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>
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