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Updated: Apr 11, 2026

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Field-Based Thermal Physiology Assay: Cold Shock Recovery under Ambient Conditions
Published on: March 9, 2021
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Thermoregulation in endotherms: physiological principles and ecological consequences
Enrico L Rezende1, Leonardo D Bacigalupe2
1Department of Life Sciences, University of Roehampton, Holybourne Avenue, London, SW15 4JD, UK. enrico.rezende@roehampton.ac.uk.
Summary
A thermoregulatory polygon, based on Newton's law of cooling, offers a new model for understanding metabolic rates in endotherms. This framework helps predict how climate change impacts animal survival and reproduction.
Area of Science:
- Physiological Ecology
- Thermoregulation Biology
- Climate Change Ecology
Background:
- Newton's law of cooling has long described metabolic rate (MR) variation with ambient temperature (T a) in endotherms.
- Existing models often use a U-shaped curve, primarily for resting metabolic rates.
Purpose of the Study:
- To explore theoretical consequences of Newton's law of cooling for thermoregulation.
- To introduce the thermoregulatory polygon as a framework for endotherm responses.
- To expand the understanding of thermoregulation beyond resting states.
Main Methods:
- Theoretical exploration of Newton's law of cooling.
- Development of the thermoregulatory polygon concept.
- Application of the framework to ecological and evolutionary questions.
Main Results:
- The thermoregulatory polygon defines the equilibrium between heat production and dissipation, indicating thermoregulatory possibility.
- This polygon integrates activity, behavior, and environmental factors impacting energy balance.
- The framework aids in studying limits to thermoregulation, allometry, and thermal insulation.
Conclusions:
- Thermoregulatory polygons offer a powerful, predictive tool for understanding ecological impacts of thermoregulation.
- This approach can elucidate constraints on fitness traits (survival, reproduction) and species responses to climate change.
- Formal mechanistic models are crucial for advancing physiological ecology and predicting climate change effects.
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