Kerr / Cadrin / Friedland Stock Identification Methods

Applications in Fishery Science
1. Auflage 2004
ISBN: 978-0-08-047043-6
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 736 Seiten, Web PDF

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.* 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

Autoren/Hrsg.

Kerr, Lisa A.

Cadrin, Steven X.

Friedland, Kevin D.

Mariani, Stefano

Waldman, John R.

Inhaltsverzeichnis

1;Cover;1
2;Annotated Table of Contents;4
3;Foreword by Michael Sissenwine;10
4;Contributors;12
5;PART I: Introduction;15
5.1;1. Stock Identification Methods: An Overview;17
5.2;2. Definition of Stocks: An Evolving Concept;21
5.3;3. Fish Migration and the Unit Stock: Three Formative Debates;31
5.4;4. Environmental and Genetic Influences on Stock Identification Characters;59
6;PART II: Life History Traits;101
6.1;5. The Use of Early Life Stages in Stock Identification Studies;103
6.2;6. Life History Parameters;133
7;PART III: Natural Marks„Morphological Analyses;165
7.1;7. Morphometric Landmarks;167
7.2;8. Morphometric Outlines;187
7.3;9. Analyses of Calcified Structures: Texture and Spacing Patterns;199
7.4;10. Meristics;211
8;PART IV: Natural Marks„Environmental Signals;223
8.1;11. Parasites as Biological Tags;225
8.2;12. Otolith Elemental Composition as a Natural Marker of Fish Stocks;241
8.3;13. Fatty Acid Profiles as Natural Marks for Stock Identification;261
9;PART V: Natural Marks„Genetic Analyses;285
9.1;14. Chromosome Morphology;287
9.2;15. Genetic Analysis: Allozymes;309
9.3;16. Mitochondrial DNA;325
9.4;17. Use of Nuclear DNA in Stock Identification: Single-Copy and Repetitive Sequence Markers;345
9.5;18. Random Amplified Polymorphic DNA (RAPD);385
9.6;19. Amplified Fragment Length Polymorphism (AFLP);403
10;PART VI: Applied Marks;427
10.1;20. Internal and External Tags;429
10.2;21. Electronic Tags;449
10.3;22. Otolith Thermal Marking;461
11;PART VII: Stock Identification Data Analysis;479
11.1;23. Experimental Design and Sampling Strategies for Mixed-Stock Analysis;481
11.2;24. An Introduction to Statistical Algorithms Useful in Stock Composition Analysis;513
11.3;25. Classical Discriminant Analysis, Classification of Individuals, and Source Population Composition of Mixtures;531
11.4;26. Neural Networks Used in Classification with Emphasis on Biological Populations;567
11.5;27. Maximum Likelihood Estimation of Stock Composition;585
11.6;28. Estimation of Movement from Tagging Data;605
12;PART VIII: Application of Stock Identification Data in Resource Management;621
12.1;29. Stock Identification for Conservation of Threatened or Endangered Species;623
12.2;30. The Role of Stock Identification in Formulating Fishery Management Advice;645
12.3;31. Identifying Fish Farm Escapees;673
13;Index;695