The group's work is based on the development of methods to evaluate if the current sampling effort for biological parameters (and associated resources) can be optimized without compromising the quality of the final estimates.
The variety of methods considered are mainly based on historical sampling data and on bootstrap procedures. The R-tools application aims to facilitate the identification of alternative sampling strategies, evaluating their impact on biological estimators through appropriate quality indicators, and testing the different tools on a variety of case studies.
The group's work will result in the development of a concise R-package, which can be applied to define an optimal number for the different samples (e.g. number of trips, number of length measurements, maturity, age and sex). The result of those applications will be useful for the definition or revision of the data collection Work Plans, mainly fixing oversampling or avoiding inefficient sampling effort distribution that don't provide significant additional information for stock assessment.
