This session will take a comprehensive look at fishery stock assessments, fostering awareness and understanding of recent advances and new assessment techniques, discussing and improving the ability to make decisions about which model, or suite of models, is sufficient for a particular stock and situation, and highlighting methods and approaches to quantify and communicate uncertainty at all steps of the fishery advisory process.
Fishery stock assessments are an applied science that is fundamental to sustainable fishery management. Recent advances in stock assessment methods include integrated models with time-varying processes, spatially explicit approaches, state-space algorithms, inclusion of multispecies and environmental processes as well as economic factors, techniques for data-limited situations, and rigorous evaluations of management strategies.
Choosing a model structure and assumptions has a direct effect on the management advice, where the appropriate model complexity is based on the data collected, findings from simulation analyses, and available expertise. Conversely, determining an appropriate model structure may help to guide investments in data collection and analytical capacity. Thus, determining the level of assessment complexity is an important decision in the fishery management process. Model ensembles offer a way to base the management advice on a spectrum of model structures and assumptions.
The final step in a stock assessment is effective communication of the main results, along with the corresponding uncertainties. Quantifying the uncertainty about stock status and catch forecasts is a challenge because of the accumulating sources of uncertainty in the observed data and analytical assumptions, as well as the intrinsic variability in the biological and human components.
Scientific advice should help stakeholders and managers to understand uncertainty, trade-offs, and risks, so management policies for each stock can incorporate the desired precaution.
The session will be organized around three themes:
State of the art in stock assessment methods
- improvements in stock assessment methods, implementation of random effects in time and space, analytical methods for data-limited situations;
- performance evaluation (e.g. MSE) of assessment methods and harvest policies; and
- multispecies and environmental processes in stock assessment, ecosystem and economic factors in harvest policy evaluation
Stock assessment model complexity and model ensemble techniques
- appropriate complexity of an assessment model for a given stock, basis of choosing a model, implications for data collection;
- application of model ensemble techniques in stock assessment; and
- performance of model ensemble, when applied to historical datasets
and simulated data
Quantifying and communicating uncertainties in stock assessment
- quantifying uncertainties in fisheries catch statistics and survey data, assessment model choices and assumptions;
- developing harvest control rules, evaluating management strategies;
- quantifying overall uncertainty at the advice level, communication of uncertainties, interpretation of advice
For each theme there will be an invited keynote presentation, followed by submitted presentations. Poster authors will be asked to give speed-presentations of their posters. Group discussions from each theme will be presented in a plenary final discussion.
