Many criteria for statistical parameter estimation, such as maximum likelihood, are formulated as a nonlinear optimization problem. Automatic Differentiation Model Builder (ADMB) is a programming framework based on automatic differentiation, aimed at highly nonlinear models with a large number of parameters. The benefits of using AD are computational efficiency and high numerical accuracy, both crucial in many practical problems. We describe the basic components and the underlying philosophy of ADMB, with an emphasis on functionality found in no other statistical software. One example of such a feature is the generic implementation of Laplace approximation of high-dimensional integrals for use in latent variable models. We also review the literature in which ADMB has been used, and discuss future development of ADMB as an open source project. Overall, the main advantages of ADMB are flexibility, speed, precision, stability and built-in methods to quantify uncertainty.

Interpretation of data used in fisheries assessment and management requires knowledge of population (e.g. growth, natural mortality, and recruitment), fisheries (e.g. selectivity), and sampling processes. Without this knowledge, assumptions need to be made, either implicitly or explicitly based on the methods used. Incorrect assumptions can have a substantial impact on stock assessment results and management advice. Unfortunately, there is a lack of understanding of these processes for most, if not all, stocks and even for processes that have traditionally been assumed to be well understood (e.g. growth and selectivity). We use information content of typical fisheries data that is informative about absolute abundance to illustrate some of the main issues in fisheries stock assessment. We concentrate on information about absolute abundance from indices of relative abundance combined with catch, and age and length-composition data and how the information depends on knowledge of population, fishing, and sampling processes. We also illustrate two recently developed diagnostic methods that can be used to evaluate the absolute abundance information content of the data. Finally, we discuss some of the reasons for the slowness of progress in fisheries stock assessment.

Fisheries have removed at least 50 million tons of tuna and other top-level predators from the Pacific Ocean pelagic ecosystem since 1950, leading to concerns about a catastrophic reduction in population biomass and the collapse of oceanic food chains. We analyzed all available data from Pacific tuna fisheries for 1950–2004 to provide comprehensive estimates of fishery impacts on population biomass and size structure. Current biomass ranges among species from 36 to 91% of the biomass predicted in the absence of fishing, a level consistent with or higher than standard fisheries management targets. Fish larger than 175 centimeters fork length have decreased from 5% to approximately 1% of the total population. The trophic level of the catch has decreased slightly, but there is no detectable decrease in the trophic level of the population. These results indicate substantial, though not catastrophic, impacts of fisheries on these top-level predators and minor impacts on the ecosystem in the Pacific Ocean.

Punt, A. E., Huang, T., and Maunder, M. N. 2013. Review of integrated size-structured models for stock assessment of hard-to-age crustacean and mollusc species. – ICES Journal of Marine Science, 70:16–33. Crustaceans and molluscs such as crabs, rock lobsters, prawns, abalone, and oysters constitute large and valuable fisheries. However, assessments of these species are hampered because they cannot be production aged, in contrast to many teleosts. The major data sources for these species, in addition to catch and abundance index data, are the size compositions of the catches and of any fishery-independent indices. Assessments of such species have been conducted using age-based methods of stock assessment, as well as surplus production models. However, size-structured methods are now preferred because they can make full use of size-composition data, are able to integrate multiple sources of data, and produce the types of outputs which are needed for management purposes. An advantage of size-based models over age-based models is that all processes can be size-based, and these processes can modify the (unmodelled) size-at-age distribution. We review these methods, highlighting the choices that need to be made when developing integrated size-structured stock assessments, the data sources which are typically available and how they are used for parameter estimation, and contrast a number of such assessments worldwide.