A simple method of tagging prawns

The recognition of individual animals is crucial to many aspects of research. Prawns (Penaeus monodon) present unique difficulties in this respect since they molt regularly. Thus, almost all tagging and marking methods developed for prawns so far have proven inadequate. Some tags or marks are lost during molting; others cause injury to the prawns. A new and efficient method has been developed at the Igang Seafarming Station of the Aquaculture Department. Rectangular brass tags measuring 5 mm by 20 mm and numbered consecutively are used. The prawn is held gently but firmly at the base of the carapace with the left hand while the right hand slips the brass tag around the stalk of the unablated eye and presses the tag gently. All tagging must be made under water to avoid stress. From May 29 to September 7 1977 to a total of 348 unilaterally-ablated adult female prawns were tagged on the unablated eyestalk in 5 batches to enable individual observations on gonadal maturation, molting, and growth. Periodic examinations were made four times a month to coincide with the different phases of the lunar cycle. On each examination, survival and recovery rates were recorded. The data included death due to immediate mortality during ablation and loss to cannibalism for the duration of the experiments. In all five tagging experiments, most of the prawns recovered had their tags intact. These included even dead and molting animals. The eyestalk tagging method is suitable for prawns because the tags can be attached without causing injury and has no effect on the rate of growth, maturity, molting and behavior of the animal. The tags are identifiable and permanent; they remain attached to the animal even after death.

Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast

Without knowledge of basic seafloor characteristics, the ability to address any number of critical marine and/or coastal management issues is diminished. For example, management and conservation of essential fish habitat (EFH), a requirement mandated by federally guided fishery management plans (FMPs), requires among other things a description of habitats for federally managed species. Although the list of attributes important to habitat are numerous, the ability to efficiently and effectively describe many, and especially at the scales required, does not exist with the tools currently available. However, several characteristics of seafloor morphology are readily obtainable at multiple scales and can serve as useful descriptors of habitat. Recent advancements in acoustic technology, such as multibeam echosounding (MBES), can provide remote indication of surficial sediment properties such as texture, hardness, or roughness, and further permit highly detailed renderings of seafloor morphology. With acoustic-based surveys providing a relatively efficient method for data acquisition, there exists a need for efficient and reproducible automated segmentation routines to process the data. Using MBES data collected by the Olympic Coast National Marine Sanctuary (OCNMS), and through a contracted seafloor survey, we expanded on the techniques of Cutter et al. (2003) to describe an objective repeatable process that uses parameterized local Fourier histogram (LFH) texture features to automate segmentation of surficial sediments from acoustic imagery using a maximum likelihood decision rule. Sonar signatures and classification performance were evaluated using video imagery obtained from a towed camera sled. Segmented raster images were converted to polygon features and attributed using a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999) for use in a geographical information system (GIS). (PDF contains 41 pages.)

The use of agreement measures and latent class models to assess the reliability of classifying thermally marked otoliths

Otolith thermal marking is an efficient method for mass marking hatchery-reared salmon and can be used to estimate the proportion of hatchery fish captured in a mixed-stock fishery. Accuracy of the thermal pattern classification depends on the prominence of the pattern, the methods used to prepare and view the patterns, and the training and experience of the personnel who determine the presence or absence of a particular pattern. Estimating accuracy rates is problematic when no secondary marking is available and no error-free standards exist. Agreement measures, such as kappa (κ), provide a relative measure of the reliability of the determinations when independent readings by two readers are available, but the magnitude of κ can be influenced by the proportion of marked fish. If a third reader is used or if two or more groups of paired readings are examined, latent class models can provide estimates of the error rates of each reader. Applications of κ and latent class models are illustrated by a program providing contribution estimates of hatchery-reared chum and sockeye salmon in Southeast Alaska.