Optimal estimation of catch by the continuous underway fish egg sampler based on a model of the vertical distribution of American plaice (Hippoglossoides platessoides) eggs

Abstract

Abstract Pepin, P., Curtis, K.A., Snelgrove, P.V.R., de Young, B., and Helbig, J.A. 2007. Optimal estimation of catch by the continous underway fish egg sampler based on a model of the vertical distribution of American plaice (Hippoglossoides platessoides) eggs – ICES Journal of Marine Science, 64, 18–30. We investigate how the vertical stratification of the water column (specifically density) affects predictions of the catch of American plaice eggs (Hipploglossoides platessoides) from a fixed-depth sampler [the continuous underway fish egg sampler (CUFES)] relative to the integrated abundance in the water column measured in bongo tows. A steady-state model of the vertical distribution of fish eggs coupled with a simple model of the vertical profile of eddy diffusivity (i.e. mixing) is applied. Key model parameters are estimated through optimization of a one-to-one relationship between predicted and observed catches fit, using a generalized linear model with a Poisson, negative binomial, or gamma error structure. The incorporation of data on the vertical structure of the water column significantly improved the ability to forecast CUFES catches when using Poisson or negative binomial error structure, but not using a gamma distribution. Optimal maximum likelihood parameter estimates for eddy diffusivity and egg buoyancy fell within the range of expected values. The degree of uncertainty in the parameterization of eddy diffusivity suggests, however, that greater understanding of the forces that determine the vertical profile of mixing is critical to achieving strong predictive capabilities. The inverse problem of predicting integrated abundance from CUFES catches did not benefit from the environmental-driven model because of the high uncertainty in the catches from the CUFES.