Inter-american Tropical Tuna Commission Workshop on Spatial Analysis for Stock Assessment

A new feature extraction method for very non-normal data: analysis of multivariate species-size data from a tuna purse-seine fishery .. This report is organized into sections corresponding to the topics discussed at the workshop. Under each section, introductory text, taken from the background information provided to participants before the workshop, is given. Then abstracts for each presentation are provided. Finally, the discussions during the workshop about the focus questions are summarized. The report does not represent the consensus of the opinions of the workshop participants. 1. INTRODUCTION It is clearly evident that stock and fishery dynamics vary spatially, and this variability should be considered in the assessment and management of fish stocks. As data collection methods improve, more fine-scale spatial data become available. These data can be analyzed to get a better understanding of the spatial variability of stock and fishery dynamics. Management strategies can then be designed to either exploit this spatial variability or to be robust to it, depending on the situation. Currently, few stock assessment models directly address spatial variability, and methods need to be developed to improve this situation. In the simplest form, stock assessment models either model spatial variability by separating fisheries into areas so that catchability and selectivity can differ or model each sub-stock separately. More complex models explicitly model separate sub-stocks and movement among them. These models are usually based on large areas, and do not model differences in biological parameters (e.g. growth) among areas. To aid in the development of spatially-explicit stock assessments, methods are needed to determine the appropriate spatial scales for separating stocks, sub-stocks, fisheries, or other factors included in the spatially-explicit stock assessment models. The goals of the workshop are to provide a forum to discuss the state of the art in spatial analysis in fisheries stock assessment and how it can be improved, and to motivate more applications.