Marine heatwaves are not a dominant driver of change in demersal fishes

Alexa L. Fredston, William W. L. Cheung, Thomas L. Frölicher, Zoë J. Kitchel, Aurore A. Maureaud, James T. Thorson, Arnaud Auber, Bastien Mérigot, Juliano Palacios-Abrantes, Maria Lourdes D. Palomares, Laurène Pecuchet, Nancy Shackell, Malin L. Pinsky

Please contact A. Fredston with questions about this project. Please cite the manuscript for all references to this project and its results, as well as the OSF DOI if data or code are reused. The results are fully reproducible from the scripts and all data files are either in this GitHub repository or (if they are too large) hosted on OSF (as described below).

Where do the raw data come from?

We used of a number of datasets that are already publicly available and/or published with this project. These are fully described and cited in the manuscript, but we also list them here for ease of download, access, and attribution.

• Trawl data from FISHGLOB, a project to harmonize publicly available trawl survey records from federal agencies around the globe. The raw data files from FISHGLOB are too big to host on GitHub but they are available on OSF.
• Sea bottom temperature data from GLORYS, an ocean reanalysis data product by the European Copernicus Marine Environment Modeling Service available beginning in 1993.
• Sea surface temperature data from OISST, a historical satellite temperature record from the U.S. National Oceanic and Atmospheric Administration beginning in 1982.
• Historical fishing pressure estimates from Sea Around Us.
• Species-specific realized thermal niche estimates from Burrows et al. 2018.
• Species traits from Beukhof et al. 2019.

What's in this repository?

The repository is organized as follows:

• scripts-to-generate-mhws includes the .csh scripts used to process OISST and GLORYS data into the files found in raw-data.
• raw-data contains raw datasets obtained from other sources (described above).
• processed-data contains outputs of scripts that filter, clean, summarize, or analyze data.
• figures contains image files generated by scripts for the main text figures.
• extended contains image files generated by scripts for the extended data figures.

What's not in the repository?

The following files are too big to host on GitHub and are available on OSF only:

• The raw FISHGLOB data (a slightly earlier version of the dataset described in Maureaud et al. 2023), FISHGLOB_public_v1.5_clean(1).csv. This should be downloaded from OSF and moved to raw-data to reproduce analyses.
• The outputs of power analyses: pwrout_yrs_glorys.rds, pwrout_yrs_oisst.rds, pwrout_gamma_glorys.rds, and pwrout_gamma_oisst.rds. These should be downloaded from OSF and moved to processed-data to reproduce analyses.

We did not host the raw GLORYS and OISST data on OSF because the source files are very large. The GLORYS12 sea bottom temperature data were downloaded from https://data.marine.copernicus.eu/product/GLOBAL_MULTIYEAR_PHY_001_030/description (accessed November 2, 2022). The NOAA OISST data were downloaded from https://www.ncei.noaa.gov/data/sea-surface-temperature-optimum-interpolation/ (accessed June 17, 2020).

In what order should things be run?

To reproduce the analysis, run these scripts in order:

1. prep_survey_extent_nc.R generates a netcdf file with the spatial footprints of trawl surveys used in the analysis, for merging with marine heatwave data. It also generates a .csv file with a "key" to translate the integer survey ID codes in the netcdf to their real names. This does not need to be re-run, but all the scripts below this should be re-run in order if the spatial footprints are updated.
2. prep_trawl_data.R takes the public trawl data records from version 1.5 of FISHGLOB (see above note about downloading the data file from OSF), processes them into a standardized format with columns for survey, year, species, and CPUE in kg, and writes them out as .csv files in the processed-data folder. This was run on a computing server (see Notes below). If you skip this step, the rest of the code will still run, using processed data files hosted on GitHub.
3. prep_MHWs.R merges those trawl records with the appropriate MHW and CTI data.
4. temporal_beta_diversity.R calculates interannual changes in richness and beta diversity (both total dissimilarity and individual components of nestedness and turnover for occurrence metrics and biomass gradient and balanced variation for biomass metrics).
5. power_analysis.R conducts a power analysis. This was run on a computing server (see Notes below) and if you download the output files from OSF (see above) you can skip this step.
6. MHW_stats_and_figures_main_text.R analyzes the data and makes figures and statistics for the main text.
7. MHW_stats_and_figures_supplement.Rmd generates the SI tables as a PDF and writes out all the extended data figures.

Notes

• Software versions used in this analysis are captured by renv and listed in the lockfile. Here is a summary of how renv works.
• Most of these analyses were run on a personal computer, and should be easy to reproduce, except prep_trawl_data.R and power_analysis.R, which were conducted in R 3.6.0 on a machine with the following specifications: Windows Server 2019 2-Intel 6154 Xeon 3.0Ghz 18cores(36 threads) each 512 GB memory 6TB- SSD storage 18TB- HDD storage NVIDIA P4000 8Gb 10Gb ethernet