Management and exploitation dynamics of small-scale fisheries in the Bay of Biafra: An integrative analysis of purse seine fishing activity

For many decades, fisheries research has focused on stock assessment and the impact of the fishery effort on resources. Although this knowledge remains necessary, a more integrated analysis of the joint dynamics of resource and operational activities is needed to provide more useful advice for the management of fishery systems. Since 1994 a new approach to fishery science has been carried out for Cameroonian small-scale fisheries, the aim being the incorporation into fishery science of research on fishery management, fishing processes and fishermen's behaviour. This paper presents a more systemic data approach which combines biological parameters and operational factor analyses with the goal of sustainable development. From two years of data collected on the purse seine fishing units operating in the Bay of Biafra (2002 and 2003), a set of three correspondence analyses is applied: (1) to the length frequency distribution of Ethmalosa fimbriata, (2) to the number of visits per fishing ground, and (3) to the species appearance frequency in the landings. These three analyses were plotted per month-year period. The results are presented in the form of an annual exploitation cycle, linking fishing grounds, the main species caught, and corresponding fishing period.     

Simultaneous behavior of skipjack (Katsuwonus pelamis), bigeye (Thunnus obsesus), and yellowfin (T. albacares) tunas, within large multi-species aggregations associated with drifting fish aggregating devices (FADs) in the equatorial eastern Pacific Ocean

Ten separate experiments monitoring the simultaneous behaviors of 26 skipjack (Katsuwonus pelamis), 26 bigeye (Thunnus obesus), and 33 yellowfin (T. albacares) tunas within large multi-species aggregations associated with drifting fish aggregating devices (FADs) were investigated using ultrasonic telemetry in the equatorial eastern Pacific Ocean. Experiments were conducted during a research cruise aboard a chartered purse seine vessel. Purse seine sets were made on the tuna aggregations associated with FADs at the termination of six of the ten experiments. Seventeen of the 44 tagged tunas were not recaptured indicating the transient nature of the associative behavior of tunas with FADs. Although there was considerable overlap in the depths of the three species, by day and night, there were some species-specific differences and diel differences within species. While we documented spatial and temporal differences in the schooling behavior of the three tuna species, the differences do not appear sufficient such that modifications in purse seine fishing practices could effectively avoid the capture of small bigeye and yellowfin tunas, while optimizing the capture of skipjack tuna in purse seine sets on FADs.     

Spatial and temporal variability in the assemblage structure of fishes associated with mangroves (<Emphasis Type="Italic">Avicennia marina</Emphasis>) and intertidal mudflats in temperate Australian embayments

Fishes using mangrove (Avicennia marina) and mudflat habitat were sampled using three different types of gear (seine, fyke, and gill nets) at three sites within each of two large embayments through time (quarterly) between January 2002 and November 2002. At least 41 species of fish were sampled, of which 78% were marine, 17% were estuarine, and 5% were freshwater. Juveniles were sampled in 41% of the species, and 5 and 6 species occurred exclusively in mangrove and mudflat habitats, respectively. The assemblage structure of fishes varied significantly between habitats (for both fyke and seine catches) and between spring and summer (seine catches), but only in one bay. Most of the variability between habitats and times of the year could be explained by differences in abundances of atherinids, mugulids, gobiids, tetraodontids, pleuronectids, and clupeids. Fyke nets sampled mainly juvenile and smaller species of fish. Fish abundance was always greater in mangroves than mudflats (but significantly so at four of the six study sites) and varied significantly between times of the year at one site, while the number of species varied significantly between times of the year at three sites. Gill nets sampled mostly adult/subadult fishes and abundances were greater in mudflats than mangroves at two sites, and in mangroves over mudflats at one site, while species abundance varied between times of the year at two sites. The seine net sampled mainly early post-settlement and small (<20 mm) fishes, more species of which were sampled in mudflat than mangrove during winter and spring, whereas the opposite pattern occurred in summer and autumn. The number of fish sampled with the seine net only varied significantly between habitats in one embayment during summer and spring, when they were larger and smaller, respectively, in mangroves than mudflats. Mangrove habitat in temperate Australian waters supports a richer juvenile fish assemblage than adjacent mudflats, but there is little difference between habitats for the subadult/adult assemblage. Ultimately, the value of mangrove habitats to fishes depends strongly on when and where (bays and sites within bays) the study is done.Communicated by M.S. Johnson, Crawley     

Effects of Fisheries Closures and Gear Restrictions on Fishing Income in a Kenyan Coral Reef

