Part I. Hydraulics of tidal inlets: simple analytic models for the engineer

Inlets are common coastal features around the world. Essentially an inlet connects a lagoon, a bay or an estuary to the ocean (or sea), and the flow through the inlet channel is primarily induced by the tidal rise and fall of water level in the ocean. When speaking of the hydraulics of an inlet, one is interested mainly in determining the flow through the inlet and the tidal variation in the bay, given the following: (1) Inlet geometry (2) Bay geometry (3) Bottom sediment characteristics in the inlet (4) Fresh water inflow into the bay (and out through the inlet) (5) Ocean tide characteristics A combination of all these factors can produce a rather complex situation. (PDF contains 34 pages.)

A meta-analytic approach to quantifying scientific uncertainty in stock assessments

Quantifying scientific uncertainty when setting total allowable catch limits for fish stocks is a major challenge, but it is a requirement in the United States since changes to national fisheries legislation. Multiple sources of error are readily identifiable, including estimation error, model specification error, forecast error, and errors associated with the definition and estimation of reference points. Our focus here, however, is to quantify the influence of estimation error and model specification error on assessment outcomes. These are fundamental sources of uncertainty in developing scientific advice concerning appropriate catch levels and although a study of these two factors may not be inclusive, it is feasible with available information. For data-rich stock assessments conducted on the U.S. west coast we report approximate coefficients of variation in terminal biomass estimates from assessments based on inversion of the assessment of the model’s Hessian matrix (i.e., the asymptotic standard error). To summarize variation “among” stock assessments, as a proxy for model specification error, we characterize variation among multiple historical assessments of the same stock. Results indicate that for 17 groundfish and coastal pelagic species, the mean coefficient of variation of terminal biomass is 18%. In contrast, the coefficient of variation ascribable to model specification error (i.e., pooled among-assessment variation) is 37%. We show that if a precautionary probability of overfishing equal to 0.40 is adopted by managers, and only model specification error is considered, a 9% reduction in the overfishing catch level is indicated.

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.

Estimating the emigration rate of fish stocks from marine sanctuaries using tag-recovery data

A critical process in assessing the impact of marine sanctuaries on fish stocks is the movement of fish out into surrounding fished areas. A method is presented for estimating the yearly rate of emigration of animals from a protected (“no-take”) zone. Movement rates for exploited populations are usually inferred from tag-recovery studies, where tagged individuals are released into the sea at known locations and their location of recapture is reported by fishermen. There are three drawbacks, however, with this method of estimating movement rates: 1) if animals are tagged and released into both protected and fished areas, movement rates will be overestimated if the prohibition on recapturing tagged fish later from within the protected area is not made explicit; 2) the times of recapture are random; and 3) an unknown proportion of tagged animals are recaptured but not reported back to researchers. An estimation method is proposed which addresses these three drawbacks of tag-recovery data. An analytic formula and an associated double-hypergeometric likelihood method were derived. These two estimators of emigration rate were applied to tag recoveries from southern rock lobsters (Jasus edwardsii) released into a sanctuary and into its surrounding fished area in South Australia.