Variability in supply and cross-shelf transport of pink shrimp (Farfantepenaeus duorarum) postlarvae into western Florida Bay

The variability in the supply of pink shrimp (Farfantepenaeus duorarum) postlarvae and the transport mechanisms of planktonic stages were investigated with field data and simulations of transport. Postlarvae entering the nursery grounds of Florida Bay were collected for three consecutive years at channels that connect the Bay with the Gulf of Mexico, and in channels of the Middle Florida Keys that connect the southeastern margin of the Bay with the Atlantic Ocean. The influx of postlarvae in the Middle Florida Keys was low in magnitude and varied seasonally and among years. In contrast, the greater postlarval influx occurred at the northwestern border of the Bay, where there was a strong seasonal pattern with peaks in influx from July through September each year. Planktonic stages need to travel up to 150 km eastward between spawning grounds (northeast of Dry Tortugas) and nursery grounds (western Florida Bay) in about 30 days, the estimated time of planktonic development for this species. A Lagrangian trajectory model was developed to estimate the drift of planktonic stages across the SW Florida shelf. The model simulated the maximal distance traveled by planktonic stages under various assumptions of behavior. Simulation results indicated that larvae traveling with the instantaneous current and exhibiting a diel behavior travel up to 65 km and 75% of the larvae travel only 30 km. However, the eastward distance traveled increased substantially when a larval response to tides was added to the behavioral variable (distance increased to 200 km and 85% of larvae traveled 150 km). The question is, when during larval development, and where on the shallow SW Florida shelf, does the tidal response become incorporated into the behavior of pink shrimp.

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.

Simulated and Actual Effects of the Brown Shrimp, Penaeus aztecus, Closure in Mexico

Simulations based on a yield-per-recruit model were performed to analyze the impact ofg rowth overfishing on brown shrimp, Penaeus aztecus, and to assess the effects of a closed season inshore and offshore of the Mexican States of Tamaulipas and Veracruz. Closure of both the inshore and offshore fisheries could enhance cohort yield by more than 300%. Cohon yield enhancement would be only about 60-80% if only the offshore season were closed. The closed season of 1993 gave better results as it covered a larger part of the brown shrimp peak recruitment period. Catch per unit of effort (CPUE) after closure in 1993, compared with 1994, was 2.4 times higher than the mean CPUE of the month. Total annual offshore yield increased 72% in 1993 (3,800 metric tons (t)) and 10% in 1994 (506 t) with respect to the mean annual offshore catch during the 10-year period prior to the 1993 closure. Simulation results could help identify alternatives that permit the coexistence of the inshore and offshore fisheries while maintaining high profitability of the brown shrimp fishery.

Recruitment as an evolving random process of aggregation and mortality

The dynamics of the survival of recruiting fish are analyzed as evolving random processes of aggregation and mortality. The analyses draw on recent advances in the physics of complex networks and, in particular, the scale-free degree distribution arising from growing random networks with preferential attachment of links to nodes. In this study simulations were conducted in which recruiting fish 1) were subjected to mortality by using alternative mortality encounter models and 2) aggregated according to random encounters (two schools randomly encountering one another join into a single school) or preferential attachment (the probability of a successful aggregation of two schools is proportional to the school sizes). The simulations started from either a “disaggregated” (all schools comprised a single fish) or an aggregated initial condition. Results showed the transition of the school-size distribution with preferential attachment evolving toward a scale-free school size distribution, whereas random attachment evolved toward an exponential distribution. Preferential attachment strategies performed better than random attachment strategies in terms of recruitment survival at time when mortality encounters were weighted toward schools rather than to individual fish. Mathematical models were developed whose solutions (either analytic or numerical) mimicked the simulation results. The resulting models included both Beverton-Holt and Ricker-like recruitment, which predict recruitment as a function of initial mean school size as well as initial stock size. Results suggest that school-size distributions during recruitment may provide information on recruitment processes. The models also provide a template for expanding both theoretical and empirical recruitment research.