Red porgy <i>Pagrus pagrus</i> is a reef fish important to both recreational and commercial fisheries off the coast of the southeastern United States. Stock assessments performed on this species since 1985 have shown a population in decline. As a result, a number of management actions were put in place, including a harvest moratorium in 1999. Stock assessments for many marine species, including red porgy, rely on a combination of fishery-dependent and fishery-independent data. When a moratorium is in place, the flow of fishery-dependent data is interrupted, making assessments more reliant on fishery-independent information. To investigate how loss of fishery-dependent data, as during a moratorium, would affect stock assessment results for red porgy, I conducted model simulations to represent moratoria of various durations. The most recent red porgy stock assessment model developed during a 2002 workshop was used as a tool in these simulations. I found that biological reference points, such as biomass and fishing mortality, and population projections were more variable for longer simulated moratoria. When fishery-dependent data were removed, minor fluctuations in length and age frequencies resulted in larger fluctuations in estimates of biological reference points. The simulated moratoria also resulted in a slight bias toward over-estimating stock productivity. Similar simulations and analyses were conducted to determine the effects of reducing fishery-independent data from the Marine Resources Monitoring, Assessment, and Prediction (MARMAP) program. Length and age data of reduced MARMAP sample sizes were bootstrapped from original data, and used as input for the stock assessment model. Biological reference points and population projections were more variable for small MARMAP sample sizes, due to the incomplete representation of the length and age frequencies of the population. Reduced sample sizes also showed a slight bias toward predicting a more productive population. These types of simulations emphasize the benefits of investigating potential effects of data reduction on assessment results prior to implementing management strategies, such as a moratorium or sampling change, that cause data loss. Although decreasing red porgy data resulted in slight changes in assessment results, there are more data available for this species than other species in the snapper-grouper complex. For these lesser-studied species, reducing data could dramatically affect assessment capabilities. To investigate this, I compiled available data for these species and identified the stock assessment method used. I then predicted assessment capabilities for each species under a moratorium and if the MARMAP survey was eliminated. A moratorium could reduce assessment capabilities for 37 of the 73 species, and 63 species would require management based on key species. Removing MARMAP data would reduce assessment capabilities of eight species, many of which are economically important. There was an overwhelming need for a reliable catch-per-effort index, information that could improve assessment capabilities of 67 species. This index could be obtained by expanding the MARMAP survey, from a fishery observer program, or from commercial logbooks. By linking the red porgy stock assessment, an evaluation of sampling regimes and data loss during a moratorium, and the expansion of this stock assessment strategy to multiple species, managers will ultimately benefit from increased ability to manage stocks experiencing varying regulations and data availability. / Master of Science

Severe weather events frequently affect important marine fish stocks and fisheries along the United States Atlantic and Gulf of Mexico coasts. However, the effects of these events on fish and fisheries are not well understood. The availability of self-reported data from two fisheries in a region frequently affected by tropical cyclones provided a unique opportunity to investigate short-term responses to past events. This study involved selecting severe weather events, calculating changes in effort and catch-per-unit- effort (CPUE), and analyzing those changes across various temporal, spatial, and species-specific scenarios. Responses in each variable were analyzed within and across scenario factors and explored for correlations and linear multivariate relationships with hypothesized explanatory variables. A negative overall directional change was identified for logbook fishing effort. Based on both correlations and linear models, changes in logbook fishing effort were inversely related to changes in average maximum wind speed. Severe weather events are more likely to affect fishing effort than catch rates of reef-fish species. However, lack of responses in CPUE may also relate to the ability of this study to detect changes. The temporal and spatial scales analyzed in this study may not have been adequate for identifying changes in effort for the headboat fishery, or in CPUE for either fishery. Although there was no region-wide response in CPUE associated with severe weather events, further research on this topic is necessary to determine if storm-induced changes in fishery data are likely strong, long-lasting, or widespread enough to influence the outcome of stock-wide assessments. / Master of Science

The statistical assessment of harvested fish populations, such as the Atlantic-Iberian sardine (AIS) stock, needs to deal with uncertainties inherent in fisheries systems. Uncertainties arising from sampling errors and stochasticity in stock dynamics must be incorporated in stock assessment models so that management decisions are based on realistic evaluation of the uncertainty about the status of the stock. The main goal of this study is to develop a stock assessment framework that accounts for some of the uncertainties associated with the AIS stock that are currently not integrated into stock assessment models. In particular, it focuses on accounting for the uncertainty arising from the catch data sampling process. The central innovation the thesis is the development of a Bayesian integrated stock assessment (ISA) model, in which an observation model explicitly links stock dynamics parameters with statistical models for the various types of data observed from catches of the AIS stock. This allows for systematic and statistically consistent propagation of the uncertainty inherent in the catch sampling process across the whole stock assessment model, through to estimates of biomass and stock parameters. The method is tested by simulations and found to provide reliable and accurate estimates of stock parameters and associated uncertainty, while also outperforming existing designed-based and model-based estimation approaches. The method is computationally very demanding and this is an obstacle to its adoption by fisheries bodies. Once this obstacle is overcame, the ISA modelling framework developed and presented in this thesis could provide an important contribution to the improvement in the evaluation of uncertainty in fisheries stock assessments, not only of the AIS stock, but of any other fish stock with similar data and dynamics structure. Furthermore, the models developed in this study establish a solid conceptual platform to allow future development of more complex models of fish population dynamics.

