Abstract
Fishery managers need robust ways of objectively estimating the quantitative composition of fish stocks, by species and age-class, from representative samples of populations. Dual-frequency identification sonar data were used to first visually identify fish to a broad taxon (Salmonidae). Subsequently, kernel-density estimations, based on calibrated size-at-age data for the possible component species, were used to assign sonar observations both to species (Atlantic Salmon Salmo salar or Brown Trout Salmo trutta) and age-classes within species. The calculations are illustrated for alternative sets of calibration data. To obtain close and relevant fits, the approach fundamentally relies on having accurate and fully representative subcomponent distributions. Firmer inferences can be made if the component data sets correspond closely to the target information in both time and space. Given carefully chosen suites of component data, robust population composition estimates with narrow confidence intervals were obtained. General principles are stated, which indicate when such methods might work well or poorly.
Received September 2, 2013; accepted October 30, 2013
ACKNOWLEDGMENTS
We thank Tiernan Henry (National University of Ireland, Galway) for helpful discussions and Nigel Bond (Marine Institute) for technical assistance during DIDSON operations. Declan Cooke kindly collected the salmon scales from the Moy. Funding for L.B.'s Ph.D. was provided by the Marine Institute and the Marine Research, Technology, Development, and Innovation (RTDI) Measure, Productive Sector Operational Programme, National Development Plan 2000–2006 (Grant-aid Agreement PhD/05/001). Equipment for the study (DIDSON dual frequency identification sonar) was purchased with the support of the Marine Institute and the Marine RTDI Measure, Productive Sector Operational Programme, National Development Plan 2000–2006, cofinanced under the European Regional Development Fund.
P.McG. was part supported by the Beaufort Marine Research award in Fish Population Genetics funded by the Irish Government under the Sea Change Programme.
Notes
Both the univariate and bivariate parameter estimates are illustrated below (see Figure 7).