Abstract: The adoption of fisheries closures and gear restrictions in the conservation of coral reefs may be limited by poor understanding of the economic profitability of competing economic uses of marine resources. Over the past 12 years, I evaluated the effects of gear regulation and fisheries closures on per person and per area incomes from fishing in coral reefs of Kenya. In two of my study areas, the use of small‐meshed beach seines was stopped after 6 years; one of these areas was next to a fishery closure. In my third study area, fishing was unregulated. Fishing yields on per capita daily wet weight basis were 20% higher after seine‐net fishing was stopped. The per person daily fishing income adjacent to the closed areas was 14 and 22% higher than the fishing income at areas with only gear restrictions before and after the seine‐net restriction, respectively. Incomes differed because larger fish were captured next to the closed area and the price per weight (kilograms) increased as fish size increased and because catches adjacent to the closure contained fish species of higher market value. Per capita incomes were 41 and 135% higher for those who fished in gear‐restricted areas and near‐closed areas, respectively, compared with those who fished areas with no restrictions. On a per unit area basis (square kilometers), differences in fishing income among the three areas were not large because fishing effort increased as the number of restrictions decreased. Changes in catch were, however, larger and often in the opposite direction expected from changes in effort alone. For example, effort declined 21% but nominal profits per square kilometer (not accounting for inflation) increased 29% near the area with gear restrictions. Gear restrictions also reduced the cost of fishing and increased the proportion of self‐employed fishers.     

Risks to large marine protected areas posed by drifting fish aggregation devices

Mapping and predicting the potential risk of fishing activities to large marine protected areas (MPAs), where management capacity is low but fish biomass may be globally important, is vital to prioritizing enforcement and maximizing conservation benefits. Drifting fish aggregating devices (dFADs) are a highly effective fishing method employed in purse seine fisheries that attract and accumulate biomass fish, making fish easier to catch. However, dFADs are associated with several negative impacts, including high bycatch rates and lost or abandoned dFADs becoming beached on sensitive coastal areas (e.g., coral reefs). Using Lagrangian particle modeling, we determined the potential transit of dFADs in a large MPA around the Chagos Archipelago in the central Indian Ocean. We then quantified the risk of dFADs beaching on the archipelago's reefs and atolls and determined the potential for dFADs to pass through the MPA, accumulate biomass while within, and export it into areas where it can be legally fished (i.e., transit). Over one-third (37.51%) of dFADs posed a risk of either beaching or transiting the MPA for >14 days, 17.70% posed a risk of beaching or transiting the MPA for >30 days, and 13.11% posed a risk of beaching or transiting the MPA for >40 days. Modeled dFADs deployed on the east and west of the perimeter were more likely to beach and have long transiting times (i.e., posed the highest risk). The Great Chagos Bank, the largest atoll in the archipelago, was the most likely site to be affected by dFADs beaching. Overall, understanding the interactions between static MPAs and drifting fishing gears is vital to developing suitable management plans to support enforcement of MPA boundaries and the functioning and sustainability of their associated biomass.     

Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models

Recent advances in technologies have lead to a vast influx of data on movements, based on discrete recorded position of animals or fishing boats, opening new horizons for future analyses. However, most of the potential interest of tracking data depends on the ability to develop suitable modelling strategies to analyze trajectories from discrete recorded positions. A serious modelling challenge is to infer the evolution of the true position and the associated spatio-temporal distribution of behavioural states using discrete, error-prone and incomplete observations. In this paper, a Bayesian Hierarchical Model (HBM) using Hidden Markov Process (HMP) is proposed as a template for analyzing fishing boats trajectories based on data available from satellite-based vessel monitoring systems (VMS). The analysis seeks to enhance the definition of the fishing pressure exerted on fish stocks, by discriminating between the different behavioural states of a fishing trip, and also by quantifying the relative importance of each of these states during a fishing trip. The HBM approach is tested to analyse the behaviour of pelagic trawlers in the Bay of Biscay. A hidden Markov chain with a regular discrete time step is used to model transitions between successive behavioural states (e.g., fishing, steaming, stopping (at Port or at sea)) of each vessel. The parameters of the movement process (speed and turning angles) are defined conditionally upon the behavioural states. Bayesian methods are used to integrate the available data (typically VMS position recorded at discrete time) and to draw inferences on any unknown parameters of the model. The model is first tested on simulated data with different parameters structures. Results provide insights on the potential of HBM with HMP to analyze VMS data. They show that if VMS positions are recorded synchronously with the instants at which the process switch from one behavioural state to another, the estimation method provides unbiased and precise inferences on behavioural states and on associated movement parameters. However, if the observations are not gathered with a sufficiently high frequency, the performance of the estimation method could be drastically impacted when the discrete observations are not synchronous with the switching instants. The model is then applied to real pathways to estimate variables of interest such as the number of operations per trip, time and distance spent fishing or travelling.     