In fisheries, advice for the management of fish populations is based upon management quantities that are estimated by stock assessment models. Fisheries stock assessment is a process in which data collected from a fish population are used to generate a model which enables the effects of fishing on a stock to be quantified. This study determined the effects of various data sources, assumptions, error scenarios and sample sizes on the accuracy with which the age-structured production model and the Schaefer model (assessment models) were able to estimate key management quantities for a fish resource similar to the Cape hakes (Merluccius capensis and M. paradoxus). An age-structured production model was used as the operating model to simulate hypothetical fish resource population dynamics for which management quantities could be determined by the assessment models. Different stocks were simulated with various harvest rate histories. These harvest rates produced Downhill trip data, where harvest rates increase over time until the resource is close to collapse, and Good contrast data, where the harvest rate increases over time until the resource is at less than half of it’s exploitable biomass, and then it decreases allowing the resource to rebuild. The accuracy of the assessment models were determined when data were drawn from the operating model with various combinations of error. The age-structured production model was more accurate at estimating maximum sustainable yield, maximum sustainable yield level and the maximum sustainable yield ratio. The Schaefer model gave more accurate estimates of Depletion and Total Allowable Catch. While the assessment models were able to estimate management quantities using Downhill trip data, the estimates improved significantly when the models were tuned with Good contrast data. When autocorrelation in the spawner-recruit curve was not accounted for by the deterministic assessment model, inaccuracy in parameter estimates were high. The assessment model management quantities were not greatly affected by multinomial ageing error in the catch-at-age matrices at a sample size of 5000 otoliths. Assessment model estimates were closer to their true values when log-normal error were assumed in the catch-at-age matrix, even when the true underlying error were multinomial. However, the multinomial had smaller coefficients of variation at all sample sizes, between 1000 and 10000, of otoliths aged. It was recommended that the assessment model is chosen based on the management quantity of interest. When the underlying error is multinomial, the weighted log-normal likelihood function should be used in the catch-at-age matrix to obtain accurate parameter estimates. However, the multinomial likelihood should be used to minimise the coefficient of variation. Investigation into correcting for autocorrelation in the stock-recruitment relationship should be carried out, as it had a large effect on the accuracy of management quantities.

Dolphinfish (Coryphaena hippurus) is a pelagic species that is ecologically and commercially important in the western Atlantic region. This species has been linked to dominant oceanographic features such as sea surface temperature (SST) frontal regions. This work first explored the linkages between the catch rates of dolphinfish and the oceanography (satellite-derived SST, distance to front calculations, bottom depth and hook depth) using Principal Components Analysis (PCA). It was demonstrated that higher catch rates are found in relation to warmer SST and nearer to frontal regions. This environmental information was then included in standardizations of catch-per-unit-effort (CPUE) indices. It was found that including the satellite-derived SST and distance to front increases the confidence in the index. The second part of this work focused on addressing spatial variability in the catch rate data for a subsection of the sampling area: the Gulf of Mexico region. This study used geostatistical techniques to model and predict spatial abundances of two pelagic species with different habitat utilization patterns: dolphinfish (Coryphaena hippurus) and swordfish (Xiphias gladius). We partitioned catch rates into two components, the probability of encounter, and the abundance, given a positive encounter. We obtained separate variograms and kriged predictions for each component and combined them to give a single density estimate with corresponding variance. By using this two stage approach we were able to detect patterns of spatial autocorrelation that had distinct differences between the two species, likely due to differences in vertical habitat utilization. The patchy distribution of many living resources necessitates a two-stage variogram modeling and prediction process where the probability of encounter and the positive observations are modeled and predicted separately. Such a "geostatistical delta-lognormal" approach to modeling spatial autocorrelation has distinct advantages in allowing the probability of encounter and the abundance, given an encounter to possess separate patterns of autocorrelation and in modeling of severely non-normally distributed data that is plagued by zeros.

Thesis (M.M.S.), Memorial University of Newfoundland, 2000. / Bibliography: leaves 61-64.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 2003. / Title from PDF title page (viewed Apr. 3, 2005). Vita. Includes bibliographical references.

The New Zealand Ministry of Fisheries relies on fishery assessments to determine suitable catch quotas for exploited fisheries. Currently, 628 fish stocks are managed in New Zealand using the Quote Management System, which includes the 8 com- mercial flatfish species caught within the Exclusive Economic Zone. These eight species of flatfish, which includes four species of flounder, two species of sole, brill and turbot, are currently managed using a combined catch quota. Since these eight species are managed using a common catch quota, there is concern that some of the individual species may be under or over-fished. This thesis describes work involving the flatfish species caught in the FLA3 man- agement area, around the south island of New Zealand. The FLA3 management area contains three key species: New Zealand sole, lemon sole, and sand flounder. Due to the nature and limitations of the data available, simple biomass dynamic models were applied to these species. The maximum likelihood and Bayesian goodness of fit techniques were used to estimate the model parameters. Three models were used: the Fox model, the Schaefer model and the Pella-Tomlinson model with m = 3. As a mathematical/statistical exercise, these models were used to conduct a risk analysis to analyse the advantages and disadvantages of six management options for setting a TACC. However, because of issues over the way that the parameter K has been modelled (due to necessity caused by the lack of data), this should not be seen as an appropriate method for estimating the fish stock. Conclusions were drawn from the results regarding suitable future action for the assessment and management of flatfish stock in FLA3.

Diss. (sammanfattning) Umeå : Sveriges lantbruksuniv., 2001. / Härtill 4 uppsatser.

Thesis (M.Eng.Sc.)--University of Western Australia, 2004.