DOI: 10.5061/dryad.vhhmgqnwq
title: Asymmetry of thermal sensitivity and the thermal risk of climate change

description: Aim. Understanding and predicting the biological consequences of climate
 change requires considering the thermal sensitivity of organisms relative
 to environmental temperatures. One common approach involves “thermal
 safety margins” (TSMs), which are generally estimated as the temperature
 differential between the highest temperature an organism can tolerate
 (CTmax) and the mean or maximum environmental temperature it experiences.
 Yet, organisms face thermal stress and performance loss at body
 temperatures below their CTmax, and the steepness of that loss increases
 with the asymmetry of the thermal performance curve (TPC). Location.
 Global Time period. 2015-2019. Major taxa studied. Ants, fish, insects,
 lizards, and phytoplankton. Methods. We examine variability in TPC
 asymmetry and the implications for thermal stress for 384 populations from
 289 species across taxa and for metrics including ant and lizard
 locomotion, fish growth, and insect and phytoplankton fitness. Results. We
 find that the thermal optimum (Topt, beyond which performance declines) is
 more labile than CTmax, inducing interspecific variation in asymmetry.
 Importantly, the degree of TPC asymmetry increases with Topt. Thus, even
 though populations with higher Topts in a hot environment might experience
 above-optimal body temperatures less often than do populations with lower
 Topts, they nonetheless experience steeper declines in performance at high
 body temperatures. Estimates of the annual cumulative decline in
 performance for temperatures above Topt suggest that TPC asymmetry alters
 the onset, rate, and severity of performance decrement at high body
 temperatures. Main conclusions. Species with the same TSMs can experience
 different thermal risk due to differences in TPC asymmetry. Metrics that
 incorporate additional aspects of TPC shape better capture the thermal
 risk of climate change than do TSMs.
description: We used the terms “thermal optima” and “Topt” to search the
 literature for datasets that included all three thermal performance curve
 parameters (CTmin, Topt, and CTmax) or that permitted estimates of these
 parameters. Our final data includes a total of 384 TPCs (289 species)
 across multiple taxa. These TPCs vary in the type of performance measured
 and in the level of biological organization (see Table S1). We refer to
 five compiled datasets labeled by the taxonomic group and level of
 performance represented. The ant performance dataset describes foraging
 activity for 22 genera of ants, where Topt is estimated based on the
 proportion of ants foraging as a function of ground surface temperature
 (Guo et al., 2020). CTmin and CTmax were replaced with minimum and maximum
 foraging temperatures, respectively, when they exceeded CTmin and CTmax
 estimates. The lizard performance dataset describes lizard sprint speed
 for 77 populations of 66 species, combining data from two studies (Huey et
 al., 2009; Muñoz et al., 2016). The fish growth dataset describes growth
 rates for 18 populations in three species of salmonid fish (Elliott
 & Hurley, 1995; Jonsson et al., 2001; Larsson et al., 2005;
 Forseth et al., 2009). The final two data sets focus on
 the temperature dependence of fitness (r: intrinsic rate of population
 increase). The insect fitness dataset describes r for 67 populations (61
 species) of insects, updating data (Huey & Berrigan, 2001; Frazier
 et al., 2006) that been used in numerous analysis of climate change
 impacts (Deutsch et al., 2008 and subsequent papers) with additional
 recent observations (Rezende & Bozinovic, 2019). The plankton
 fitness dataset describes r for a total of 266 populations in 184 species
 of phytoplankton (Thomas et al., 2012, 2016). It is
 important to appreciate the heterogeneity in biological levels and types
 of performance for interpreting the different patterns in TPCs (see
 Discussion). Note that performance is a rate for four of the five datasets
 but is a proportion for the ant performance data. Topt values were
 estimated by fitting TPC curves to performance measured at multiple
 constant temperatures. For ants and lizards, CTmin and CTmax estimates
 were based on temperature ramping experiments. For the other taxa, CTmin
 and CTmax were estimated by extrapolating the fitted TPC curves (Deutsch
 et al., 2008). The TPC functions and fitting methods differed among the
 initial publications. The Rezende and Bozinovic (2019) insect dataset used
 a TPC function with a long left tail that was not designed for estimating
 CTmin. We thus re-estimated CTmin, Topt, and CTmax for this dataset using
 the fitting algorithm from the plankton dataset (Thomas et al., 2012).
 Quality control criteria for these TPC estimates are described in Table
 S1.
description: R code for analysis and figures along with data are available at
 https://github.com/HuckleyLab/ThermalStress.