Foraging in the seed-harvester ant genus Pogonomyrmex: are energy costs important?

Energy intake and expenditure on natural foraging trips were estimated for the seed-harvester ants, Pogonomyrmex maricopa and P. rugosus. During seed collection, P. maricopa foraged individually, whereas P. rugosus employed a trunk-trail foraging system. Energy gain per trip and per minute were not significantly different between species. There was also no interspecific difference in energy cost per trip, but energy cost per minute was lower for P. maricopa foragers because they spent on average 7 min longer searching for a load on each trip. Including both unsuccessful and successful foraging trips, average energy gain per trip was more than 100 times the energy cost per trip for both species. Based on this result, we suggest that time cost incurred during individual foraging trips is much more important than energy cost in terms of maximizing net resource intake over time. In addition, because energy costs are so small relative to gains, we propose that energy costs associated with foraging may be safely ignored in future tests of foraging theory with seed-harvesting ant species.     

Scale-invariant movements of fishermen: the same foraging strategy as natural predators.

We analyzed the movement of fishing vessels during fishing trips in order to understand how fishermen behave in space while searching for fish. For that purpose we used hourly geo-referenced positions of vessels, provided by a satellite vessel monitoring system, for the entire industrial fleet (809 vessels) of the world's largest single species fishery (Peruvian anchovy, Engraulis ringens) from December 1999 to March 2003. Observed trajectories of fishing vessels are well modeled by Lévy random walks, suggesting that fishermen use a stochastic search strategy which conforms to the same search statistics as non-human predators. We show that human skills (technology, communication, or others) do not result in the fishermen's spatial behavior being fundamentally different from that of animal predators. With respect to probability of prey encounter, our results suggest that fishermen, on average, evolved an optimal movement pattern (mu = 2.00) among the family of Lévy random walks. This Lagrangian approach opens several perspectives in terms of operational management of the pelagic fish stock.     

Depth utilisation by breeding Adélie penguins,Pygoscelis adeliae,at Esperanza Bay,Antarctica

Miniature depth gauges were attached in December 1987 and January 1988 to Adélie penguins,Pygoscelis adeliae, breeding at Esperanza on the Antarctic Peninsula. Results from 34 birds showed that foraging penguins with eggs and with brooded and crèching chicks spent mean periods away from the nest of 96, 36 and 21 h, respectively, during which time means of 29.0 h (30%), 11.2 h (31%) and 2.7 h (13%), respectively, were spent under water at depths > 5 m. Time under water was positively correlated with time absent from nest. Maximum depth reached was 170 m but overall birds spent most time at shallower depths. Birds foraging for brooded chicks dived deeper than birds foraging for crèching chicks. Stomach-pumping indicated that the principal prey caught at this time was krill,Euphausia superba. Mean mass changes of adults during single foraging trips indicated that krill were caught at a mean rate of 7.2 g min^–1 spent under water.     

Provisioning behavior and the estimation of investment ratios in a solitary bee,Calliopsis (Hypomacrotera) persimilis (Cockerell) (Hymenoptera: Andrenidae)

Summary One aspect of behavioral ecology that has received considerable attention, especially by students of social insects, is the relative amount of energy invested by parents in the rearing of male versus female offspring. Sexual selection theory makes predictions about how individuals should allocate their total investment in the sexes. To test these predictions we must accurately quantify the relative cost incurred by a parent in the production of an average individual of either sex. Body weight ratios are the most common estimate of cost ratio, but the correspondence between offspring body weight and energetic investment on the part of the parent has rarely been determined. Calliopsis (Hypomacrotera) persimilis is a solitary, ground-nesting bee whose natural history makes it particularly convenient for studies of investment patterns and foraging behavior. Each day females construct and provision from 1 to 6 cells in linear, closely-spaced series. Each cell is provisioned with pollen from Physalis Wrightii flowers, which is collected on two or three foraging trips. However, the temporal sequence in which two- and three-trip foraging bouts occur is not random. Females invariably begin each day provisioning cells with three trips worth of pollen and usually switch to provisioning the latter cells of the day with just two trips worth of pollen. The sex of the offspring within the same co-linear series of cells also varies non-randomly — female offspring predominate in the first cells of each series and male offspring in the latter cells. The correspondence between the number of foraging trips to provision a cell, the total time spent foraging, and offspring sex was determined for 36 cells. The data indicate a close, though not absolute, relationship between the number of foraging trips and the sex of the offspring: males usually received two trips of pollen, though some received three, whereas female offspring invariably received three trips worth of pollen. A number of potential estimates of the relative cost of female and male offspring production were calculated. Estimates of the cost ratio based on the amount of time spent foraging, adult dry body weight, and pollen ball dry weight all give similar values. Female offspring receive an energetic investment of from 1.3 to 1.5 times that of males. These results support the use of adult dry body weight ratios in the estimation of cost ratios.     

