Individual-Based Model of Yellow Perch and Walleye Populations in Oneida Lake

Abstract

Predator–prey dynamics and density dependence are fundamental issues in ecology. We use a detailed, individual‐based model of walleye and yellow perch to investigate the effects of alternative prey and compensatory responses on predator and prey population dynamics. Our analyses focus on the numerical and developmental responses of the predator, rather than the traditional emphasis on functional responses. The extensive database for Oneida Lake, New York, USA was used to configure the model and ensure its realism. The model follows the daily growth, mortality, and spawning of individuals of each species through their lifetime. Three ecologically distinct periods in the history of Oneida Lake were simulated: baseline, high mayfly densities, and high forage fish densities. Mayflies and forage fish act as alternative prey for walleye. For model corroboration, the three periods were simulated sequentially as they occurred in Oneida Lake. Model predictions of abundances, size at age, and growth and survival rates compared favorably with Oneida Lake data. Three hypotheses suggested by the data were evaluated: alternative prey stabilizes yellow perch and walleye populations; alternative prey increases yellow perch and walleye recruitment; and density‐dependent growth and survival compensate for changes in young‐of‐the‐year mortality. Model simulations were performed under increased mayfly densities, increased forage fish densities, and increased egg mortality rates. Predicted recruitment and population stability depended on the magnitude of increased walleye prey and differed between mayflies and forage fish. Compensation was driven by density‐dependent growth, resulting in younger age at maturation and increased fecundity. We compare our results using a detailed, size‐structured model capable of numerical and developmental responses of predators to results from classical predator–prey theory. Weaknesses in the current version of the individual‐based model and knowledge gaps that require additional empirical data collection are also discussed.

Effects of Simulated Angler Capture and Live‐Release Tournaments on Walleye Survival

“…• C optimum and preferred temperatures of adult Walleyes (Coutant 1977;Christie and Regier 1988;Rose et al 1999). The significantly lower survival of fish that were acclimated to 18…”

Contribution of individual-based coupled physical–biological models to understanding recruitment in marine fish populations

“…However, none specifically tested classical hypotheses related to the determination of year class strength. If ICPBMs are to be used to test such hypotheses, it is critical that they are developed as a part of whole life cycle models as has been accomplished by Rose and colleagues in the ecological literature using either solely IBMs (Rose et al 1999b) or IBMs as a component in a nested modeling approach (Rose et al 2003). Development of a nested modeling approach to addressing biological oceanographic questions generally would likely be most effective for recruitment questions (deYoung et al 2004).…”

“…However, this should not be a barrier to the inclusion of predators in ICPBMs. Predators have been included in spatially explicit IBMs in the ecological field (Rose et al 1999b). Inclusion of predation will require consideration of whether and how potential predators respond to the distribution of the eggs and larvae modeled in the ICPBM and may require inclusion of alternative prey.…”

Application of a bioenergetics growth model for European anchovy (Engraulis encrasicolus) linked with a lower trophic level ecosystem model

“…However, it must be noted that according to recent studies concerning E. capensis (Huggett et al, 2003;Van der Lingen et al, 2006), E. encrasicolus and E. capensis must be considered as a single species (E. encrasicolus). Further data gaps were filled with parameter values from related species (Vasquez, 1989;Luo & Brandt, 1993;Rose et al, 1999) and NEMURO.FISH model (Ito et al, 2004;Megrey et al, 2007).…”