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A standardized method and analytical approach for predicting female reproductive stage in teleosts by using ovary color and female characteristics.
Determining and understanding patterns in the reproductive status of fishes are essential for assessing individual and population reproductive potential. The least biased method for determining reproductive stage is through the use of ovarian histology; however, this method can be time consuming and expensive. To overcome these restrictions, we developed models to predict the reproductive stage of female striped bass Morone saxatilis by using ovary color and other female characteristics. We provide a standardized and calibrated method for quantifying ovary color, and we outline an analytical approach that utilizes binary and ordinal logistic regression. Our results indicated that binary models had high accuracy (<6% error) in distinguishing between the regressing phase (i.e., recently spawned) and the nonregressing phase (i.e., all other reproductive phases); we found even better accuracy (4% error) for ordinal models in discriminating among four nonregressing reproductive phases. All of the best-fitting models required the inclusion of an ovary color variable and ovary energy density; however, good predictive accuracy was also obtained when we replaced ovary energy density with ovary percent water to produce models requiring minimal laboratory processing time and cost. Although tested on striped bass, our method could be used to develop similar models for other species.
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