coral-bleach-recovery

This repository contains R code for the Bayesian models accompanying Robinson, Wilson and Graham "Abiotic and biotic controls on coral recovery 16 years after mass bleaching", Coral Reefs 2019.

https://link.springer.com/article/10.1007/s00338-019-01831-7

The following R packages were used to analyse data.

install.packages(c("tidyverse", "rethinking", "here"))

data

• recovery_year_model.Rdata contains model structure (rec.year.m) and parameter effect sizes (rec.params) for predicting recovery year
• recovery_trajectory.Rdata contains logistic model strucutre (rec.trajectory.m), predicted recovery years (base) and recovery trajectory for each reef over 100 years (rec.trajectory)
• posterior_sims.Rdata contains posterior samples for each recovery year predictor covariate (depth, complex, init_cover, wave, herb, coral_juv, nitrogen)
• jacknife/ contains model structures and posterior samples for jacknife sensitivity analysis

figures

• logistic_models_predictions.pdf are model predictions for each candidate logistic model, with uncertainty intervals and plotted against observed data
• recovery_diagnostic_jackknife.pdf are parameter effect sizes for each jacknife subsample

scripts

• 1_logistic_growth_model.R fits Bayesian logistic growth models
• 2_recovery_year_model.R fits Bayesian linear model to predict recovery year
• 3_jacknife_analysis.R runs jacknife sensitivity analysis on recovery year model (2)
• scaling_function.R is generic function for scaling covariates to mean of 0 (for continuous) or creating dummy variables (for categorical)