NIWA Casal2 User and Developer Support
Casal2 is NIWA’s next generation open-source integrated assessment tool for modelling the population dynamics of marine species, including fishery stock assessments. Casal2 expands functionality and increases maintainability relative to its predecessor, CASAL. Casal2 can be used for quantitative assessments of marine populations, including fish, invertebrates, marine mammals, and seabirds.
The NIWA Casal2 Development Team welcomes your contributions and feedback. Information about the use and development of Casal2 is available in the following locations.
The Casal2 Age-based User Manual The Casal2 Length-based User Manual
The Casal2 production and development release packages are available in the Casal2 GitHub repository.
Files for CASAL, the predecessor of Casal2
The Casal2 user and developer support forums are available on the Casal2 Discourse site.
The Casal2 contributor guidelines
The Casal2 software implements a generalised age-structured population model that allows for a great deal of choice in specifying the population dynamics, parameter estimation, and model outputs. Casal2 is designed for flexibility. It can implement an age-structured model for a single population or multiple populations using user-defined categories such as area, sex, and maturity. These structural elements are generic and not predefined, and are easily constructed. Casal2 models can be used for a single population with a single anthropogenic event (in a fish population model this would be a single fishery), or for multiple species and populations, areas, and/or anthropogenic or exploitation methods, and including predator-prey interactions.
In Casal2 the processes in a time period and within an annual cycle are defined by the user. Observation data used for model fitting can be from many different sources, like, removals-at-size or -age from an anthropogenic or exploitation event (e.g., fishery or other human impact), research survey and other biomass indices, and mark-recapture data. Model parameters can be estimated using penalised maximum likelihood or Bayesian methods.
As well as the point estimates of the parameters, Casal2 can calculate the likelihood or posterior distribution profiles, and can generate Bayesian posterior distributions using Markov chain Monte Carlo methods. Casal2 can project population status using deterministic or stochastic population dynamics. Casal2 can also simulate observations from a set of given model structures.