This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

A framework for modelling thermal load sensitivity across life
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Abstract
Forecasts of vulnerability to climate warming require an integrative understanding of how species are exposed to, are damaged by, and recover from thermal stress in natural environments. The sensitivity of species to temperature depends on the frequency, duration, and magnitude of thermal stress. Thus, there is a generally recognised need to move beyond physiological metrics based solely on critical thermal limits and integrate them with natural heat exposure regimes. Here we propose the Thermal Load Sensitivity (TLS) framework, which integrates biophysical principles for quantifying exposure with physiological principles of the dynamics of damage and repair processes in driving sublethal impacts on organisms. Building upon the established Thermal Death Time (TDT) model, which integrates both the magnitude and duration of stress, the TLS framework attempts to disentangle accumulation of damage and subsequent repair processes that alter responses to thermal stress. With the aid of case studies and reproducible simulation examples, we discuss how the TLS framework can be applied to enhance our understanding of the ecology and evolution of heat stress responses. These include assessing thermal sensitivity across diverse taxonomic groups, throughout ontogeny, and for modular organisms, as well as integrating additional stressors in combination with temperature. We identify critical research opportunities, knowledge gaps, and new ways of integrating physiological measures of thermal sensitivity to improve forecasts of thermal vulnerability.
DOI
https://doi.org/10.32942/X23M0R
Subjects
Ecology and Evolutionary Biology, Integrative Biology, Life Sciences, Physiology, Systems and Integrative Physiology Life Sciences
Keywords
critical thermal limits, Heat load, Thermal Ecology, thermal fertility limits, Thermal sensitivity, Thermal tolerance, thermal vulnerability
Dates
Published: 2025-06-01 07:23
Last Updated: 2025-06-01 07:23
License
CC-BY Attribution-NonCommercial-ShareAlike 4.0 International
Additional Metadata
Conflict of interest statement:
None
Data and Code Availability Statement:
Data and analytical code associated with this preprint are publicly available at:
Language:
English
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