43 resultados para tag data structure
Resumo:
In a tagging experiment carried out in the Kenyan waters of Lake Victoria, an annual growth increment of 29 cm yr was obtained for Lates niloticus (L.). Growth parameters obtained using the von Bertalanffy model on the growth curve fitted by eye were L (inf.) = 122 cm yr and k = 0.26 yr. Data for other species tagged were inadequate to obtain meaningful results.
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Three commercially important fish species, Lates niloticus (L.), Rastrineobola argentea (Pellegrin) and Oreochromis niloticus (L.) that are fished by artisanal fishermen of Lake Victoria, Tanzania part, were studied in Kagera, Mwanza and Mara beaches from October 1997 to July 1999. Catches, effort, exploitation and stock structure were investigated. Beaches for sampling were selected based on importance for landing the above named fish species. The number of boats found on beach that day, the number that lay idle and their means of propulsion were recorded. As many boats as possible were sampled for gear type and gear size. The catches were sorted into species and measured. Variation in the species and size composition of landings was observed between regions, between months and between gears used. The implications of the findings to management are discussed.
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ENGLISH: The population structure and production of Pacific yellowfin tuna, Thunnus albacares, were examined by studying most of the basic data available on stock assessment, as well as other data, for the period 1965 to 1972. The data were obtained mainly from the Japanese longline fishery in the Pacific Ocean east of about 1200E and from the purse-seine fishery in the eastern Pacific east of about 140oW. Data from genetic studies of subpopulations were not used due to their preliminary nature. It was concluded that the concept of "semi-independent" subpopulations proposed by Kamimura and Honma (1963) and Royce (1964) defines the population structure of Pacific yellowfin. At least three stocks (i.e. western, central and eastern), relatively independent of each other, are thought to exist, but the actual number and location of subpopulations is still unclear. Possible north-south separations, indicated to some extent by genetic studies and tagging, could be neither substantiated nor rejected on the basis of this study. Finally, unless some major change in the fishing technology occurs, it is doubtful if any significant sustainable increase in yellowfin production from the Pacific is possible. The greatest potential for increase, if any, appears to be based on changing the size structure of yellowfin in the catch from the central Pacific. SPANISH: Se examino la estructura de la población y la producción del atún aleta amarilla del Pacifico Thunnus albacares para estudiar la mayoría de los datos básicos que se tenían sobre el avalúo de la población, como también otra información correspondiente al periodo de 1965·1972. Los datos fueron obtenidos principalmente de las pescas palangreros japonesas del Océano Pacifico al este de los 1200 E y de las pescas con redes de cerco del Pacifico oriental, al este de los 140oW. No se emplearon los datos de estudios genéticos de las subpoblaciones porque eran mas bien preliminares. Se concluyo que el concepto propuesto por Kamimura y Honma (1963) y Royce (1964) de subpoblaciones "semiindependientes" define la estructura de la población del aleta amarilla en el Pacifico. Se cree que existen por 10 menos tres existencias (e.d. la occidental, central y oriental), relativamente independientes la una de la otra, pero no se conoce con certeza cuantas subpoblaciones hay y donde se encuentran. La posible separación norte-sur, indicada, hasta cierto punto, por los análisis genéticos y del marcado, no puede ni confirmarse ni rechazarse basados en este estudio. Finalmente, a no ser que ocurra algún gran cambio en la tecnología pesquera es dudoso que sea posible obtener un aumento constante e importante en la producción del aleta amarilla del Pacifico. El potencial mayor de aumento, si es que existe alguno, parece que se basa en el cambio de la estructura de talla en la captura del aleta amarilla del Pacifico central. (PDF contains 169 pages.)
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We develop and test a method to estimate relative abundance from catch and effort data using neural networks. Most stock assessment models use time series of relative abundance as their major source of information on abundance levels. These time series of relative abundance are frequently derived from catch-per-unit-of-effort (CPUE) data, using general linearized models (GLMs). GLMs are used to attempt to remove variation in CPUE that is not related to the abundance of the population. However, GLMs are restricted in the types of relationships between the CPUE and the explanatory variables. An alternative approach is to use structural models based on scientific understanding to develop complex non-linear relationships between CPUE and the explanatory variables. Unfortunately, the scientific understanding required to develop these models may not be available. In contrast to structural models, neural networks uses the data to estimate the structure of the non-linear relationship between CPUE and the explanatory variables. Therefore neural networks may provide a better alternative when the structure of the relationship is uncertain. We use simulated data based on a habitat based-method to test the neural network approach and to compare it to the GLM approach. Cross validation and simulation tests show that the neural network performed better than nominal effort and the GLM approach. However, the improvement over GLMs is not substantial. We applied the neural network model to CPUE data for bigeye tuna (Thunnus obesus) in the Pacific Ocean.
