Validation of otolith ages for walleye (Sander vitreus) in the Winnebago System

Precision and Bias in Aging Northern Pike: Comparisons among Four Calcified Structures

“…However, in our 2 years of field work conducted during spring migrations in six watersheds, we encountered only 16 fish (out of 252 fish sampled) that were larger than 890 mm TL. It is possible that the Northern Pike population in Green Bay sustains sufficient growth rates to allow detection of clear annuli throughout much of their life span; we did not observe the substantial annulus crowding that is typical for the outer annuli of the oldest individuals in a population due to decreases in growth rate with age (e.g., Welch et al 1993;Koenigs et al 2015). We suspect that the observed patterns of among-reader precision and bias would persist into the oldest segments of the population, but to confirm this, it would be ideal to include older individuals.…”

Polychlorinated biphenyl exposure and fish recruitment from 1988 to 2002 in the upper Hudson River, New York, USA

“…Residuals about a catch-curve regression have been shown to be related to the formation of strong and weak year classes of fish (Maceina, 1997), which allows examination of historical trends in recruitment (Isermann et al, 2002;Allen et al, 2003;Maceina, 2004;Bonvechio and Allen, 2005;Smith et al, 2005;Koenigs et al, 2015). Formation of strong and weak year classes will also affect the slope of the catch-curve regression, hence survival.…”

Comparison of Two Viewing Methods for Estimating Largemouth Bass and Walleye Ages from Sectioned Otoliths and Dorsal Spines

“…Fish age estimation is a fundamental step in monitoring and managing fish populations (Beamish and McFarlane 1983;Leaman and Beamish 1984). Ages are typically estimated from calcified structures (e.g., scales, spines, otoliths, and cleithra) by enumerating annuli while directly viewing these structures with the naked eye (Phelps et al 2007;Faust et al 2013) or using a microscope or other device to magnify the structure (Erickson 1983;Isermann et al 2003;Koenigs et al 2015). Advancements in technology and subsequent reductions in cost have resulted in the increased use of digital images in the age estimation process (Santamaria et al 2009;Hansen et al 2012;Koenigs et al 2015).…”

“…Ages are typically estimated from calcified structures (e.g., scales, spines, otoliths, and cleithra) by enumerating annuli while directly viewing these structures with the naked eye (Phelps et al 2007;Faust et al 2013) or using a microscope or other device to magnify the structure (Erickson 1983;Isermann et al 2003;Koenigs et al 2015). Advancements in technology and subsequent reductions in cost have resulted in the increased use of digital images in the age estimation process (Santamaria et al 2009;Hansen et al 2012;Koenigs et al 2015). Digital images require less space for archiving structures, allow multiple readers to estimate ages for the same sample of fish without direct transfer of the physical structures, and allow for use of computer programs that can be used to automate the identification and enumeration of annuli (Welleman and Storbeck 1995;Morison et al 1998;Takashima et al 2000) or to expedite measurement of growth increments for back-calculation of fish growth (Santamaria et al 2009;Hansen et al 2012).…”

“…Only one previous assessment has included Largemouth Bass with known ages of 10 and older (Buckmeier and Howells 2003), and those fish were reared in ponds at a Texas hatchery. Only a single assessment has included partially known-age Walleyes of ages 10 and older from a population in Wisconsin (Koenigs et al 2015).…”