The collection contains programs that have been developed over the last 15-20 years. Most of them are in still in use, some have been reproduced by others as parts of e.g. FLR.
All programs are distributed as open source. They can be used free of charge. If they are modified, it would be appreciated if the origin is clearly stated, as well as the changes and modifications that are made. The programs have been used and tested extensively, but there is no guarantee that they are free of bugs.
For each program, there is an executable version, the source code, a manual and examples of input files. The program language is mostly Fortran 77 and should compile with any standard F77 compiler. None of the programs use proprietary subroutines or other facilities.
Assessment program with a wide variety of options. Basically it has a separable model for the fishing mortalities, but with the option to let the selection at age change gradually according to a recursive updating algorithm. The user decides which parameters to estimate, which allows a good deal flexibility to condition the model. There is a range of objective functions. Weighting of the observations in the objective functions is manual, weighting by inverse variance is not included. The optimisation is by a searching routine. Uncertainties are estimated by bootstrap.
Assessment program based on the algorithms in XSA, but with seasonal (quarterly or half-yearly) time steps. It was made to assess short lived species (Sandeel and Norway pout). Compared to the standard version of XSA, it has an option to fill in holes in the catch numbers at age data and an option to let the survey catchabilities vary over time using a kernel algorithm. The shrinkage towards the mean option in standard XSA is not included. There have been problems reproducing the assessments done by ICES. The code for that version has been lost, the code in the present package is the original one.
Length based assessment program. It has a self-contained population model which describes the time course in terms of length distributions and loss due to mortality. The population is an assembly of 'super-individuals', with individual growth parameters and time and length at entry. Derived data for fitting to observations include catches and survey indices at length, aggregate biomass indices and acoustic sA values. The user decides which parameters to estimate. Weighting of the observations in the objective functions is manual, weighting by inverse variance is not included. The optimisation is by a searching routine. Uncertainties are estimated by bootstrap. The program is primarily an experimental tool. It has been attempted for assessing some stocks but never been used for formal assessments, mostly because the data have been too poor.
Short term deterministic program for multiple competing fleets. This program was made specifically for providing advice on herring in the North Sea and Skagerak. Recently, members of the ICES HAWG have translated this program into R with some amendments.
is a medium term stochastic stock simulation program with two competing fishing fleets, and a variety of options for harvest rules. It was made primarily for evaluating harvest rules for North Sea herring, but should be more generally applicable. It has evolved gradually since the mid 1990ies, and the code is now rather messy. LTEQ produces long term stochastic equilibria for a range of fishing mortalities. The stochastic element is the recruitment, and the equilibrium is found by an iterative process: A distribution of recruitments generates a distribution of SSBs and vice versa, and this process is continued until the distributions are stable.
Medium term stochastic simulation of harvest rules, for a single stock and single fishing fleet. It has evolved gradually as it has been applied to various new stocks, 3 versions are included in this package. It has various options for recruitment models (including cycling variations and occasional large year classes) and a quite wide range of management options. It is made to scan over ranges of management options. Assessment error is only implemented as a random noise applied to the true model stock, with no explicit assessment included.