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Field experiments were conducted to test the hypotheses that Pacific halibut (Hippoglossus stenolepis) display small-scale spatial structure within longline catches, relative to other species and empty hooks, or within-species based on sex or length. Sequential hook-by-hook inventories, along with length and sex data, were taken at thirty-one survey stations. Two-dimensional spatial statistics were used to test for 1) aggregation, defined as the clustering of individuals within a given demographic of size or sex over small intervals of distance; and 2) segregation, defined as the sequential occurrence of individuals within a given demographic of size or sex, uninterrupted by other observations, irrespective of the distance between individuals. Statistically significant structure was detected within catches that is more commonly associated with fish length than sex. Significant spatial structuring occurred at 60% of all stations tested. Significant aggregation of halibut of legal length for commercial retention (≥82 cm) was detected at 44% of stations and aggregation of sublegal-size halibut was detected at 11%. Maleand female-based aggregations were observed at 22% and 11% of stations, respectively. Significant segregation of females was observed at 20% of stations, male segregation occurred at 8% of stations, and segregation by size at 16% of stations. Understanding small-scale spatial structure within longline catches may help us interpret changes in survey and commercial catch data. If structure is generated by behavior, then observed size-at-age or relative sex-ratios may be biased relative to underlying distributions. Although physical processes such as gape limitation should remain stable over the time, dynamic processes may be spatially and temporally variabl
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The sandbar shark (Carcharhinus plumbeus) was the cornerstone species of western North Atlantic and Gulf of Mexico large coastal shark fisheries until 2008 when they were allocated to a research-only fishery. Despite decades of fishing on this species, important life history parameters, such as age and growth, have not been well known. Some validated age and growth information exists for sandbar shark, but more comprehensive life history information is needed. The complementary application of bomb radiocarbon and tag-recapture dating was used in this study to determine valid age-estimation criteria and longevity estimates for this species. These two methods indicated that current age interpretations based on counts of growth bands in vertebrae are accurate to 10 or 12 years. Beyond these years, we could not determine with certainty when such an underestimation of age begins; however, bomb radiocarbon and tag-recapture data indicated that large adult sharks were considerably older than the estimates derived from counts of growth bands. Three adult sandbar sharks were 20 to 26 years old based on bomb radiocarbon results and were a 5- to 11-year increase over the previous age estimates for these sharks. In support of these findings, the tag-recapture data provided results that were consistent with bomb radiocarbon dating and further supported a longevity that exceeds 30 years for this species.
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Research on assessment and monitoring methods has primarily focused on fisheries with long multivariate data sets. Less research exists on methods applicable to data-poor fisheries with univariate data sets with a small sample size. In this study, we examine the capabilities of seasonal autoregressive integrated moving average (SARIMA) models to fit, forecast, and monitor the landings of such data-poor fisheries. We use a European fishery on meagre (Sciaenidae: Argyrosomus regius), where only a short time series of landings was available to model (n=60 months), as our case-study. We show that despite the limited sample size, a SARIMA model could be found that adequately fitted and forecasted the time series of meagre landings (12-month forecasts; mean error: 3.5 tons (t); annual absolute percentage error: 15.4%). We derive model-based prediction intervals and show how they can be used to detect problematic situations in the fishery. Our results indicate that over the course of one year the meagre landings remained within the prediction limits of the model and therefore indicated no need for urgent management intervention. We discuss the information that SARIMA model structure conveys on the meagre lifecycle and fishery, the methodological requirements of SARIMA forecasting of data-poor fisheries landings, and the capabilities SARIMA models present within current efforts to monitor the world’s data-poorest resources.
