4.7 Article

Modeling larval fish behavior: Scaling the sublethal effects of methylmercury to population-relevant endpoints

Journal

AQUATIC TOXICOLOGY
Volume 86, Issue 4, Pages 470-484

Publisher

ELSEVIER
DOI: 10.1016/j.aquatox.2007.12.009

Keywords

methylmercury; predator-prey interactions; individual-based model; regression tree; larval fish; Behavior; population-level effects

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Expressing the sublethal effects of contaminants measured on individual fish as cohort and population responses would greatly help in their interpretation. Our approach combines laboratory studies with coupled statistical and individual-based models to simulate the effects of methylmercury (MeHg) on Atlantic croaker larval survival and growth. We used results of video-taped laboratory experiments on the effects of MeHg on larval behavioral responses to artificial predatory stimuli. Laboratory results were analyzed with a regression tree to obtain the probability of control and MeHg-exposed larvae escaping a real predatory fish attack. Measured changes in swimming speeds and regression tree-predicted escape abilities induced by MeHg exposure were then inputted into an individual-based larval fish cohort model. The individual-based model predicted larval-stage growth and survival under baseline (control) conditions, and low- and high-dose MeHg exposure under two alternative predator composition scenarios (medusa-dominated and predatory fish-dominated). Under MeHg exposure, stage survival was 7-19% of baseline (control) survival, and the roughly 33-day stage duration was extended by about 1-4 days. MeHg effects on larval growth dominated the response under the medusa-dominated predator composition, while predation played a more important role under the fish-dominated predator composition. Simulation results suggest that MeHg exposures near extreme maximum values observed in field studies can have a significant impact on larval cohort dynamics, and that the characteristics of the predator-prey interactions can greatly influence the underlying causes of the predicted responses. (c) 2007 Elsevier B.V. All rights reserved.

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