CASAL is an advanced software package developed by NIWA for fish stock assessment.
It is used for quantitative assessments of the status of most of New Zealand's fish stocks,including our deepwater (e.g. orange roughy), middle depth (e.g. hoki), inshore (e.g. snapper), and shellfish fisheries. Internationally, it has been used to assess Patagonian and Antarctic toothfish, and broadbill swordfish fisheries.
CASAL2 is an advanced software package developed by NIWA for modelling the population dynamics of marine species.
CASAL2 is NIWA’s new integrated assessment tool for modelling population dynamics of marine species, including fishery stock assessments. CASAL2 expands functionality and maintainability over its predecessor, CASAL. CASAL2 can be used for quantitative assessments of marine populations, including fish, invertebrates, marine mammals and seabirds.
Introduction to CASAL
CASAL (C++ Algorithmic Stock Assessment Laboratory) is an advanced software package developed by NIWA for fish stock assessment. The software implements a generalised age- or length-structured fish stock assessment model that allows a great deal of choice in specifying the population dynamics, parameter estimation, and model outputs.
CASAL is designed for flexibility. It can implement either an age- or size-structured model, optionally also structuring the population by sex, maturity, and/or growth-path. It can be used for a single stock for a single fishery, or for multiple stocks, areas, and/or fishing methods. The user can choose the sequence of events in a model year. The data used can be from many different sources of information, for example catch-at-age or catch-at-size data from commercial fishing, survey and other biomass indices, survey catch-at-age or catch-at-size data, and tag-release and tag-recapture data. Estimation can be by either maximum likelihood or Bayes.
As well as generating point estimates of the parameters of interest, CASAL can calculate likelihood or posterior profiles and can generate Bayesian posterior distributions using Monte Carlo Markov Chain methods. CASAL can project stock status into the future using deterministic or stochastic recruitment and can generate a number of yield measures commonly used in New Zealand stock assessment, including MCY, CAY, Fmax, F0.1, deterministic MSY, and CSP.
Technical details
CASAL is available for Linux and from the command prompt for Microsoft Windows. The current version of CASAL is v2.30-2012/03/21.
For a full description of CASAL see: Bull, B.; Francis, R.I.C.C.; Dunn, A.; McKenzie, A.; Gilbert, D.J.; Smith, M.H.; Bain, R.; Fu, D. (2012). CASAL (C++ algorithmic stock assessment laboratory): CASAL user manual v2.30-2012/03/21 . NIWA Technical Report 135. 280 p.
Several of CASAL’s tasks are highly computer intensive and a powerful processor is recommended. A minimum of 64 megabytes of free RAM is recommended for running CASAL (although, depending on the scope of the problem, you may need much more). The program itself requires less than 10 megabytes of hard-disk space but output files can consume large amounts of disk space. Depending on number and type of user output requests, the output could range from a few hundred kilobytes to several hundred megabytes.
Getting CASAL
The CASAL software, documentation, example files, and R utility files are available on request. A copy of CASAL is freely available on request. Requests for CASAL or more information about CASAL can be made by contacting the CASAL development team.
CASAL user manual (PDF 3.9 MB)
