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Status and Trends of Coral Reefs of the Pacific: 1980-2023

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Status and Trends of Coral Reefs of the Pacific

1. Introduction

2. Code

Functions

  • data_descriptors.R Get number of sites, surveys, datasets, first and last year of monitoring.
  • graphical_par.R Graphical parameters, including colors and fonts.
  • theme_graph.R Main ggplot theme for the plots of the reports.
  • theme_map.R Main ggplot theme for the maps of the reports.

Cleaning and selection (a_)

  • a1_select_benthic-data.R Select gcrmndb_benthos data to use in the analyses.
  • a2_benthic_data_sources.R Extract data sources from gcrmndb_benthos.
  • a3_clean_eez.R Select and clean economic exclusive zones (EEZ) from marineregions.
  • a4_clean_land.R Clean Pacific land data (high spatial resolution) from Princeton University.
  • a5_clean_bathy.R Clean bathymetry data from Natural Earth Data.
  • a6_clean-reef-distribution.R Select Pacific coral reefs distribution from the Tropical Coral Reefs of the World World Resources Institute (WRI).
  • a7_reef-buffer.js Create 100 km reef buffer using Google Earth Engine (GEE).
  • a8_clean_cyclones.R Clean cyclone dataset from IBTrACS.
  • a9_extract_dhw-year.R Create TIFF files of maximum DHW per year using Coral Reef Watch data.

Extract indicators (except benthic cover) (b_)

  • b1_extract_indicator_land.js Extract total land area for each EEZ using GEE.
  • b2_extract_indicator_elevation.js Extract mean land elevation for each EEZ using GEE.
  • b3_extract_indicator_population.js Extract human population for each EEZ using GEE.
  • b4_extract_indicator_sst.R Extract SST on coral reefs for each EEZ.
  • b5_extract_indicator_cyclones.R Extract cyclones on coral reefs for each EEZ.

Models (benthic cover) (c_)

  • c1_select_pred-sites.js Generate sites on which the predictions will be made.
  • c2_extract_predictor_gee.js Extract the values of the predictors for data sources available on GEE.
  • c3_extract_predictor_gravity.R Extract gravity as a predictor.
  • c4_extract_predictor_enso.R Extract ENSO as a predictor.
  • c5_extract_predictor_cyclones.R Extract cyclones as a predictor.
  • c6_extract_predictor_dhw-year.R Extract DHW as a predictor.
  • c7_model_data-preparation.R Combine predictors and prepare observed data.
  • c8_model_data-exploration.R Data exploration.
  • c9_model_tuning.R Machine Learning model hyperparameters tuning.
  • c10_model_bootstrap.R Machine Learning model bootstrap.

Figures and tables (d_)

  • d1_materials-and-methods.R
  • d2_pacific_map.R
  • d3_territories_map.R
  • d4_pacific_sst.R
  • d5_territories_sst.R
  • d6_pacific_cyclones.R
  • d7_territories_cyclones.R
  • d8_pacific_spatio-temporal.R
  • d9_territories_spatio-temporal.R
  • d10_benthic-cover_trends.R
  • d11_other-indicators.R
  • d12_case-studies.R

3. Reproducibility parameters

─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.4.1 (2024-06-14 ucrt)
 os       Windows 10 x64 (build 18363)
 system   x86_64, mingw32
 ui       RTerm
 language (EN)
 collate  French_France.utf8
 ctype    French_France.utf8
 tz       Europe/Paris
 date     2024-10-15
 pandoc   3.2 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)

─ Packages ───────────────────────────────────────────────────────────────────
 package       * version    date (UTC) lib source
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 callr           3.7.6      2024-03-25 [1] CRAN (R 4.4.1)
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Status and Trends of Coral Reefs of the Pacific: 1980-2023

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