed: “Species may be more constrained than feared when it comes to their ability to adapt to global climate change, given that in most places temperatures are rising.”
From Lizards to Bacteria: What Seven Kingdoms of Data Look Like Converging
The breadth of the dataset deserves emphasis, because it is what separates this finding from the many previous studies that found similar patterns in narrower datasets.
From lizards running on a treadmill, to sharks swimming in the ocean, and cell division rates in bacteria, the universal thermal performance curve applies to all species and dictates how they respond to temperature change.
Lizards are ectotherms: animals whose body temperature is determined by their environment. Their performance is directly tied to ambient temperature in ways that endotherms, warm-blooded animals like mammals and birds, partially buffer through internal heat generation. Including both in the same dataset and finding the same curve shape is significant, because it suggests the constraint operates at the level of cellular biochemistry rather than at the level of thermoregulatory physiology.
Bacteria are single-celled organisms with no thermoregulation at all. Their optimal temperatures span an enormous range: from near-freezing for psychrophilic species in polar oceans to above 80 degrees Celsius for thermophilic species in hot springs. Yet when normalized, their thermal performance curves follow the same UTPC shape.
Plants do not move. They cannot behaviorally thermoregulate. Their photosynthesis rates, growth rates, and metabolic rates across temperature all follow the same curve shape.
Across life
The curve appears deeper than lifestyle, body plan, habitat, or kingdom. It seems written into cellular biochemistry.
Seven kingdoms. 39 phyla. The curve does not care about the complexity of the organism or the ecological niche it occupies. It is written into the biochemistry of life at a level deeper than the differences between kingdoms.
The Climate Change Implication: A Hard Limit
The timing of this discovery, published in October 2025, is not coincidental. Climate change is the defining environmental challenge of this century, and one of its most consequential and least understood aspects is how living organisms will respond to sustained warming.
There are optimistic scenarios and pessimistic ones. The optimistic view is that evolution has produced organisms adapted to a wide range of temperatures throughout Earth’s history, and that given enough time and selection pressure, populations can adapt to warming environments. The pessimistic view is that the rate of anthropogenic warming is faster than evolutionary adaptation can respond to, and that many species will simply overheat before adaptation can save them.
The UTPC adds a structural dimension to the pessimistic scenario that is independent of the rate of warming. Even given unlimited time for adaptation, the shape of the performance curve appears to constrain what evolution can achieve. Species can evolve higher optimal temperatures. They cannot escape the asymmetric curve that makes overheating so dangerous and so fast.
Climate implication
Small warming can push organisms past their optimum and onto the steep decline side of the curve.
By tying all life to the same mathematical arc, the work clarifies how far the planet can heat before nature reaches hard limits.
The practical implication is concerning. If most of Earth’s species are operating near their thermal optimum in their current environments, as many appear to be, then warming by even a degree or two does not simply slide them to a new, slightly suboptimal position on the left side of their curve. It pushes them past their optimum and onto the steep right-side decline. And on the right side of the UTPC, performance does not gently decrease. It collapses.
This is not speculation. The curve shape makes it mathematically explicit.
A New Practical Tool: Predicting Thermal Responses From Two Numbers
Beyond the fundamental biological insight, the UTPC offers something immediately practical for researchers and ecologists: a powerful predictive shortcut.
When scientists want to understand how a species will respond to temperature changes, they currently need to measure its thermal performance curve directly, which requires running experiments across a range of temperatures. This is time-consuming and expensive, and it is not feasible for the thousands of species whose thermal responses are unknown.
Practical shortcut
If the curve shape is universal, scientists may estimate a species’ full thermal response from just a few key measurements.
The UTPC changes this calculation. If the shape of the curve is universal and can be described by a single mathematical equation, then knowing just two parameters for any given organism, its optimal temperature and its critical upper temperature at which performance collapses, is enough to reconstruct its entire thermal performance curve with high confidence.
A potentially powerful outcome of the UTPC framework is that it enables estimating the decline phase of performance beyond the thermal optimum by only measuring some components; if we can estimate just two parameters from an organism’s empirically measured TPC, we have a strong prior for its entire temperature response.
For conservation biology, this is significant. Predicting which species are most at risk from warming, which habitats will become thermally unsuitable, and how quickly ecosystem-level processes will change with increasing temperatures, all of these become more tractable if you can reliably extrapolate from partial measurements to complete thermal response profiles.
For crop science and food security, where the thermal performance of major staple crops determines agricultural yields under changing conditions, the UTPC provides a common framework for predicting and potentially improving temperature tolerance.
The lead researcher, Ignacio Peralta-Maraver of the University of Granada, said: “This model could become a new standard in the ecology and physiology of global warming.”
What the Paper Does Not Claim
Scientific integrity requires being precise about what the UTPC is and what it is not.
The authors are explicit that the UTPC should be viewed as a null model with important limitations, not as a one-size-fits-all solution.
Important caveat
The UTPC is powerful, but it is not magic. It is a strong null model with limitations, scatter, and open questions.
First, the curve assumes that performance rises exponentially below the thermal optimum following Arrhenius kinetics. Some species show more complex patterns of increase, and in those cases the UTPC may not fit well.
