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Status and Trends of Caribbean Coral Reefs: 1970-2024

1. Introduction

Coral reefs of the Anthropocene are increasingly threatened by a range of human-induced stressors from anthropogenic local drivers of loss including overfishing, pollution, and coastal development, to regional stressors such as climate change and ocean acidification. The cumulative impacts of these stressors have significantly altered the structure, function, and composition of coral reef ecosystems worldwide. One of the most documented consequences is the sustained decline in hard coral cover exacerbated by mass bleaching events driven by anomalously high sea surface temperatures such as those recorded in 1998, 2010, and 2014-2017, and most recently during the Fourth Global Mass Bleaching Event. Beyond these ecological changes, coral reef degradation undermines the ability of these ecosystems to provide vital services to human populations including coastal protection, food security through fisheries, and income from tourism.

Established in 1995 as an operational network of the International Coral Reef Initiative (ICRI), the Global Coral Reef Monitoring Network (GCRMN) plays a central role in global coral reef monitoring efforts. Working through ten regional nodes - including the Pacific - the GCRMN produces regular syntheses of the status and trends of coral reefs based on harmonized scientific data. The network’s mission is to improve understanding of reef health, support evidence-based policy and management, and build the technical and human capacity for reef monitoring at local, national, and regional levels. The GCRMN’s global and regional reports are designed for policymakers, managers, researchers, and international organizations to guide conservation strategies and help countries meet their national and international biodiversity commitments. In combining science, capacity building, and policy relevance, the GCRMN is a cornerstone of efforts to safeguard coral reefs in an era of accelerating environmental change. Since its establishment, the GCRMN has published six global reports. Alongside these global assessments, the GCRMN has produced numerous regional and thematic reports focusing on the status and trends of coral reefs in specific regions, such as the Western Indian Ocean, the Pacific, and the East Asian Seas.

This GitHub repository accompanies the Status and Trends of Caribbean Coral Reefs: 1970-2024 GCRMN report, which provides a comprehensive overview of the status and trends of shallow-water coral reefs across the Caribbean region. The report addresses key questions about changes in benthic cover (hard coral, macroalgae, turf algae, coralline algae, and other fauna) and evolving threats to reef ecosystems over the last four decades. It includes analyses of major coral genera (Acropora, Orbicella, and Porites), as well as environmental stressors such as human population pressure, thermal stress (SST trends and anomalies), and cyclone activity. Structured in two main parts — a regional synthesis and 44 country and territory chapters — it combines biophysical monitoring data with local insights through 9 case studies. This GitHub repository provides the code used to produce the results of the report.

2. Code

Functions

  • combine_model_data.R Combine benthic cover model results.
  • combine_plot_trends.R Combine temporal trend plots produced by the function plot_trends.R.
  • create_chapter_doc.qmd Countries and territories chapter template.
  • data_descriptors.R Get number of sites, surveys, datasets, first and last year of monitoring.
  • download_predictors.R Download predictors extracted through GEE and stored on Google Drive.
  • extract_coeff.R Extract linear models a and b coefficients.
  • extract_mankendall.R Calculate temporal trends using Man Kendall test.
  • graphical_par.R Graphical parameters, including colors and fonts.
  • plot_pred_obs.R Plot predicted vs observed values (model evaluation).
  • plot_region.R Regional background map.
  • plot_residuals.R Plot residuals (model evaluation).
  • plot_trends.R Plot temporal trends.
  • plot_vimp.R Plot Variable Importance Plot (VIMP).
  • prepare_benthic_data.R Prepare benthic cover data.
  • plot_pdp.R Plot Partial Dependence Plot (PDP).
  • plot_prediction_map.R Plot the map of the Caribbean with predicted values.
  • render_qmd.R Render script create_chapter_doc.qmd.
  • theme_graph.R Main ggplot theme for plots.
  • theme_map.R Main ggplot theme for maps.
  • theme_map_area.R ggplot theme for countries and territories maps.

Cleaning and selection (a_)

  • a01_select_topo-bathy.js Extract topography and bathymetry using Google Earth Engine (GEE).
  • a02_clean_shp.R Clean shapefiles from different sources.
  • a03_select_benthic-data.R Extract benthic cover data from gcrmndb_benthos.
  • a04_benthic-data_sources.R Extract lists of datasetID and contributors details.
  • a05_reef-buffer.js Create coral reef buffer polygons at 20, 50, and 100 km using GEE.
  • a06_reef-buffer-area.R Join reef buffer with areas’ boundaries.
  • a07_clean_cyclones.R Clean cyclones data.
  • a08_download_crw-year.R Extract netCDF file aggregated per year from Coral Reef Watch (CRW).

Indicators’ extraction (b_)

  • b01_extract_indicator_population.js Extract population indicators using GEE.
  • b02_extract_indicator_sst.R Extract SST indicators.
  • b03_extract_indicator_cyclones.R Extract cyclones indicators.

Models (benthic cover) (c_)

  • c01_explo_benthic-data.qmd Exploratory analyses of benthic cover data.
  • c02_select_pred-sites.js Generate sites on which the predictions will be made.
  • c03_extract_predictor_gee.js Extract predictors on GEE.
  • c04_extract_predictor_gravity.R Extract gravity as a predictor.
  • c05_extract_predictor_enso.R Extract ENSO as a predictor.
  • c06_extract_predictor_cyclones.R Extract cyclones as a predictor.
  • c07_extract_predictor_crw.R Extract CRW derived predictors.
  • c08_model_data-preparation.R Combine predictors and prepare benthic cover data.
  • c09_xgboost-model.R Run XGBoost models.

Figures and tables (d_)

  • d01_materials-and-methods.R Produce figures for the Materials and Methods.
  • d02_region_map.R Produce map of the region.
  • d03_areas_map.R Produce contextual maps for areas.
  • d04_region_sst.R Produce figures for SST for the region.
  • d05_areas_sst.R Produce figures for SST for areas.
  • d06_region_cyclones.R Produce figures for cyclones for the region.
  • d07_areas_cyclones.R Produce figures for cyclones for areas.
  • d08_region_spatio-temporal.R Produce figures for spatio-temporal distribution of monitoring for the region.
  • d09_areas_spatio-temporal.R Produce figures for spatio-temporal distribution of monitoring for areas.
  • d10_benthic-cover_trends.R Produce figures for benthic cover temporal trends.
  • d11_other-indicators.R Produce figures, tables, and numbers for other indicators.
  • d12_fish-biomass.R Produce figure for the fish biomass box.
  • d13_case-study.R Produce figures for the case studies.

Writing and sharing (e_)

  • e01_create-chapters.R Generate .docx chapters for areas.
  • e02_authors-contribution.R Export author’s contributions .xlsx file.
  • e03_push-google-drive.R Export figures to the Google Drive folder.

3. Reproducibility parameters

Warning in system2("quarto", "-V", stdout = TRUE, env = paste0("TMPDIR=", :
l'exécution de la commande '"quarto"
TMPDIR=C:/Users/jerem/AppData/Local/Temp/RtmpIpwreI/file5c5470b94740 -V'
renvoie un statut 1
─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.5.2 (2025-10-31 ucrt)
 os       Windows 11 x64 (build 26200)
 system   x86_64, mingw32
 ui       RTerm
 language (EN)
 collate  French_France.utf8
 ctype    French_France.utf8
 tz       Europe/Paris
 date     2025-12-26
 pandoc   3.6.3 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
 quarto   NA @ C:\\PROGRA~1\\RStudio\\RESOUR~1\\app\\bin\\quarto\\bin\\quarto.exe

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