DOI: 10.5061/dryad.18931zd4v
title: Rate and capacity of acclimation of temperature tolerance in ectothermic animals

description: Organisms experience environments that change by different amounts and at
 different rates throughout their lives. Phenotypic plasticity helps
 organisms respond to such change because it can facilitate a ‘match’
 between the phenotype of the individual and the phenotype that is optimal
 in its present environment. Here we evaluate the ability of organisms to
 match both the amplitude and tempo of environmental fluctuations by asking
 whether a relationship exists between the capacity and rate of phenotypic
 plasticity, and if so, in what direction? We re-analyze published data
 from experiments documenting the temporal dynamics of acclimation in
 thermal tolerance to temperature change. Across species of reptiles,
 amphibians, fish, insects and crustaceans, we find that the rate and the
 capacity with which thermal tolerance can respond plastically to
 temperature change is negatively correlated. In other words, when plastic
 adjustment of the phenotype is large, the rate at which that adjustment
 can be realized is slow.. Our results indicate that if changes in the
 environment occur rapidly and are large in magnitude, an example being the
 extremes in weather brought about by climate change, it may be difficult
 for organisms to evolve plasticity that is rapid enough and of sufficient
 capacity to counteract them.
description: We utilized the existing database of plasticity time course
 experiments provided by Einum and Burton (2023), https://doi.org/10.5061/dryad.gtht76hqq. This database contained data from 308 experiments from 60 studies. The procedure for compiling studies, eligibility criteria for inclusion, and the method applied for estimating rates of plasticity is given in detail in (Einum & Burton 2023). Briefly, though, these studies consisted of experiments where animals, having been acclimated to a given initial temperature, were abruptly shifted to a new acclimation temperature (either lower or higher). Thermal tolerance was measured prior to and at different time steps t (in h) after this shift. Measures of thermal tolerance were either critical maximum temperature (CTmax) or critical minimum temperature (CTmin). The data set also contained a lower number of experiments that had measured the time to some defined response such as immobility or death when exposed to a detrimental high or low temperature (TTD). However, for the current work TTD measurements were excluded, as the approach we used estimated plasticity capacity on the original scale of the data (see below), and thus these were not comparable for measurements of critical temperatures and TTD. This left data from 277 experiments from 47 studies. The model fitted to each dataset (see below) estimates two parameters, and thus to avoid overparameterization we excluded 36 experiments with less than three time points of observation following the initial value measured at time = 0. Finally, we removed another 36 experiments that were missing acclimation temperatures (required for calculating capacity, see below). Thus, the data set available for estimation of rate and capacity consisted of 205 experiments originating from 39 studies. For each experiment, a time series of phenotypic values, <em>z<sub>t</sub></em>, charting the time-course of the acclimation response were obtained, typically from figures showing the mean tolerance of groups of individuals that had experienced the ‘new’ temperature for differing lengths of time. Einum and Burton (2023) provided a method to calculate a single parameter that describes the rate of phenotypic plasticity. In the current analysis, we required estimates of plasticity capacity that corresponded to estimates of the rate of plasticity. To obtain estimates of both plasticity rate and capacity we first rescaled each experimental dataset to have a critical temperature of 0°C at the first measurement timepoint and with a subsequent increase, i.e.  , where <em>Z<sub>t</sub></em> is the rescaled critical temperature at time t (in hours). We then fitted the model <em>Z<sub>t</sub></em> = <em>Z<sub>∞</sub></em>(1-<em>e</em><sup>-<em>λt</em></sup>), where <em>Z<sub>∞</sub></em> is the rescaled asymptotic critical temperature when acclimation is complete (i.e. plasticity capacity), and <em>λ</em> (h<sup>-1</sup>) is the plasticity rate (Fig 1). The model was fitted using the function <em>nls_multstart</em> from the <em>nls.multstart</em> package v.1.2.0 (Padfield & Matheson, 2020) in R v.4.1.2 (R Core Team, 2021), and for each data set we extracted the estimated means and variances of the capacity and rate parameters. The model failed to converge for ten of the 205 experiments, and these were excluded from further analyses. To make plasticity capacity comparable among experiments that varied in the difference between the initial and new acclimation temperatures, we transformed each <em>Z<sub>∞ </sub></em>estimate into an acclimation response ratio, or ARR (e.g. Claussen 1977). The ARR is given as the absolute change in critical temperature per degree difference in temperature between the initial temperature (i.e. the first temperature the experimental organisms are completely acclimated to) and the new acclimation temperature once the plastic response is completed, i.e. |<em>Z<sub>∞</sub></em>/(acclimation temperature – initial temperature)|. The variance associated with each <em>Z<sub>∞</sub></em> estimate was also divided by the difference between the initial and new acclimation temperatures so that plasticity capacity variances were expressed on the same scale as the ARR values.