Activity patterns of giant petrels, Macronectes spp., using different foraging strategies

We studied foraging activity of giant petrels during the incubation period, by simultaneously deploying activity recorders and satellite transmitters on northern (Macronectes halli) and southern giant petrels (Macronectes giganteus) at Bird Island (South Georgia, Antarctica) between 29 October and 26 December 1998. Satellite tracking showed two types of trips: (1) coastal trips, all undertaken by male northern giant petrels, to the nearby South Georgia mainland, presumably foraging on seal and penguin carcasses on beaches, and (2) pelagic trips, foraging at sea for marine prey or potentially scavenging on distant archipelagos (e.g. South Sandwich, Falkland or South Orkney Islands). Activity recorder data were consistent with the types of trip defined by the satellite tracking data, with median wet activity (time spent at the sea surface) during pelagic trips being 41%, but only 14% on coastal trips. On pelagic trips, there was a significant negative correlation between the duration of wet periods and the speed of travel between satellite uplinks. Mean travelling speed between uplinks was greater during day than night for both types of trips, suggesting that giant petrels prefer to travel during daylight and are less active at night. The scarcity of wet periods during the night in giant petrels foraging to the South Georgia coast (median=3%, range=1-9%) indicates that such birds spent almost all night on land. Likewise, the scarcity of wet periods at night for three birds foraging 700-1,000 km south of Bird Island, where there is no land but abundant icebergs, suggests these birds were resting on the icebergs at night. In addition to the adaptations to scavenging on carrion, pelagic trips by giant petrels contain elements similar to those of albatrosses, indicating a complexity to giant petrel lifestyle hitherto unrecognised.     

Predicting fish diet composition using a bagged classification tree approach: a case study using yellowfin tuna (<Emphasis Type="Italic">Thunnus albacares</Emphasis>)

We provided a classification tree modeling framework for investigating complex feeding relationships and illustrated the method using stomach contents data for yellowfin tuna (Thunnus albacares) collected by longline fishing gear deployed off eastern Australia between 1992 and 2006. The non-parametric method is both exploratory and predictive, can be applied to varying size datasets and therefore is not restricted to a minimum sample size. The method uses a bootstrap approach to provide standard errors of predicted prey proportions, variable importance measures to highlight important variables and partial dependence plots to explore the relationships between explanatory variables and predicted prey composition. Our results supported previous studies of yellowfin tuna feeding ecology in the region. However, the method provided a number of novel insights. For example, significant differences were noted in the prey of yellowfin tuna sampled north of 20°S in summer where oligotrophic waters dominate. The analysis also identified that sea-surface temperature, latitude and yellowfin size were the most important variables associated with dietary differences. The methodology is appropriate for delineating ecosystem-level trophic dynamics, as it can easily incorporate large datasets comprising multiple predators to explore trophic interactions among members of a community. Broad-scale relationships among explanatory variables (environmental, biological, temporal and spatial) and prey composition elucidated by this method then serve to focus and lend validity to subsequent fine-scale analyses of important parameters using standard diet methods and chemical tracers such as stable isotopes.     

Size and seasonal influences on the foraging range of female grey seals in the northeast Atlantic

Evidence of segregation in foraging habitat has been demonstrated in some top marine predators, including cetaceans, pinnipeds and seabirds. However, most data are not adequate to assess differences relating to body size or seasonal influences. This has implications for quantitative modelling of population-level predator–prey interactions and ecosystem structure. We examined potential influence of body size and ‘fatness’ on the foraging trip characteristics of a top marine predator, the Atlantic grey seal (Halichoerus grypus), in southwest Ireland within the framework of optimal foraging theory to examine how female grey seals foraging behaviour varied with size, and across the period between moult and breeding. Larger seals undertook trips of greater duration and travelled further from haul-out sites than smaller seals. However, body fat was negatively associated with trip duration and extent. Seals spent more time at sea during the summer, but trips were shorter in extent, suggesting more localized foraging during this season.     

