Otolith Weight as a Predictor of Age in Kokanee Salmon from Four Colorado Reservoirs

Estimating ages of individuals in fish populations is crucial for determining characteristics necessary to effectively manage sport fisheries. Currently, the most accepted approach for fish age determination is using thin sectioned otoliths for interpretation. This method is labor-intensive, requires extensive training, and subjectively determines age. Several studies have shown that otolith mass increases with age, yet use of otolith weights to determine fish age is relatively underutilized. However, determining fish age using otolith weight requires relatively little training, is relatively non-subjective, and is faster compared to other aging techniques. We collected kokanee salmon (Oncorhynchus nerka) in 2004 from four reservoirs, and from 2000 – 2009 in one reservoir, to evaluate the efficacy of using otolith weights to determine fish ages. We used a machine learning technique to predict kokanee salmon ages using otolith weight and various other covariates. Our findings suggest this method has potential to significantly reduce time and financial resources required to age fish. We conclude that using otolith weights to determine fish age may represent an efficient and accurate approach for some species.