Because of ongoing climate change, populations of organisms are being subjected to stressful temperatures more often. This is especially problematic for ectothermic organisms, which are likely to be more sensitive to changes in temperature. Therefore, we need to know if ectotherms have adapted to environmental temperature and, if so, what are the evolutionary mechanisms behind such adaptation. Here, we use the nematode Pristionchus pacificus as a case study to investigate thermal adaptation on the Indian Ocean island of La Réunion, which experiences a range of temperatures from coast to summit. We study the evolution of high temperature tolerance by constructing a phylogenetic tree of strains collected from many different thermal niches. We show that populations of P. pacificus at low altitudes have higher fertility at warmer temperatures. Most likely, this phenotype has arisen recently and at least twice independently, consistent with parallel evolution. We also studied low temperature tolerance and showed that populations from high altitudes have increased their fertility at cooler temperatures. Together, these data indicate that P. pacificus strains on La Réunion are subject to divergent selection, adapting to hot and cold niches at the coast and summit of the volcano. Precisely defining these thermal niches provides essential information for models that predict the impact of future climate change on these populations.

This dataset consists of a list of P. pacificus strains, phenotype data, clade and beetle host. The data was processed In Matlab to plot the data and in R for statistical analysis. The data is from the manuscript "Adaptation to environmental temperature in divergent clades of the nematode Pristionchus pacificus" which is in press at Evolution.

Save these files to a folder 

• Leaver_Temerature_Adaptation_figures_in_Matlab.m
• get_counts.m
• equal_bins.m
• Strain_Table_name_phenotype_location_alt_beetle_clade.csv
• stations.csv
• beetleRange.csv

Open the .m file in Matlab and run the script from that folder. The script calls the two functions 'get_counts.m' and 'equal_bins.m' and loads the three '.cvs' files.

The output are the figures and a file called 'HBAC.txt' which is input for the R script.

Download these files

• Leaver_et_al_2022_Adaptation to environmental temperature_Evolution_statistical_analysis.R
• Alt-Freq_groups.txt
• HBAC.txt
• stations.txt
• TFmaxVclade.txt

Open the .R file in an R compiler and run the script. The script calls loads the four .txt files and performs statistical analyses.

Please consult the comments in the scripts for futher details.