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Surveys were conducted to evaluate and compare assemblage structure and trophodynamics of ichthyoplankton, and their variability, in an estuarine transition zone. Environmental gradients in the saltfront region of the Patuxent River subestuary, Chesapeake Bay, were hypothesized to define spatiotemporal distributions and assemblages of ichthyoplankton. Larval fishes, zooplankton, and hydrographic data were collected during spring through early summer 2000 and 2001. Larvae of 28 fish species were collected and species richness was similar each year. Total larval abundance was highest in the oligohaline region down-estuary of the salt front in 2000, but highest at the salt front in 2001. Larvae of anadromous fishes were most abundant at or up-estuary of the salt front in both years. Two ichthyoplankton assemblages were distinguished: 1) riverine—characterized predominantly by anadromous species (Moronidae and Alosinae); and 2) estuarine—characterized predominantly by naked goby (Gobiosoma bosc) (Gobiidae). Temperature, dissolved oxygen, salinity-associated variables (e.g., salt-front location), and concentrations of larval prey, specifically the calanoid copepod Eurytemora affinis and the cladoceran Bosmina longirostris, were important indicators of larval fish abundance. In the tidal freshwater region up-estuary of the salt front, there was substantial diet overlap between congeneric striped bass (Morone saxatilis) and white perch (M. americana) larvae, and also larvae of alewife (Alosa pseudoharengus) (overlap= 0.71–0.93). Larval abundance, taxonomic diversity, and dietary overlap were highest within and up-estuary of the salt front, which serves to both structure the ichthyoplankton community and control trophic relationships in the estuarine transition zone.
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Pop-up satellite archival tags (PSATs) have been used to study movements, habitat use, and postrelease survival of large pelagic vertebrates, but the size of these tags has historically precluded their use on smaller coastal species. To evaluate a new generation of smaller PSATs for the study of postrelease survival and habitat use of coastal species, we attached Microwave Telemetry, Inc., X-tags to ten striped bass (Morone saxatilis) 94–112 cm total length (TL) caught on J hooks and circle hooks during the winter recreational fishery in Virginia. Tags collected temperature and depth information every five minutes and detached from the fish after 30 days. Nine of the ten tags released on schedule and eight transmitted 30% to 96% (mean 78.6%) of the archived data. Three tags were physically recovered during or after the transmission period, allowing retrieval of all archived data. All eight striped bass whose tags transmitted data survived for 30 days after release, including two fish that were hooked deeply with J hooks. The eight fish spent more than 90% of their time at depths less than 10 m and in temperatures of 6–9°C, demonstrated no significant diel differences in depth or temperature utilization (P>0.05), and exhibited weak periodicities in vertical movements consistent with daily and tidal cycles.
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A new method of finding the optimal group membership and number of groupings to partition population genetic distance data is presented. The software program Partitioning Optimization with Restricted Growth Strings (PORGS), visits all possible set partitions and deems acceptable partitions to be those that reduce mean intracluster distance. The optimal number of groups is determined with the gap statistic which compares PORGS results with a reference distribution. The PORGS method was validated by a simulated data set with a known distribution. For efficiency, where values of n were larger, restricted growth strings (RGS) were used to bipartition populations during a nested search (bi-PORGS). Bi-PORGS was applied to a set of genetic data from 18 Chinook salmon (Oncorhynchus tshawytscha) populations from the west coast of Vancouver Island. The optimal grouping of these populations corresponded to four geographic locations: 1) Quatsino Sound, 2) Nootka Sound, 3) Clayoquot +Barkley sounds, and 4) southwest Vancouver Island. However, assignment of populations to groups did not strictly reflect the geographical divisions; fish of Barkley Sound origin that had strayed into the Gold River and close genetic similarity between transferred and donor populations meant groupings crossed geographic boundaries. Overall, stock structure determined by this partitioning method was similar to that determined by the unweighted pair-group method with arithmetic averages (UPGMA), an agglomerative clustering algorithm.
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A generalized Bayesian population dynamics model was developed for analysis of historical mark-recapture studies. The Bayesian approach builds upon existing maximum likelihood methods and is useful when substantial uncertainties exist in the data or little information is available about auxiliary parameters such as tag loss and reporting rates. Movement rates are obtained through Markov-chain Monte-Carlo (MCMC) simulation, which are suitable for use as input in subsequent stock assessment analysis. The mark-recapture model was applied to English sole (Parophrys vetulus) off the west coast of the United States and Canada and migration rates were estimated to be 2% per month to the north and 4% per month to the south. These posterior parameter distributions and the Bayesian framework for comparing hypotheses can guide fishery scientists in structuring the spatial and temporal complexity of future analyses of this kind. This approach could be easily generalized for application to other species and more data-rich fishery analyses.
