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Estimating the number of fish in Atlantic bluefin tuna (Thunnus thynnus thynnus) schools using models derived from captive school observations
Hanrahan, B.; Juanes, F. (2001). Estimating the number of fish in Atlantic bluefin tuna (Thunnus thynnus thynnus) schools using models derived from captive school observations. Fish. Bull. 99(3): 420-431
In: Fishery Bulletin. US Government Printing Office: Washington, D.C.. ISSN 0090-0656, more
Peer reviewed article  

Available in Authors 

Keywords
    Abundance; Florida; Florida; Indexes; Indexes; Marine

Authors  Top 
  • Hanrahan, B.
  • Juanes, F.

Abstract
    Aerial photographic assessment is a promising technique that could be structured to yield a fishery-independent index of abundance for Atlantic bluefin tuna, Thunnus thynnus thynnus (ABT). The accuracy of this approach may be increased by incorporating the relationship between the surface characteristics of a school and the total number of individuals. Our objective was to develop models to facilitate the estimation of number of fish in ABT schools from aerial photographs.Video cameras were used to observe 74 incidences of schooling for 50 captive ABT approximately one meter in length. Relationships between the surface characteristics of ABT schools and the number of fish in the school were explored by using least-squares regression. The schools ranged in number from 2 to 45 individuals. A weighted regression model incorporating the number of fish in the school at the surface as the independent variable and the number of fish in the remaining portion of the school yielded an r(2) of 0.74. A second weighted multiple-regression model incorporating the number of fish in the school at the surface and in the second depth interval (0-25% school depth below surface layer) of the school as independent variables, and the number of fish in the remaining portion of the school as the dependent variable, with 1/variance as the weight, achieved an r(2) of 0.70. A third model using the length and width of the surface layer of the school as the independent variables and the number of fish in the school as the dependent variable had an r(2) of 0.86. One data point from a wild school is currently available to verify model predictions. This school of 125 individuals is well outside the range of school sizes used to construct the model (2-45 individuals), yet differs from model predictions by only 7%.We believe that these models have the potential to improve an abundance index based on aerial photographs by estimating the number of individuals in wild ABT schools from surface characteristics observed in aerial photographs.

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