CONTENTS OF THIS DATASET Data files: 1) growth_rate_dataset.csv Phytoplankton growth rate vs temperature measurements, extracted from the literature. 2) final_calibrated_tree.phy The relative time-calibrated phylogeny reconstructed for this study. 3) dataset_for_TPC_MCMCglmms.csv Reliable TPC parameter estimates (along with measures of uncertainty), latitude/longitude values, and habitat (marine or freshwater) for all phytoplankton strains of this study. 4) dataset_for_marine_TPC_MCMCglmms.csv As above, but only for marine strains. Besides lat/lon values, this dataset also includes temperature data (from Lagrangian simulations and from the NOAA OISST dataset) for each isolation location. 5) dataset_of_B_0_B_pk_and_cell_volume.csv B_0 and B_pk estimates for all phytoplankton along with cell volume measurements in units of cubic meters. Source code: 1) TPC_fitting.py Python 2 script for fitting the 4-parameter variant of the Sharpe-Schoolfield model to the data in growth_rate_dataset.csv. 2) Lagrangian_trajectory_simulation.py Python 2 script for simulating backwards-in-time Lagrangian trajectories of drifting particles (marine phytoplankton) from a list of latide/longitude locations. 3) run_TPC_MCMCglmms.R R script for fitting regression models to the entire TPC dataset with all TPC parameters forming a combined response. 4) run_marine_TPC_MCMCglmms.R R script for fitting regression models to the TPC dataset of marine phytoplankton only. 5) run_B_0_or_B_pk_against_cell_volume_MCMCglmms.R R script for estimating the influence of cell volume on B_0 or B_pk values.