A temporal perspective on population structure and gene flow in Atlantic salmon (Salmo salar) in Newfoundland, Canada

2010 ◽  
Vol 67 (2) ◽  
pp. 225-242 ◽  
Author(s):  
Friso P. Palstra ◽  
Daniel E. Ruzzante

Studying population structure and gene flow patterns on temporal scales facilitates an evaluation of the consequences of demographic, physical, and environmental changes on the stability and persistence of populations. Here, we examine temporal genetic variation within and among Atlantic salmon ( Salmo salar ) rivers in Newfoundland and Labrador, Canada, using samples collected over a period of six decades (1951–2004). Our objective was to evaluate temporal changes in population connectivity associated with the closure of a commercial marine fishery. Despite demographic instability, we find that population structure remained temporally stable over more than 50 years. However, age structure can affect results when not taken into consideration, particularly in populations of large effective size where genetic drift is not strong. Where weak signals of genetic differentiation did not complicate analyses, contemporary migration was often asymmetric, yet low, suggesting patterns of intermittent gene flow. Nevertheless, we find some links between changes in population dynamics and contemporary gene flow. These findings may therefore imply that management decisions impacting the contemporary population dynamics of individual Atlantic salmon rivers can also affect the genetic stability of this species as a whole.

2005 ◽  
Vol 62 (1) ◽  
pp. 131-143 ◽  
Author(s):  
G. Chaput ◽  
C.M. Legault ◽  
D.G. Reddin ◽  
F. Caron ◽  
P.G. Amiro

Abstract The paper presents the data, the models, and the approach for the provision of management advice for a high seas mixed stock fishery on Atlantic salmon (Salmo salar L.). The approach incorporates observation errors, model uncertainty, and considers a possible shift in the productivity of Atlantic salmon. The risk analysis framework further incorporates uncertainty in the fishery harvest characteristics and presents the catch advice as probabilities of meeting or exceeding the conservation objectives relative to catch options. There is very strong evidence from the analyses that there has been a phase shift in productivity of Atlantic salmon of North American origin in the Northwest Atlantic. The change in productivity likely resulted from a change in marine survival which occurred in the early 1990s and has persisted to date. When the uncertainties in the input data are considered, the most parsimonious models suggest that there has been a shift in absolute abundance independent of variations in the spawner index contributing to the recruitment. There continues to be a large amount of uncertainty in the measures of abundance and population dynamics of Atlantic salmon. Uncertainty in the understanding of population dynamics does not necessarily equate to uncertainty in management advice. If model results suggest that spawning objectives are unattainable even when harvest rates are zero, then any harvest level will either accelerate the rate of decline if the model prediction is correct or diminish the probability of recovery if the model prediction is wrong.


1998 ◽  
Vol 55 (S1) ◽  
pp. 48-58 ◽  
Author(s):  
Elizabeth A Marschall ◽  
Thomas P Quinn ◽  
Derek A Roff ◽  
Jeffrey A Hutchings ◽  
Neil B Metcalfe ◽  
...  

We took a hierarchical approach to understanding Atlantic salmon (Salmo salar) life history patterns by first comparing salmonids to other teleosts, next comparing Atlantic salmon to other salmonids, and finally, mapping correlations among individual life history traits within Atlantic salmon. The combination of anadromy, large eggs, nest construction and egg burial by females, and large size at maturity differentiates salmonids from most other teleosts. Within the family Salmonidae, there is considerable variation in all traits but Atlantic salmon are generally in the middle of the range. Within Atlantic salmon, we were able to map correlations among individual life history traits, but we found that we still lacked an understanding comprehensive and quantitative enough to allow us to predict how the entire life history should respond to environmental changes. Thus, we proposed several general courses of action: (i) use models to synthesize complex patterns and relationships, (ii) collect long time series of data in individual systems, and (iii) design experiments to assess phenotypic plasticity and how environmental influences differ from genetic effects and constraints.


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