description: # Title of Dataset: Rate and capacity of acclimation to temperature
 tolerance in ectothermic animals --- We compiled data on rates of
 acclimation of temperature tolerance in ectothermic animals from the
 litterature. The data were used to describe how such rates may vary
 taxonomically as well as in response to environmental temperature and body
 size. ## Description of the Data and file structure All data are given in
 the file "Raw_data.txt". Missing data for specific variables are
 given as "NA" ## Abbreviated variable names in
 "Raw\_data.txt": Search "Which search the study was
 identified by. See ""Methods"" in current entry for
 details" Author Lead author of study from which the data were
 obtained Year Year of publication of study from which the data were
 obtained study Study coded as number species Species name of organism used
 in study measurement.type Measure of thermal tolerance as reported by
 study measurement.type.simplified Measure of thermal tolerance categorized
 life.stage Life stage of experimental organisms Mass.g.from.paper Mean
 mass (g) of experimental organisms reported in study Length.mm.from.paper
 Mean length (mm) of experimental organisms reported in study Size.comment
 Comment about length or mass data Med.mass.g Median mass (g) of species
 obtained from other sources (not from original study) Med.length.mm Median
 length (mm) of species obtained from other sources (not from original
 study) Min.adultmass.g Minimum adult mass (g) of species obtained from
 other sources (not from original study) Max.adultmass.g Maximum adult mass
 (g) of species obtained from other sources (not from original study)
 Min.adultlength.mm Minimum adult length (mm) of species obtained from
 other sources (not from original study) Max.adultlength.mm Maximum adult
 length (mm) of species obtained from other sources (not from original
 study) Phylum Phylum the species belongs to Class Class the species
 belongs to Habitat Habitat the species inhabit Experiment Unique
 experiment number assigned to each experiment (each study contain up to
 several experiment data sets) acctemp1 temperature (degrees C) organisms
 were kept at prior to acclimation acctemp1duration_d duration of time (d)
 organisms were kept at acctemp1 prior to acclimation to new temperature
 acctemp2 acclimation temperature (degrees C) regulation Whether thermal
 tolerance was induced to be up- or down-regulated trait Type of thermal
 tolerance trait. CTMax = maximum critical temperature (degrees C). CTMin =
 minimum critical temperature (degrees C). TTDh = time to death (h). Surv =
 survival rate (%) temp_TTD Temperature (degrees C) at which time to death
 was measured time_d Time elapsed (d) since moving organism into
 acclimation temperature time_h Time elapsed (h) since moving organism into
 acclimation temperature Traitvalue "Measured value of trait used to
 assess thermal tolerance. Unit depends on variable
 ""trait"", and is given by variable
 ""Traitunit""" Traitunit "Unit associated
 with the variable ""Traitvalue"""
 reciprocal_control Whether the experiment employs a design where thermal
 tolerance following complete acclimation to two different acclimation
 temperatures is ensured comment Comments regarding experimental design
 \##The annotated R script used for analyses is the file
 "Acclimation_rate_and_capacity.R" ## Sharing/access Information
 Links to other publicly accessible locations of the data: Was data derived
 from another source? Yes If yes, list source(s): Alemu, T., Alemneh, T.,
 Pertoldi, C., Ambelu, A., & Bahrndorff, S. (2017). Costs and benefits
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