Introduction Life History Traits Natural Marks-Morphological Analyses Natural Marks-Environmental Signals Natural Marks-Genetic Analyses Applied Marks Stock Identification Data Analysis Application of Stock Identification Data in Resource Management
* Describes eighteen distinct approaches to stock identification grouped into sections on life history traits, environmental signals, genetic analyses, and applied marks * Features experts reviews of benchmark case studies, general protocols, and the strengths and weaknesses of each identification method * Reviews statistical techniques for exploring stock patterns, testing for differences among putative stocks, stock discrimination, and stock composition analysis * Focuses on the challenges of interpreting data and managing mixed-stock fisheries
Lisa Kerr is a fisheries ecologist at the Gulf of Maine Research Institute (Portland, ME). Lisa is broadly interested in understanding the structure and dynamics of fish populations, with the goal of enhancing our ability to sustainably manage fisheries and ecosystems as a whole. She is particularly motivated to identify complex stock structure and understand the role it plays in the stability and resilience of local and regional populations. Lisa employs a diverse skill set to address critical ecological questions related to population structure that are also directly applicable to fisheries management. Her expertise includes structural analysis of fish hard parts (e.g. otoliths, vertebrae) and the application of the chemical methods (stable isotope, radioisotope, and trace element analysis) to these structures. She also uses mathematical modeling as a tool to understand how biocomplexity within fish stocks (e.g., spatial structure, connectivity, life cycle diversity) impacts their response to natural climatic oscillations, climate change, fishing, and management measures.