Stock Synthesis (SS3) is the most commonly used general age-structured integrated stock assessment model. SS is programmed in AD Model Builder (ADMB). It has a wide range of options for population dynamics and fishery assumptions, parameter configurations, and data fitting. It also has several support tools for reporting (r4ss), simulation, diagnostics, etc. SS3 has been used for many stock assessments and journal publications.
Methot, R.D., Wetzel, C.R., 2013. Stock synthesis: a biological and statistical framework for fish stock assessment and fishery management. Fish. Res. 142, 86–99. https://doi.org/10.1016/j.fishres.2012.10.012
MULTIFAN-CL is an integrated age-structured model specifically developed for tuna assessments and fitting to length composition data. MULTIFAN-CL was extended to include spatial dynamics and fit to composition data, an important development for tuna assessments. MULTIFAN-CL is programmed in C++ using AUTODIF, the precursor to ADMB. MULTIFAN-CL is now used routinely for tuna stock assessments by the Oceanic Fisheries Programme (OFP) of the Secretariat of the Pacific Community (SPC) in the western and central Pacific Ocean (WCPO).
Fournier, D.A., Hampton, J., and Sibert, J.R. (1998).MULTIFAN-CL: a length-based, age-structured model for fisheries stock assessment, with application to South Pacific albacore, Thunnus alalunga.(pdf - 287k) Canadian Journal of Fisheries and Aquatic Sciences 55, 2105-2116. https://cdnsciencepub.com/doi/10.1139/f98-100
Hampton, J., Fournier, D.A., 2001. A spatially disaggregated, length-based, age structured population model of yellowfin tuna (Thunnus albacares) in the western and central Pacific Ocean. Mar. Freshwat. Res. 52, 937–963. https://connectsci.au/mf/article/52/7/937/58445/A-spatially-disaggregated-length-based-age
SAM is a state-space stock assessment model that explicitly deals with temporal variation in model parameters (e.g., recruitment, survival, and selectivity) within a random effects framework. SAM is programmed in TMB. SAM is used extensively for assessments in Europe under ICES.
Nielsen, A.N. and Berg, C.W. 2014. Estimation of time-varying selectivity in stock assessments using state-space models. Fisheries Research 158: 96-101. https://www.sciencedirect.com/science/article/abs/pii/S0165783614000228
Casal2 , developed in New Zealand by the National Institute of Water & Atmospheric Research Ltd. (NIWA) is a next generation open-source population assessment tool for modelling the dynamics of marine species. Casal2 expands functionality and increases maintainability relative to its predecessor, CASAL. The Casal2 software implements an age-structured population model that includes a wide range of population dynamics, parameter estimation, and model outputs. It can implement 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 can be used for quantitative assessments of marine populations, including fish, invertebrates, marine mammals, and seabirds.
GADGET is an extensive program that implements a wide range of options ranging from standard single species stock-assessments to ecosystem models. The current version 3 is programmed in TMB.
WAM is a state-space stock assessment model that explicitly deals with temporal variation in model parameters (e.g., recruitment, survival, and selectivity) within a random effects framework. SAM is used extensively for assessments in Europe under ICES.
Miller, T. J., Hare, J. A., and Alade, L. A. 2016. A state-space approach to incorporating environmental effects on recruitment in an age-structured assessment model with an application to Southern New England yellowtail flounder. Canadian Journal of Fisheries and Aquatic Sciences 73(8): 1261-1270. https://cdnsciencepub.com/doi/10.1139/cjfas-2015-0339
Stock, B. C., and Miller, T. J. 2021. The Woods Hole Assessment Model (WHAM): A general state-space assessment framework that incorporates time- and age-varying processes via random effects and links to environmental covariates. Fisheries Research, 240: 105967. https://www.sciencedirect.com/science/article/pii/S0165783621000953?via%3Dihub
The NOAA Fisheries Integrated Modeling System (FIMS) is a broad software system under development designed to support next-generation fisheries stock assessment, ecosystem, and socioeconomic modeling.