Diving behaviour of female northern rockhopper penguins, Eudyptes chrysocome moseleyi, during the brooding period at Amsterdam Island (Southern Indian Ocean)

The pattern and characteristics of diving in 14 female northern rockhopper penguins, Eudyptes chrysocome moseleyi, were studied at Amsterdam Island (37°50′S; 77°31′E) during the guard stage, using electronic time–depth recorders. Twenty-nine foraging trips (27 daily foraging trips and two longer trips including one night) with a total of 16 572 dives of ≥3 m were recorded. Females typically left the colony at dawn and returned in the late afternoon, spending an average of 12 h at sea, during which they performed ∼550 dives. They were essentially inshore foragers (mean estimated foraging range 6 km), and mainly preyed upon the pelagic euphausiid Thysanoessa gregaria, fishes and squid being only minor components of the diet. Mean dive depth, dive duration, and post-dive intervals were 18.4 m (max. depth 109 m), 57 s (max. dive duration 168 s), and 21 s (37% of dive duration), respectively. Descent and ascent rates averaged 1.2 and 1.0 ms⁻¹ and were, together with dive duration, significantly correlated with dive depth. Birds spent 18% of their total diving time in dives reaching 15 to 20 m, and the mean maximum diving efficiency (bottom time:dive cycle duration) occurred for dives reaching 15 to 35 m. The most remarkable feature of diving behaviour in northern rockhopper penguins was the high percentage of time spent diving during daily foraging trips (on average, 69% of their time at sea); this was mainly due to a high dive frequency (∼44 dives per hour), which explained the high total vertical distance travelled during one trip (18 km on average). Diving activity at night was greatly reduced, suggesting that, as other penguins, E. chrysocome moseleyi are essentially diurnal, and locate prey using visual cues. Received: 9 December 1998 / Accepted: 3 March 1999     

Malthusian overfishing and efforts to overcome it on Kenyan coral reefs

This study examined trends along a gradient of fishing intensity in an artisanal coral reef fishery over a 10-year period along 75 km of Kenya's most populated coastline. As predicted by Malthusian scenarios, catch per unit effort (CPUE), mean trophic level, the functional diversity of fished taxa, and the diversity of gear declined, while total annual catch and catch variability increased along the fishing pressure gradient. The fishery was able to sustain high (approximately 16 Mg x km(-2) x yr(-1)) but variable yields at high fishing pressure due to the dominance of a few productive herbivorous fish species in the catch. The effect of two separate management strategies to overcome this Malthusian pattern was investigated: fisheries area closure and elimination of the dominant and most "competitive" gear. We found that sites within 5 km of the enforced closure showed significantly lower total catch and CPUE, but increased yield stability and trophic level of catch than predicted by regression models normalized for fishing effort. Sites that had excluded illegal beach seine use through active gear management exhibited increased total catch and CPUE. There was a strong interaction between closure and gear management, which indicates that, for closures to be effective at increasing catch, there must be simultaneous efforts at gear management around the periphery of the closures. We propose that Malthusian effects are responsible for the variation in gear and catch and that active management through reduced effort and reductions in the most competitive gear have the greatest potential to increase the functional and trophic diversity and per-person productivity.     

Community structure,density and standing crop of fishes in a subtropical Australian mangrove area

The fishes occurring in a subtropical mangrove (Avicennia marina) area in Moreton Bay, Australia, were studied for one year (November 1987 to November 1988, inclusive). Fishes within the mangroves were sampled using a block net, whilst those in adjacent waters were sampled using seine and gill nets. Forty six percent of the species, 75% of the number of fishes and 94% of the biomass taken during the study (all methods combined) were of direct importance to regional fisheries. The fish community utilising the habitat within the mangrove forest differed from that occurring in adjacent waters in terms of density, standing crop, species composition and diversity-index values. Standing-crop estimates for the fishes occurring within the mangroves (study period mean ± SD = 25.3 ± 20.4 g m^–2) were amongst the highest recorded values for estuarine areas whilst those for adjacent waters (2.9±2.3 g m^–2) were comparable to those of other estuarine studies.     

