Future Ocean Warming Threatens 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.parquet

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

CSV files: bootstrap_parameters.csv, cultures_thermal_reactions.csv

License

This code is licensed under the MIT License.