Second, the collapse of data onto the UTPC is not perfect. There is scatter around the universal curve. Some organisms deviate from it in ways that may reflect genuine biological differences rather than measurement noise. Ectotherms have a limited but measurable capacity to reduce the thermodynamic influence of temperature on biological rates, and residual variation around the UTPC could reflect acclimation capacity that is worthy of future study.
Third, the UTPC is descriptive, not mechanistic. It describes what biological performance across life does when plotted against temperature. The biochemical explanations involving Arrhenius kinetics and protein denaturation are proposed mechanisms that are consistent with the curve shape, but they are not proven to be the only or the complete explanation.
Fourth, the statement that evolution is shackled by the UTPC is a strong interpretation of the finding that no species in the current dataset has escaped the curve shape. It remains possible that species exist, or could evolve, whose performance curves deviate significantly from the UTPC in ways that would not be captured by the current dataset. Whether ancestral or evolved TPCs align with the UTPC framework or exhibit significant deviations remains an open question that warrants further research.
The finding is powerful. It is also, appropriately, an opening for further inquiry rather than a closed door.
The Deep Question This Raises
Underneath all the data and the equations and the practical applications, the UTPC raises a question that is genuinely philosophical: what does it mean for a law to govern life?
Laws in physics are inevitable. The law of gravity applies to every mass in the universe not because masses choose to obey it, but because the geometry of spacetime makes any other behavior impossible. There is no way around it.
The UTPC appears to operate differently. Species can, in principle, evolve enzymes with different optimal temperatures, and they do. They can evolve behavioral strategies for thermoregulation that buffer the direct impact of environmental temperature on their tissues. They can evolve heat shock proteins that stabilize other proteins against denaturation. They can do all of this, and evolution has done all of this across billions of years of life’s history.
And yet the curve shape persists. None of it is enough to break free from the UTPC.
The deepest idea
Evolution can optimize life within chemistry. But it may not be able to rewrite the chemistry life is built from.
The most likely explanation is that the constraint is fundamental enough that no evolutionary path leads around it. The physics of protein folding, the mathematics of Arrhenius kinetics, the structural reality that the same forces that make proteins functional also make them thermally sensitive, these are not features of life that evolution can redesign. They are features of chemistry that life is built on top of. Evolution can optimize within the space the chemistry allows. It cannot change the chemistry.
If that is right, then the UTPC is not a law like a rule: it is a law like a fact. Life does not obey it. Life is made of it.
References and Attributions
Primary Source:
Arnoldi J.F., Payne N.L., Jackson A.L., Peralta-Maraver I. et al. “A universal thermal performance curve arises in biology and ecology.” Proceedings of the National Academy of Sciences, October 22, 2025; 122(43).
DOI: 10.1073/pnas.2513099122
PubMed ID: 41123997
URL: https://www.pnas.org/doi/10.1073/pnas.2513099122
Commentary on the primary paper:
Pawar S., Kontopoulos D.G. “Toward a general understanding of thermal performance curves in biology.” Proceedings of the National Academy of Sciences, December 23, 2025; 122(51): e2528528122.
DOI: 10.1073/pnas.2528528122
URL: https://www.pnas.org/doi/10.1073/pnas.2528528122
Institutional press releases:
Trinity College Dublin News and Events. “Universal thermal performance curve.” October 21, 2025.
URL: https://www.tcd.ie/news_events/articles/2025/universal-thermal-performance-curve/
EurekAlert! “What goes up must come down: scientists unearth universal thermal performance curve that shackles evolution.” October 20, 2025.
URL: https://www.eurekalert.org/news-releases/1102388
ScienceDaily. “Scientists discover a universal temperature curve that governs all life.” March 13, 2026.
URL: https://www.sciencedaily.com/releases/2026/03/260311213448.htm
Biochemical mechanism sources:
Nguyen V., Wilson C., Hoemberger M. et al. “Evolutionary drivers of thermoadaptation in enzyme catalysis.” Science, 2017; 355(6322): 289-294.
Peterson M.E., Daniel R.M., Danson M.J., Eisenthal R. “The dependence of enzyme activity on temperature: determination and validation of parameters.” Biochemical Journal, 2007; 402(2): 331-337. PMC1798444.
Ritchie M.E. “Reaction and diffusion thermodynamics explain optimal temperatures of biochemical reactions.” Scientific Reports, 2018; 8: 11105. DOI: 10.1038/s41598-018-28833-9. PMC6056565.
Lead researchers:
Prof. Nicholas Payne, School of Natural Sciences, Trinity College Dublin
Prof. Andrew Jackson, School of Natural Sciences, Trinity College Dublin
Prof. Ignacio Peralta-Maraver, Department of Ecology, University of Granada (UGR), Spain
Prof. Jean-François Arnoldi, CNRS, Montpellier, France
Coverage:
Earth.com: “Universal law found that shackles evolution across all life forms.” May 6, 2026.
URL: https://www.earth.com/news/universal-thermal-performance-curve-utpc-heat-shackles-evolution-links-all-life-forms/
Phys.org: “What goes up must come down: The universal thermal performance curve that shackles evolution.” October 20, 2025.
URL: https://phys.org/news/2025-10-universal-thermal-shackles-evolution.html
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