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JABBA: Just Another Bayesian Biomass Assessment

The materials in this repository present the stock assessment tool ‘Just Another Bayesian Biomass Assessment’ JABBA. The motivation for developing JABBA was to provide a user-friendly R to JAGS (Plummer) interface for fitting generalized Bayesian State-Space SPMs with the aim to generate reproducible stock status estimates and diagnostics. Building on recent advances in optimizing the fitting procedures through the development of Bayesian state-space modelling approaches, JABBA originates from a continuous development process of a Bayesian State-Space SPM tool that has been applied and tested in many assessments across oceans. JABBA was conceived in the Hawaiian Summer of 2015 as a collaboration between young researchers from South Africa and the Pacific Islands Fisheries Science Center (NOAA) in Honolulu, HI USA. The goal was to provide a bridge between age-structured and biomass dynamic models, which are still widely used. JABBA runs quickly and by default generates many useful plots and diagnosic tools for stock assessments.

Inbuilt JABBA features include:

  • Integrated state-space tool for averaging multiple CPUE series (+SE) for optional use in assessments
  • Automatic fitting of multiple CPUE time series and associated standard errors
  • Fox, Schaefer or Pella Tomlinson production function (optional as input Bmsy/K)
  • Kobe-type biplot plotting functions
  • Forecasting for alternative TACs
  • Residual and MCMC diagnostics
  • Estimating or fixing the process variance
  • Optional estimation additional observation variance for individual or grouped CPUE time series
  • Easy implementation of time-block changes in selectivity
  • New: Estimating Catch with Error
  • New: Estimating shape with prior
  • New: Catch-Only option with additional relative biomass priors
  • New: Inbuilt retrospective and hindcasting run and plotting options

Installing JABBA as R package

library(devtools)
install_github("jabbamodel/JABBA")

Test-drive JABBA

library(JABBA)
data(iccat)

# Compile JABBA JAGS model and input object for bigeye tuna (bet)
jbinput = build_jabba(catch=iccat$bet$catch,cpue=iccat$bet$cpue,se=iccat$bet$se,assessment="BET",scenario = "TestRun",model.type = "Fox",sigma.est = FALSE,fixed.obsE = 0.01)

# Fit JABBA (here mostly default value - careful)
bet1 = fit_jabba(jbinput,quickmcmc=TRUE)

# Make individual plots
jbplot_catcherror(bet1)
jbplot_ppdist(bet1)
jbplot_cpuefits(bet1)
jbplot_logfits(bet1)

# Plot Status Summary
par(mfrow=c(3,2),mar = c(3.5, 3.5, 0.5, 0.1))
jbplot_trj(bet1,type="B",add=T)
jbplot_trj(bet1,type="F",add=T)
jbplot_trj(bet1,type="BBmsy",add=T)
jbplot_trj(bet1,type="FFmsy",add=T)
jbplot_spphase(bet1,add=T)
jbplot_kobe(bet1,add=T)
# Test run end

More detailed examples of JABBA applications to ICCAT stocks can be found in Examples_iccat.R.

An updated vignette is currently under development...

Reference
Winker, H., Carvalho, F., Kapur, M. (2018) JABBA: Just Another Bayesian Biomass Assessment. Fisheries Research 204: 275-288.

JABBAbeta GitHub repository

JABBA development version for testing new JABBA features and stock assessment examples