A general bioeconomic simulation model for annual-crop marine fisheries

A generalized bioeconomic simulation model of annual-crop marine fisheries is described and its use in marine fisheries management is demonstrated. The biological submodel represents the recruitment of new organisms into the fishery, the movement of organisms from one fishing area to another and from one depth to another, the growth of organisms and the mortality of organisms resulting both from natural causes and from fishing. The economic submodel represents the fishing effort exerted on each resource species, the monetary costs of fishing, the value of the harvest and the rent (or excess profits) to the fishery.Basic dynamics of the model results from changes in the number of organisms in the fishery over time, which can be summarized as a set of difference equations of the general form ΔN/Δt = R + I ? E ? M ? F where ΔN/Δt is the net change in number of organisms in the fishery over time, R is recruitment, I is immigration, E is emigration, M is natural mortality and F is fishing mortality. R is a driving variable, whereas I, E, M and F are functions of the state of the system at any given point in time. The model can be run in a deterministic or stochastic mode. Values for parameters affecting rates of recruitment, movement, growth, natural mortality and fishing mortality can be selected from uniform, triangular or normal distributions.Use of the model within a fisheries-management framework is demonstrated by evaluating several management alternatives for the pink shrimp (Penaeus duorarum) fishery on the Tortugas grounds in the Gulf of Mexico. Steps involved in use of the model, including parameterization, validation, sensitivity analysis and stochastic simulations of management policies, are explained.     

Modeling spatial patterns in fisheries bycatch: improving bycatch maps to aid fisheries management.

Fisheries bycatch, or incidental take, of large vertebrates such as sea turtles, seabirds, and marine mammals, is a pressing conservation and fisheries management issue. Identifying spatial patterns of bycatch is an important element in managing and mitigating bycatch occurrences. Because bycatch of these taxa involves rare events and fishing effort is highly variable in space and time, maps of raw bycatch rates (the ratio of bycatch to fishing effort) can be misleading. Here we show how mapping bycatch can be enhanced through the use of Bayesian hierarchical spatial models. We compare model-based estimates of bycatch rates to raw rates. The model-based estimates were more precise and fit the data well. Using these results, we demonstrate the utility of this approach for providing information to managers on bycatch probabilities and cross-taxa bycatch comparisons. To illustrate this approach, we present an analysis of bycatch data from the U.S. gill net fishery for groundfish in the northwest Atlantic. The goals of this analysis are to produce more reliable estimates of bycatch rates, assess similarity of spatial patterns between taxa, and identify areas of elevated risk of bycatch.     

Disentangling the causes of protected‐species bycatch in gillnet fisheries

Gillnet fisheries are widely thought to pose a conservation threat to many populations of marine mammals, seabirds, and turtles. Gillnet fisheries also support a significant proportion of small‐scale fishing communities worldwide. Despite a large number of studies on protected‐species bycatch in recent decades, relatively few have examined the underlying causes of bycatch and fewer still have considered the issue from a multitaxon perspective. We used 3 bibliographic databases and one search engine to identify studies by year of publication and taxon. The majority of studies on the mechanisms of gillnet bycatch are not accessible through the mainstream published literature. Many are reported in technical papers, government reports, and university theses. We reviewed over 600 published and unpublished studies of bycatch in which causal or correlative factors were considered and identified therein 28 environmental, operational, technical, and behavioral factors that may be associated with high or low bycatch rates of the taxa. Of the factors considered, 11 were associated with potential bycatch reduction in 2 out of the 3 taxa, and 3 factors (water depth, mesh size, and net height) were associated with trends in bycatch rate for all 3 taxa. These findings provide a basis to guide further experimental work to test hypotheses about which factors most influence bycatch rates and to explore ways of managing fishing activities and improving gear design to minimize the incidental capture of species of conservation concern while ensuring the viability of the fisheries concerned.     

Aggregation and fishery dynamics: Multiple time scales,times to extinction,and random environments

This paper is a mathematical study of the models introduced by C.W. Clark and M. Mangel to describe the tropical tuna purse seine fishery. By casting the equations into dimensionless form, it is easy to study the bifurcations of the system models and to study the dynamical behavior of the models. The dynamics are analyzed by using singular perturbation theory. A number of stochastic problems related to the dynamics of the models are formulated and solutions are obtained by using the diffusion approximation and asymptotic analysis. Finally, the question of model identification is addressed, and two methods for model identification are sketched.