10.6084/m9.figshare.3520538.v1 Summer L. Martin Summer L. Martin Stephen M. Stohs Stephen M. Stohs Jeffrey E. Moore Jeffrey E. Moore Supplement 2. R simulation code for predicting annual bycatch and mortality using WinBUGS model estimates. Wiley 2016 leatherback sea turtle Bayesian prediction Markov chain Monte Carlo protected species California drift gillnet fishery rare events humpback whale marine megafauna fisheries bycatch endangered species model Environmental Science Ecology 2016-08-04 21:19:12 Dataset https://wiley.figshare.com/articles/dataset/Supplement_2_R_simulation_code_for_predicting_annual_bycatch_and_mortality_using_WinBUGS_model_estimates_/3520538 <h2>File List</h2><div> <p><a href="Supplement2_RCode_PredictionByYears.R">Supplement2_RCode_PredictionByYears.R</a> (MD5: ff27d3e2303bd8e670eea82b70f70780)</p> </div><h2>Description</h2><div> <p>Supplement2_RCode_PredictionByYears.R – This R code uses the posterior distributions for model parameters generated by WinBUGS in Supplement 1 to predict annual bycatch and mortality for leatherback turtles and humpback whales in the California drift gillnet fishery (1990–2009). For each species, we generated posterior distributions for <i>m<sub>i</sub></i>, expected annual mortality for year <i>i</i>. In the context of our fisheries bycatch problem, posterior <i>predictive</i> distributions (PPDs) are estimated distributions of unobserved bycatch or mortality counts given the estimated posterior for <i>Ɵ</i>, the bycatch rate per fishing set, and a specified number of sets fished, <i>n</i>. Using this code, we generated PPDs for <i>x<sub>i</sub></i> (observed takes), <i>y<sub>i</sub> - x<sub>i</sub></i> (unobserved takes), <i>y<sub>i</sub></i> (total takes), <i>w<sub>i</sub></i> (observed deaths), <i>z<sub>i</sub> - w<sub>i</sub></i> (unobserved deaths), and <i>z<sub>i</sub></i> (total deaths).</p> </div>