Stock Identification Methods: Applications in Fishery Science |
|
Editor:
| Cadrin, Steven X. Kerr, Lisa A. Mariani, Stefano |
ISBN: | 978-1-299-98119-5 |
Publication Date: | Jan 2013 |
Publisher: | Academic Press
|
Book Format: | Ebook |
List Price: | USD $119.94 |
Book Description:
|
"Stock Identification Methods, 2e, " continues to provide 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...
More Description
"Stock Identification Methods, 2e, " continues to provide 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, this valuable resource offers a unified framework for understanding stock structure by promoting an understanding of the relative merits and sensitivities of each approach.
* Describes 18 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