Abstract

Temperature tolerance is critical for defining the fundamental niche of ectotherms and researchers classically use either static (exposure to a constant temperature) or dynamic (ramping temperature) assays to assess tolerance. The use of different methods complicates comparison between studies and here we present a mathematical model (and R-scripts) to reconcile thermal tolerance measures obtained from static and dynamic assays. Our model uses input data from several static or dynamic experiments and is based on the well-supported assumption that thermal injury accumulation rate increases exponentially with temperature (known as a thermal death time curve). The model also assumes thermal stress at different temperatures to be additive and using experiments with Drosophila melanogaster, we validate these central assumptions by demonstrating that heat injury attained at different heat stress intensities and durations is additive. In a separate experiment we demonstrate that our model can accurately describe injury accumulation during fluctuating temperature stress and further we validate the model by successfully converting literature data of ectotherm heat tolerance (both static and dynamic assays) to a single, comparable metric (the temperature tolerated for 1 h). The model presented here has many promising applications for the analysis of ectotherm thermal tolerance and we also discuss potential pitfalls that should be considered and avoided using this model.

Highlights

  • IntroductionTemperature tolerance is critical for defining the fundamental niche of ectotherms and researchers classically use either static (exposure to a constant temperature) or dynamic (ramping temperature) assays to assess tolerance

  • Temperature tolerance is critical for defining the fundamental niche of ectotherms and researchers classically use either static or dynamic assays to assess tolerance

  • The thermal death time curve usually employs death as the tolerance assessment endpoint, but here we use the time of coma onset, a different endpoint that is closely related to mortality at high ­temperatures[29,30,31]

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Summary

Introduction

Temperature tolerance is critical for defining the fundamental niche of ectotherms and researchers classically use either static (exposure to a constant temperature) or dynamic (ramping temperature) assays to assess tolerance. We expand this TDT curve analysis further and present a theoretical and mathematical framework that allows researchers to directly compare thermal tolerance measurements obtained during constant and dynamic experiments. This model (and associated R-scripts) allows researchers to convert assessments of tolerance from static to dynamic assays. The TDT curve describes thermal tolerance of a species/population using the slope of the relation between assay temperature and l­og10(tcoma) and a point on the line (here we use s­ CTmax (1 h) which is the temperature causing heat coma after a 1-h exposure) (Fig. 1B). The TDT parameters from the linear regression can be used to estimate the exposure duration ­(tcoma) tolerated at a specific temperature or to calculate the maximal static temperature (­ sCTmax) that can be tolerated for a specific duration (but see below and associated R-script for details)

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