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We investigated the use of otolith morphology to indicate the stock structure of an exploited serranid coral reef fish, Plectropomus leopardus, on the Great Barrier Reef (GBR), Australia. Otoliths were measured by traditional one-and two-dimensional measures (otolith length, width, area, perimeter, circularity, and rectangularity), as well as by Fourier analysis to capture the finer details of otolith shape. Variables were compared among four regions of the GBR separated by hundreds of kilometers, as well as among three reefs within each region, hundreds of meters to tens of kilometers apart. The temporal stability in otolith structure was examined by comparing two cohorts of fully recruited four-year-old P. leopardus collected two years before and two years after a signif icant disturbance in the southern parts of the GBR caused by a large tropical cyclone in March 1997. Results indicated the presence of at least two stocks of P. leopardus, although the structure of each stock varied depending on the cohort considered. The results highlight the importance of incorporating data from several years in studies using otolith morphology to discriminate temporary and possibly misleading signals from those that indicate persistent spatial structure in stocks. We conclude that otolith morphology can be used as an initial step to direct further research on groups of P. leopardus that have lived at least a part of their life in different environments.
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Molecular markers have been demonstrated to be useful for the estimation of stock mixture proportions where the origin of individuals is determined from baseline samples. Bayesian statistical methods are widely recognized as providing a preferable strategy for such analyses. In general, Bayesian estimation is based on standard latent class models using data augmentation through Markov chain Monte Carlo techniques. In this study, we introduce a novel approach based on recent developments in the estimation of genetic population structure. Our strategy combines analytical integration with stochastic optimization to identify stock mixtures. An important enhancement over previous methods is the possibility of appropriately handling data where only partial baseline sample information is available. We address the potential use of nonmolecular, auxiliary biological information in our Bayesian model.
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The population structure and abundance of the American lobster (Homarus americanus) stock in the Gulf of Maine are defined by data derived from a fishery-independent trawl survey program conducted by the National Marine Fisheries Service (NMFS). Few sampling stations in the survey area are located inshore, in particular along coastal Maine. According to statistics, however, more than two thirds of the lobster landings come from inshore waters within three miles off the coast of Maine. In order to include an inshore survey program, complementary to the NMFS survey, the Maine Department of Marine Resources (DMR) initialized an inshore survey program in 2000. The survey was modeled on the NMFS survey program, making these two survey programs comparable. Using data from both survey programs, we evaluated the population structure of the American lobster in the Gulf of Maine. Our findings indicate that lobsters in the Gulf of Maine tend to have a size-dependent inshore-off-shore distribution; smaller lobsters are more likely to stay inshore and larger lobsters are more likely to stay offshore. The DMR inshore and NMFS survey programs focused on different areas in the Gulf of Maine and likely targeted different segments of the stock. We suggest that data from both survey programs be used to assess the lobster stock and to describe the dynamics of the stock in the Gulf of Maine.
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We assayed allelic variation at 19 nuclear-encoded microsatellites among 1622 Gulf red snapper (Lutjanus campechanus) sampled from the 1995 and 1997 cohorts at each of three offshore localities in the northern Gulf of Mexico (Gulf). Localities represented western, central, and eastern subregions within the northern Gulf. Number of alleles per microsatellite per sample ranged from four to 23, and gene diversity ranged from 0.170 to 0.917. Tests of conformity to Hardy-Weinberg equilibrium expectations and of genotypic equilibrium between pairs of micro-satellites were generally nonsignificant following Bonferroni correction. Significant genic or genotypic heterogeneity (or both) among samples was detected at four microsatellites and over all microsatellites. Levels of divergence among samples were low (FST ≤0.001). Pairwise exact tests revealed that six of seven “significant” comparisons involved temporal rather than spatial heterogeneity. Contemporaneous or variance effective size (NeV) was estimated from the temporal variance in allele frequencies by using a maximum-likelihood method. Estimates of NeV ranged between 1098 and >75,000 and differed significantly among localities; the NeV estimate for the sample from the northcentral Gulf was >60 times as large as the estimates for the other two localities. The differences in variance effective size could ref lect differences in number of individuals successfully reproducing, differences in patterns and intensity of immigration, or both, and are consistent with the hypothesis, supported by life-history data, that different “demographic stocks” of red snapper are found in the northern Gulf. Estimates of NeV for red snapper in the northern Gulf were at least three orders of magnitude lower than current estimates of census size (N). The ratio of effective to census size (Ne/N) is far below that expected in an ideal population and may reflect high variance in individual reproductive success, high temporal and spatial variance in productivity among subregions or a combination of the two.