AbstractStudies to determine precision and bias of both methods and age-readers are important to evaluate reliability of age data used for developing fisheries management objectives. We assessed within-reader, between-reader, and between-method precision (coefficient of variation, CV%) and bias of age estimations for long-lived lake trout, Salvelinus namaycush, from Great Bear Lake using three readers with different levels of experience. The assessment used independent age estimates (n = 3 per reader) from whole and transverse-sectioned otoliths (range = 1–67 years), and pelvic fin-ray sections (range = 3–26 years). We also examined between-method differences in assigned confidence scores. Within readers, age estimates from sectioned otoliths were more precise (2.6–3.0%) than whole (3.6–4.5%) otoliths. Between whole and sectioned otoliths, precision of age estimates was 5.4% and bias was low up to age 20. Age was typically under-estimated from whole otoliths compared to sections for fish ≥ 34 years. Increased reader confidence was correlated with greater precision and younger age estimates, particularly for whole otoliths, but less so for fin rays. Age was estimated with higher confidence from otolith sections than other methods. The least experienced reader estimated age with the lowest precision, and between-reader bias was evident among older ages. Age was consistently under-estimated and less precise from pelvic fins compared to sectioned otoliths, and are therefore an unsuitable non-lethal alternative. Sectioned otoliths revealed longevity was greater (67 years) than historically documented using whole otoliths (53 years) for these fish. Our findings contribute to those relying on otoliths or pelvic fin rays to estimate ages of long-lived lake trout populations, which are a key component of freshwater fauna in polar North America.
Microsatellite and mtDNA analysis of lake trout,Salvelinus namaycush, from Great Bear Lake, Northwest Territories: impacts of historical and contemporary evolutionary forces on Arctic ecosystems