Reliable assessment of fish origin is of critical importance for exploited species, since nursery areas must be identified and protected to maintain recruitment to the adult stock. During the last two decades, otolith chemical signatures (or "fingerprints") have been increasingly used as tools to discriminate between coastal habitats. However, correct assessment of fish origin from otolith fingerprints depends on various environmental and methodological parameters, including the choice of the statistical method used to assign fish to unknown origin. Among the available methods of classification, Linear Discriminant Analysis (LDA) is the most frequently used, although it assumes data are multivariate normal with homogeneous within-group dispersions, conditions that are not always met by otolith chemical data, even after transformation. Other less constrained classification methods are available, but there is a current lack of comparative analysis in applications to otolith microchemistry. Here, we assessed stock identification accuracy for four classification methods (LDA, Quadratic Discriminant Analysis [QDA], Random Forests [RF], and Artificial Neural Networks [ANN]), through the use of three distinct data sets. In each case, all possible combinations of chemical elements were examined to identify the elements to be used for optimal accuracy in fish assignment to their actual origin. Our study shows that accuracy differs according to the model and the number of elements considered. Best combinations did not include all the elements measured, and it was not possible to define an ad hoc multielement combination for accurate site discrimination. Among all the models tested, RF and ANN performed best, especially for complex data sets (e.g., with numerous fish species and/or chemical elements involved). However, for these data, RF was less time-consuming and more interpretable than ANN, and far more efficient and less demanding in terms of assumptions than LDA or QDA. Therefore, when LDA and QDA assumptions cannot be reached, the use of machine learning methods, such as RF, should be preferred for stock assessment and nursery identification based on otolith microchemistry, especially when data set include multispecific otolith signatures and/or many chemical elements.

Over the last three decades, the California sea hare, Aplysia californica, has played an increasingly important role as a model organism in the neurosciences. Since 1995, the National Resource for Aplysia has supported a growing research community by providing a consistent supply of laboratory-reared individuals of known age, reproductive status, and environmental history. The purpose of the present study was to resolve the key biological factors necessary for successful culture of large numbers of high quality larval Aplysia. Data from a sequence of five experiments demonstrated that algal diet, food concentration, and veliger density significantly affected growth, attainment of metamorphic competency, and survival of Aplysia larvae. The highest growth and survival were achieved with a mixed algal diet of 1:1 Isochrysis sp (TISO) and Chaetoceros muelleri (CHGRA) at a total concentration of 250 x 103 cells/mL and a larval density of 0.5 – 1.0 per mL. Rapid growth was always correlated with faster attainment of developmental milestones and increased survival, indicating that the more rapidly growing larvae were healthier. Trials conducted with our improved protocol resulted in larval growth rates of >14 μm/d, which yielded metamorphically competent animals within 21 days with survival rates in excess of 90%. These data indicate the important effects of biotic factors on the critical larval growth period in the laboratory and show the advantages of developing optimized protocols for culture of such marine invertebrates.

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From September through December 2001 to 2004, goliath grouper juveniles (15 to 87 mm standard length [SL]) were collected from tributary mouths in the Ten Thousand Islands region of southwest Florida's Gulf coast. These juveniles represent the smallest individuals of this species collected to date. These individuals were newly settled and showed only minor pigmentation. Descriptions and illustrations of juveniles between 15 and 38 mm SL are provided herein. Otolith analyses revealed a pelagic larval duration of 30 to 80 d with the potential for delayed larval metamorphosis. Based on back-calculation of daily rings, spawning generally occurred around the full moon, with settlement times irrespective of lunar phase. Length and age data provided the basis for the growth curve.