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Validating Atlantic salmon (Salmo Salar) scale reading by genetic parent assignment and PIT-tagging
Kjell Rong Utne1, Marine Servane Ono Brieuc1, Per Tommy Fjeldheim1
1Department of population genetics, Institute of Marine Research, Bergen, Norway.
Plos One
|May 9, 2025
Summary
This study validates Atlantic salmon (Salmo salar) aging using scales, finding high accuracy for sea-age but lower accuracy for freshwater-age. The validated dataset aids in improving salmon population assessments.
Area of Science:
- Ecology
- Fisheries Science
- Population Dynamics
Background:
- Accurate age determination is crucial for understanding Atlantic salmon population dynamics and survival rates.
- Traditional scale reading methods for aging salmon lack consistent validation with wild, age-verified individuals.
- Existing methods for estimating salmon age and growth require rigorous validation to ensure reliability.
Purpose of the Study:
- To assess the precision and bias of experienced readers in determining Atlantic salmon age from scales.
- To validate scale-based age estimates against known ages derived from PIT-tagging and genetic parentage.
- To evaluate the accuracy of back-calculated smolt lengths compared to direct measurements.
Main Methods:
- Utilized a unique dataset of 254 PIT-tagged Atlantic salmon with known sea-age and 81 with known freshwater-age.
- Employed three independent, experienced salmon scale readers to estimate ages and back-calculate lengths.
- Compared scale-derived ages and lengths against known ages and direct measurements for validation.
Main Results:
- Scale readers achieved 97.1% accuracy for sea-age and 71.7% for freshwater-age.
- Sea-age accuracy decreased for salmon with longer marine residency (≥2 years).
- Freshwater age did not impact scale reading accuracy; no systematic over- or underestimation was observed.
Conclusions:
- Scale reading is a reliable method for determining sea-age in Atlantic salmon, especially for shorter marine migrations.
- While freshwater-age estimation from scales is less accurate, it does not lead to significant misclassification by more than one year.
- The study provides a valuable, openly accessible dataset for training and validating salmon scale readers globally, enhancing fisheries management.
