Effect of type of otolith and preparation technique on age estimation of larval and juvenile spot (Leiostomus xanthurus)

Otoliths of larval and juvenile fish provide a record of age, size, growth, and development (Campana and Neilson, 1985; Thorrold and Hare, 2002). However, determining the time of first increment formation in otoliths (Campana, 2001) and assessing the accuracy (deviation from real age) and precision (repeatability of increment counts from the same otolith) of increment counts are prerequisites for using otoliths to study the life history of fish (Campana and Moksness, 1991). For most fish species, first increment deposition occurs either at hatching, a day after hatching, or after first feeding and yolksac absorption (Jones, 1986; Thorrold and Hare, 2002). Increment deposition before hatching also occurs (Barkmann and Beck, 1976; Radtke and Dean, 1982). If first increment deposition does not occur at hatching, the standard procedure is to add a predetermined number to increment counts to estimate fish age (Campana and Neilson, 1985).

Maximum likelihood estimation of mortality and growth with individual variability from multiple length-frequency data

We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock and derive the underlying length distribution of the population and the catch when there is individual variability in the von Bertalanffy growth parameter L∞. The model is flexible enough to accommodate 1) any recruitment pattern as a function of both time and length, 2) length-specific selectivity, and 3) varying fishing effort over time. The maximum likelihood method gives consistent estimates, provided the underlying distribution for individual variation in growth is correctly specified. Simulation results indicate that our method is reasonably robust to violations in the assumptions. The method is applied to tiger prawn data (Penaeus semisulcatus) to obtain estimates of natural and fishing mortality.

Quantification of drag and lift imposed by pop-up satellite archival tags and estimation of the metabolic cost to cownose rays (Rhinoptera bonasus)

The recent development of the pop-up satellite archival tag (PSAT) has allowed the collection of information on a tagged animal, such as geolocation, pressure (depth), and ambient water temperature. The success of early studies, where PSATs were used on pelagic fishes, has spurred increasing interest in the use of these tags on a large variety of species and age groups. However, some species and age groups may not be suitable candidates for carrying a PSAT because of the relatively large size of the tag and the consequent energy cost to the study animal. We examined potential energetic costs to carrying a tag for the cownose ray (Rhinoptera bonasus). Two forces act on an animal tagged with a PSAT: lift from the PSATs buoyancy and drag as the tag is moved through the water column. In a freshwater flume, a spring scale measured the total force exerted by a PSAT at flume velocities from 0.00 to 0.60 m/s. By measuring the angle of deflection of the PSAT at each velocity, we separated total force into its constituent forces — lift and drag. The power required to carry a PSAT horizontally through the water was then calculated from the drag force and velocity. Using published metabolic rates, we calculated the power for a ray of a given size to swim at a specified velocity (i.e., its swimming power). For each velocity, the power required to carry a PSAT was compared to the swimming power expressed as a percentage, %TAX (Tag Altered eXertion). A %TAX greater than 5% was felt to be energetically significant. Our analysis indicated that a ray larger than 14.8 kg can carry a PSAT without exceeding this criterion. This method of estimating swimming power can be applied to other species and would allow a researcher to decide the suitability of a given study animal for tagging with a PSAT.

Estimation of Standardized Effort in the Heterogeneous Gulf of Mexico Shrimp Fleet

In this paper we estimate nominal and standardized shrimping effort in the Gulf of Mexico for the years 1965 through 1993. We accomplish this by first developing a standardization method (model) and then an expansion method (model). The expansion model estimates nominal days fished for noninterview landings data. The standardization model converts nominal days fished to standard days fished. We then characterize the historical trends of the penaeid shrimp fishery byvessel configuration, relative fishing power, and nominal and standardized effort. Wherever possible, we provide comparison with previous estimates by the National Marine Fisheries Service, NOAA.