Ecological Archives A025-026-S2

Summer L. Martin, Stephen M. Stohs, and Jeffrey E. Moore. 2015. Bayesian inference and assessment for rare-event by catch in marine fisheries: a drift gillnet fishery. Ecological Applications 25:416–429. http://dx.doi.org/10.1890/14-0059.1

R simulation code for predicting annual bycatch and mortality using WinBUGS model estimates.
Ecological Archives A025-026-S2.

Summer L. Martin
Scripps Institution of Oceanography & NOAA Southwest Fisheries Science Center
8901 La Jolla Shores Drive
La Jolla, California 92037
E-mail: [email protected] or [email protected]

Stephen M. Stohs
NOAA Southwest Fisheries Science Center
8901 La Jolla Shores Drive
La Jolla, California 92037

Jeffrey E. Moore
NOAA Southwest Fisheries Science Center
8901 La Jolla Shores Drive
La Jolla, California 92037

Supplement2_RCode_PredictionByYears.R (MD5: ff27d3e2303bd8e670eea82b70f70780)

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 m_i, expected annual mortality for year i. In the context of our fisheries bycatch problem, posterior predictive distributions (PPDs) are estimated distributions of unobserved bycatch or mortality counts given the estimated posterior for Ɵ, the bycatch rate per fishing set, and a specified number of sets fished, n. Using this code, we generated PPDs for x_i (observed takes), y_i - x_i (unobserved takes), y_i (total takes), w_i (observed deaths), z_i - w_i (unobserved deaths), and z_i (total deaths).