Stock Identification Methods

Stock Identification Methods : Applications in Fishery Science

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Description

Stock Identification Methods provides a comprehensive review of the various disciplines used to study the population structure of fishery resources. It represents the worldwide experience and perspectives of experts on each method, assembled through a working group of the International Council for the Exploration of the Sea. The book is organized to foster interdisciplinary analyses and conclusions about stock structure, a crucial topic for fishery science and management.

Technological advances have promoted the development of stock identification methods in many directions, resulting in a confusing variety of approaches. Based on central tenets of population biology and management needs, Stock Identification Methods offers a unified framework for understanding stock structure by promoting an understanding of the relative merits and sensitivities of each approach.
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Product details

  • Hardback | 736 pages
  • 154.9 x 228.6 x 40.6mm | 1,043.27g
  • Academic Press Inc
  • San Diego, United States
  • English
  • Revised
  • 2nd Revised edition
  • Approx. 150 illustrations
  • 012154351X
  • 9780121543518

About Lisa A. Kerr

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.
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Table of contents

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
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