Inferring Adult Status and Trends from Juvenile Density Data for Atlantic Salmon
Abstract Typically, juvenile survey data are not used explicitly to determine status, trends, or abundance designations for Atlantic salmon Salmo salar , even though they can be the only source of information for many populations. To determine whether juvenile data can be informative about adult abu...
Published in: | North American Journal of Fisheries Management |
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Main Authors: | , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2012
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Subjects: | |
Online Access: | http://dx.doi.org/10.1080/02755947.2012.720648 https://afspubs.onlinelibrary.wiley.com/doi/pdf/10.1080/02755947.2012.720648 |
Summary: | Abstract Typically, juvenile survey data are not used explicitly to determine status, trends, or abundance designations for Atlantic salmon Salmo salar , even though they can be the only source of information for many populations. To determine whether juvenile data can be informative about adult abundance and status in Atlantic salmon, we evaluated the similarities in trends among age‐classes for two data‐rich populations using a nested log‐linear model. We found relatively consistent and significant trends for the age‐0, adult and egg time series, but the trends in juvenile density data for older age‐classes were less consistent with adult abundance trends. A threshold‐based analysis demonstrated that relatively low misclassification rates for adult status relative to a set reference level could be obtained from juvenile density estimates. Together, these results suggest that juvenile density data can be an informative proxy for adult abundance and may be useful as an indicator for large changes in population status relative to reference points. This would make data collection via electrofishing an appropriate monitoring method for fisheries management or conservation programs. However, the validity of the idea that dramatic changes in adult abundance will be mirrored in juvenile data partially depends on the specific age‐classes monitored, the survey design, and the timing of density dependence in the population. Using juvenile data as an index would necessitate some prior knowledge of the underlying population dynamics before the method could be applied more generally. Received May 9, 2012; accepted August 8, 2012 |
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