Future Ocean Warming May Threaten Key Photosynthetic Microbes

Description The datasets supporting the conclusions of this article, including field measurements of Prochlorococcus division rates, are available in this repository. The R code performs the following tasks: Loads data from various sources, including lab experiments, dilution experiments, and in-situ measurements. Calculates thermal norm predictions using different models (Eppley, Hinshelwood, Eppley-Norberg) to predict division rates based on temperature. Generates figures to visualize the results, including latitudinal and temperature effects on division rates, model predictions compared with observed data, and changes in primary production under different emission scenarios. Fits the Hinshelwood model to culture data and extracts best-fit parameters. Performs bootstrapping to estimate uncertainty in the Hinshelwood model parameters. Calculates confidence intervals for the bootstrapped parameters. R Scripts Ribalet_main.R: This script contains the main analysis code, including data loading, model fitting, figure generation, and bootstrapping. Ribalet_fitting.R: This script defines functions for fitting different growth models to the data and estimating model parameters. Requirements R version 4.4.2 (2024-10-31)Platform: aarch64-apple-darwin20Running under: macOS Sequoia 15.1.1 Matrix products: defaultBLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib LAPACK: /Library/Frameworks/R.framework/Versions/4.4-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.12.0 attached base packages:[1] parallel stats graphics grDevices utils datasets [7] methods base other attached packages: [1] DEoptim_2.2-8 arrow_15.0.1 ggpubr_0.6.0 lubridate_1.9.3 [5] forcats_1.0.0 stringr_1.5.1 dplyr_1.1.4 purrr_1.0.2 [9] readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.1 [13] tidyverse_2.0.0 Installation Install the required R packages: Code snippet install.packages(c("tidyverse", "ggpubr", "arrow", "DEoptim")) Usage The scripts will generate figures and output files in the same directory. Input Data The code requires the following input data files: culture.csv dilution.csv abundance.csv mpm.csv model_results.parquet bootstrap_projections.csv modeled-thermal-traits.tsv sst.parquet culture_syn.csv Please ensure that these files are present in the same directory as the R script files. Output Data The code generates the following output files: Figures: Figure1.png, Figure2.png, Figure3.png, FigureS1.png, FigureS2.png, FigureS3.png, FigureS4.png, FigureS5.png, FigureS6.png, FigureS9.png, FigureS11.png, FigureS12.png, FigureS13.png, FigureS14.png, FigureS15.png CSV files: bootstrap_parameters.csv, cultures_thermal_reactions.csv License This code is licensed under the MIT License.