DOI: 10.5061/dryad.k6djh9wk3
title: Thermal performance curves dataset based on <em>Littorina littorea</em> from different locations along a latitudinal gradient: Physiological and life history traits

description: Intraspecific variation in functional traits may indicate adaptation to
 environmental gradients and is crucial to understanding species
 distributions and range dynamics. We tested the hypotheses that: (1)
 thermal performance of Littorina littorea follows a countergradient cline,
 reflecting compensation in northern individuals and (2) local
 differentiation occurs at the range limits of its non-native Atlantic
 distribution. Snails from 10 locations, spanning 10° of latitude and
 approximately 1700 km, were exposed to a gradient of 12 temperatures in
 the laboratory, and survival, growth, feeding, metabolic rate and heat
 tolerance were measured. Thermal performance curves obtained were compared
 and used to calculate performance parameters: that is, thermal optimum,
 maximum performance and thermal breadth. Snails from the northern and
 southern range edges exhibited a gradual divergence in growth performance
 parameters relative to central populations. Snails from colder northern
 locations exhibited greater survival, feeding rate and heat tolerance when
 exposed to higher temperatures. The dataset can be used in meta-analyses
 focused on evaluating differences among taxa and populations in thermal
 performance of functional traits, as well as thermal tolerance and
 acclimation capacity.
description: # Garlaschè et al. 2025 Dataset on Littorina littorea thermal performance
 curves [Access this dataset on](10.5281/zenodo.14781307) The dataset
 regards physiological measurements of Survival, Growth, Feeding rate,
 Metabolic rate, and CTmax measured in L. littorea individuals after an
 exposure period of 30 days to 12 temperature levels. ## Description of the
 data and file structure This dataset is composed on 5 excel files and 1
 csv file. Each of them contain the raw data used for the analyses of the
 paper. The analysed variable are Survival, Growth, Feeding rate, Metabolic
 rate, CTmax. "CTmax.xlsx" Columns = Population (code),
 Temperature (Temperature of exposure, C°), CTMax (°C), Latitude (°),
 MeanSST (Summer mean Sea surface temperature, °C), SeasonLength (Day),
 MaxSST (Maximal SST, °C), Spawnmeansst (Mean SST of the spawning period,
 °C), Upper25thperc (Upper 25th percentile SST, °C), Upper10thperc (°C).
 "Feeding_rate.xlsx" Columns = Temperature (Temperature of
 exposure, C°), CTMax (°C), Latitude (°), MeanSST (Summer mean Sea surface
 temperature, °C), SeasonLength (Day), MaxSST (Maximal SST, °C),
 Spawnmeansst (Mean SST of the spawning period, °C), Upper25thperc (Upper
 25th percentile SST, °C), Upper10thperc (°C), lastrate (feeding rate, g
 day-1) Size2 (size at the end of exposure, mm).
 "Growth_dataset.xlsx" Columns = Shellgrowth (growth of the shell
 after exposure, mm), Temperature (Temperature of exposure, C°), CTMax
 (°C), Latitude (°), MeanSST (Summer mean Sea surface temperature, °C),
 SeasonLength (Day), MaxSST (Maximal SST, °C), Spawnmeansst (Mean SST of
 the spawning period, °C), Upper25thperc (Upper 25th percentile SST, °C),
 Upper10thperc (°C). "Metabolic_rate.csv" Columns = MO2
 (metabolic rate O2 h-1), Population (code), Temperature (Temperature of
 exposure, C°), CTMax (°C), Latitude (°), MeanSST (Summer mean Sea surface
 temperature, °C), SeasonLength (Day), MaxSST (Maximal SST, °C),
 Spawnmeansst (Mean SST of the spawning period, °C), Upper25thperc (Upper
 25th percentile SST, °C), Upper10thperc (°C). "Survival.xlsx"
 Columns = Survival (Until end of exposure, 1 = alive, 0 = dead),
 Population (code), Temperature (Temperature of exposure, C°), CTMax (°C),
 Latitude (°), MeanSST (Summer mean Sea surface temperature, °C),
 SeasonLength (Day), MaxSST (Maximal SST, °C), Spawnmeansst (Mean SST of
 the spawning period, °C), Upper25thperc (Upper 25th percentile SST, °C),
 Upper10thperc (°C). "TPC_estimation_CI.xlsx" columns = MeanSST
 (Summer mean Sea surface temperature, °C), Corresponding location (code)
 ,Param (type of parameter) Estimation (value of the parameter) CI_Lower
 (lower confidence interval) CI_Upper (upper confidence interval). ##
 Code/Software The code files (.R) are:
 "best_AIC_combination_selection.R" - the code used to select the
 best model through every combinations of factors and polynomial degrees -
 , "Models and plots for each variable.R" - The models selected
 for each variable and the plots created based on these models - ,
 "Rmax bootstrap CI.R", "Thermal breadth bootstrap
 CI.R", "Topt bootstrap CI.R" - The bootstrap methodology
 used to extract TPC parameters (Rmax, Topt, Breadth, respectively) from
 predictions based on the selected model for Feeding rate and Growth and
 their correspondant confidence intervals - ,
 "Models_and_plots_for_each_variable.R" - The models with plot
 for each variable -, "Rmax_bootstrap_CI.R" - Rmax bootstrap to
 obtain the confidence intervals of the parameter -,
 "Thermal_breadth_bootstrap_CI.R" - Thermal breadth bootstrap to
 obtain the confidence intervals of the parameter -,
 "Topt_bootstrap_CI.R" - Thermal optimum bootstrap to obtain the
 confidence intervals of the parameter -, "Map_Figure1.R" - Code
 used to make the map of figure 1, using the data from
 "Litto_locations.xlsx" - , "Plot_figure3.R" - Code to
 create the plot of Figure 3 based on "TPC_estimation_CI.xlsx"
 data -.