Limited plasticity in thermally tolerant ectotherm populations: evidence for a trade-off

Many species face extinction risks owing to climate change, and there is an urgent need to identify which species' populations will be most vulnerable. Plasticity in heat tolerance, which includes acclimation or hardening, occurs when prior exposure to a warmer temperature changes an organism's upper thermal limit. The capacity for thermal acclimation could provide protection against warming, but prior work has found few generalizable patterns to explain variation in this trait. Here, we report the results of, to our knowledge, the first meta-analysis to examine within-species variation in thermal plasticity, using results from 20 studies (19 species) that quantified thermal acclimation capacities across 78 populations. We used meta-regression to evaluate two leading hypotheses. The climate variability hypothesis predicts that populations from more thermally variable habitats will have greater plasticity, while the trade-off hypothesis predicts that populations with the lowest heat tolerance will have the greatest plasticity. Our analysis indicates strong support for the trade-off hypothesis because populations with greater thermal tolerance had reduced plasticity. These results advance our understanding of variation in populations' susceptibility to climate change and imply that populations with the highest thermal tolerance may have limited phenotypic plasticity to adjust to ongoing climate warming.

Methods
Studies which measure thermal tolerance plasticity typically collect organisms from nature and acclimate them to different temperatures for defined periods of time in the lab before measuring thermal tolerance. Important methodological considerations for these types of studies include (1) for how long and at what temperature organisms are acclimated, (2) how fast the temperature is changed, and (3) whether measurements are made on field collected or F1 individuals, given that parental conditions are known to influence thermal plasticity. To identify publications for use in our study, we followed PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines (supplemental figure S1). We searched titles, abstracts, and key words in Web of Science (Clarivate Analytics, Philadelphia, USA) using the following search string: (Thermal OR temperatures) AND (Lethal OR “Thermal tolerance” OR “Thermal limit” OR CTmax OR CTmin OR LT50 OR “freezing tolerance”) AND ("Local* Adapt*" OR "“Latitud* Var” OR Intraspecific). We conducted an initial literature search on 24 August 2019 and updated the search on 28 July 2020. We also added studies that we were aware of but were not returned in the literature search. We used the following criteria for inclusion, where each study must have: (1) reported new results of whole-organism upper thermal limit in degrees Celsius for at least 2 populations of the same species, (2) experimentally measured thermal tolerance after acclimating all individuals to at least two temperatures, (3) reported a measure of error for the thermal tolerance estimate, and (4) not measured tolerance of introduced species, hybrid lines, cultivars, domesticated species, or later generations of experimental laboratory populations (greater than F2). Although we initially included both cold and heat tolerance studies, we later excluded cold tolerance studies from our analysis due to insufficient data. Studies of cold tolerance, and additional studies that met criteria (1) and (2) but were excluded based on (3) and/or (4) are listed in supplemental table S1. We screened 400 publications that measured thermal tolerances across populations and identified 20 studies to include in our meta-analysis, representing 19 species. The studies that were accepted after looking through titles and abstracts but were later excluded from our analysis are listed in Table S1. We extracted data from each publication using relevant figures, tables, text, or supplementary material. In the case of figures, we used WebPlotDigitizer to extract means and error estimates.