2017
DOI: 10.1016/j.fishres.2016.09.012
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Accurate aging of juvenile salmonids using fork lengths

Abstract: Juvenile salmon life history strategies, survival, and habitat interactions may vary by age cohort. However, aging individual juvenile fish using scale reading is time consuming and can be error prone. Fork length data are routinely measured while sampling juvenile salmonids. We explore the performance of aging juvenile fish based solely on fork length data, using finite Gaussian mixture models to describe multimodal size distributions and estimate optimal agediscriminating length thresholds. Fork length-based… Show more

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Cited by 13 publications
(14 citation statements)
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“…Larval lamprey were aged based on established length–frequency distributions (Sethi et al, ). Aging error, particularly in tributaries of low productivity, can lead to individuals from multiple year cohorts being assigned to a single‐year class (Dawson et al, ).…”
Section: Discussionmentioning
confidence: 99%
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“…Larval lamprey were aged based on established length–frequency distributions (Sethi et al, ). Aging error, particularly in tributaries of low productivity, can lead to individuals from multiple year cohorts being assigned to a single‐year class (Dawson et al, ).…”
Section: Discussionmentioning
confidence: 99%
“…Samples (whole body) were stored in 95% ethanol and delivered to the laboratory at Michigan State University (MSU). In the laboratory, we measured body length for each individual from DC and used a mixture of four Gaussian distributions to group larval body lengths into age 0, age 1, and age 2, age 3+ years (Sethi, Gerken, & Ashline, 2017). We used the DC length-frequency distributions to age larvae from the SCR because of small sample size (Table 1).…”
Section: Sample Field Collectionsmentioning
confidence: 99%
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“…The proportions of tagged fish across overwinter locations were calculated for each year and age class. Fish were aged as young of year (hatched in spring in a sampling year) or age 1+ (one or more years in fresh water) from fork length measurements at the time of capture for tagging based upon age‐discriminating size thresholds calculated following methods in Sethi, Gerken & Ashline (2017) and Gerken & Sethi (2013). For tracked fish that engaged in overwinter migrations, the distance travelled was calculated as the river network distance between the specimen’s inferred summer rearing location (i.e.…”
Section: Methodsmentioning
confidence: 99%
“…Mixture models have become popular for discriminating distinct modal groups in biological size-frequency datasets, e.g. Laslett et al [51] and Sethi et al [52]. They determine the most likely number of modes in a length-frequency dataset (among many theoretical permutations of modal number) using model performance estimates and then use optimization algorithms to fit one or more Gaussian distribution curves to the data around these modes.…”
Section: Methodsmentioning
confidence: 99%