Resumen
Management of Atlantic salmon populations has for decades been carried out in the near absence of quantitative information, except in a few cases. Since the 1960s an increasing number of rivers have been monitored for the number of upmigrating spawners and outmigrating smolts. We are now in the position to capitalise on the quantitative information accumulated by this monitoring. This chapter describes methods for modelling relationships between spawning stock and recruitment in the subsequent generation, and how to extract information on conservation limits and spawning targets from the models. We review spatial and temporal variation in stock-recruitment relationships, assess uncertainties in deriving spawning targets from data-rich populations, and review suggestions for transferring spawning targets from data-rich to data-poor populations. Even for well studied rivers, the uncertainties in setting spawning targets are pronounced. This is a challenge for management as there is usually limited opportunity to obtain precise information on pre-fishery abundance, and limited understanding of variation in exploitation rates. We describe how fishing for Atlantic salmon has moved from fresh water into sea water and back into fresh water through history, and show how fishing can have evolutionary and ecological consequences for harvested populations. We end by discussing some of the management implications of the current knowledge on stock-recruitment relationships and exploitation. The overriding challenge is to apply the increasing knowledge to securing viable populations of Atlantic salmon in an era of declining population sizes.
Idioma original | English |
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Título de la publicación alojada | Atlantic Salmon Ecology |
Editorial | wiley |
Páginas | 299-331 |
Número de páginas | 33 |
ISBN (versión digital) | 9781444327755 |
ISBN (versión impresa) | 9781405197694 |
DOI | |
Estado | Published - ene. 1 2011 |
Nota bibliográfica
Publisher Copyright:© 2011 by Blackwell Publishing Ltd. All rights reserved.
ASJC Scopus Subject Areas
- General Engineering
- General Agricultural and Biological Sciences