INDIVIDUAL-BASED MODEL FOR GROWTH OF YOUNG-OF-THE-YEAR WALLEYE - A PIECE OF THE RECRUITMENT PUZZLE

Authored by Charles P Madenjian, Stephen R Carpenter

Date Published: 1991

DOI: 10.2307/1941756

Sponsors: Federal Aid in Sport Fish Restoration Program

Platforms: No platforms listed

Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

Young-of-the-year (YOY) walleye (Stizostedion vitreum vitreum) growth is a vital step in walleye recruitment. An individual-based model (IBM) was developed to describe the growth of YOY walleye in Oneida Lake (New York, USA) and Lake Mendota (Wisconsin, USA). In Oneida Lake the only prey species included in the model was yellow perch (Perca flavescens), whereas both yellow perch and bluegill (Lepomis macrochirus) were prey species in the model for Lake Mendota. IBM predictions for length frequencies of the YOY walleye population at the end of the growing season showed good agreement with observed length frequencies. A theoretical relationship was derived between the encounter rate, lambda, used in the IBM and the half-saturation constant, kappa, used in a type 11 functional response model. Estimates of kappa from the two models showed good agreement, thus corroborating the value of lambda-chosen for the IBM application to Oneida Lake. The mean length of the YOY walleye cohort and the percentage of larger (greater-than-or-equal-to 175 mm in total length) walleyes in the cohort at the end of the growing season were most sensitive to gross growth efficiency, bioenergetics parameters for maximum daily consumption by walleyes, and the ratio of prey length to predator length at which the prey is susceptible to predation. In Lake Mendota the vulnerability of bluegills to predation by YOY walleyes was especially important in determining the growth of walleyes during their first growing season. The IBM approach was valuable for modeling those stages of life history in which characteristics of the individual were critical in determining recruitment.

Tags

Sensitivity Analysis Stizostedion-vitreum-vitreum Oneida lake New-york Yellow perch Perch perca-flavescens Smallmouth bass Food-consumption Error analysis Computer-models