988 resultados para Individual fishery quotas (IFQ)
Resumo:
Applying Turkey's jackknife method on MSY estimates from the surplus production models of Schaefer and Fox showed that the optimum yield for shrimps in industrial fishery in Sierra Leone is estimated at 2,686.8 t with 15,822 fishing days. Annual catch for 1996 was 2,788 t, indicating an escalation in exploitation which, if prolonged, could bring reduced productivity as experienced in the fishery some years ago.
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Some problems associated with fitting surplus production models to unsuitable data are discussed. This is illustrated by an application of the Schaefer, Fox and PRODFIT models to Pacific Ocean bigeye tuna (Thunnus obesus ) catch and effort data for 1952-1987, which appear to be better described by purely empirical models.
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A brief description of the Greek fisheries for the anchovy (Engraulis encrasicolus, Engraulidae) is given, with emphasis on the spatial distribution of the catch. Satellite images of phytoplankton pigment distribution obtained with NIMBUS-7 are used to explain local abundance of the dynamics of anchovy populations.
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The article was extracted from the author's dissertation entitled "Management of small pelagic fisheries on the northwest coast of Peninsular Malaysia: a bio-socioeconomic simulation analysis". The basic structure and uses of this simulation model are presented here.
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Formal decision analysis was applied to the management of loco (Concholepas concholepas, Fam. Muricidae) in Chile, 29-35 degrees S. Four interested groups were considered "Fishers", "Scientists", "Buyers" and the "State", along with three fishing effort levels and four subobjectives. The method was found to encourage the emergence of a consensus (here: halving of effort), and is recommended for use in other fisheries.
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The highly productive fisheries of Kerala, India, are suffering from overexploitation. Use of unsuitable fishing gears that result in a high level of wasteful bycatch and destruction of egg bearing and juvenile fish should be controlled. This paper makes some suggestions for monitoring and conservation of the fisheries in Kerala.
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Two relatively inexpensive light traps to capture pre-settling reef fish and invertebrates are described. A trap made from a plastic bucket (with plastic bottles, a small plastic waste bin and two sheets of plywood) that costs US$15 appears to be just as effective as a large aluminium and plexiglass trap that costs US$275.
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Growth of a temperate reefa-ssociated fish, the purple wrasse (Notolabrus fucicola), was examined from two sites on the east coast of Tasmania by using age- and length-based models. Models based on the von Bertalanffy growth function, in the standard and a reparameterized form, were constructed by using otolith-derived age estimates. Growth trajectories from tag-recaptures were used to construct length-based growth models derived from the GROTAG model, in turn a reparameterization of the Fabens model. Likelihood ratio tests (LRTs) determined the optimal parameterization of the GROTAG model, including estimators of individual growth variability, seasonal growth, measurement error, and outliers for each data set. Growth models and parameter estimates were compared by bootstrap confidence intervals, LRTs, and randomization tests and plots of bootstrap parameter estimates. The relative merit of these methods for comparing models and parameters was evaluated; LRTs combined with bootstrapping and randomization tests provided the most insight into the relationships between parameter estimates. Significant differences in growth of purple wrasse were found between sites in both length- and age-based models. A significant difference in the peak growth season was found between sites, and a large difference in growth rate between sexes was found at one site with the use of length-based models.
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Fishing is widely recognized to have profound effects on estuarine and marine ecosystems (Hammer and Jansson, 1993; Dayton et al., 1995). Intense commercial and recreational harvest of valuable species can result in population collapses of target and nontarget species (Botsford et al., 1997; Pauly et al., 1998; Collie et al. 2000; Jackson et al., 2001). Fishing gear, such as trawls and dredges, that are dragged over the seafloor inflict damage to the benthic habitat (Dayton et al., 1995; Engel and Kvitek, 1995; Jennings and Kaiser, 1998; Watling and Norse, 1998). As the growing human population, over-capitalization, and increasing government subsidies of fishing place increasing pressures on marine resources (Myers, 1997), a clear understanding of the mechanisms by which fishing affects coastal systems is required to craft sustainable fisheries management.
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Population assessments seldom incorporate habitat information or use previously observed distributions of fish density. Because habitat affects the spatial distribution of fish density and overall abundance, the use of habitat information and previous estimates of fish density can produce more precise and less biased population estimates. In this study, we describe how poststratification can be applied as an unbiased estimator to data sets that were collected under a probability sampling design, typical of many multispecies trawl surveys. With data from a multispecies survey of juvenile flatfish, we show how poststratification can be applied to a data set that was not collected under a probability sampling design, where both the precision and the bias are unknown. For each of four species, three estimates of total abundance were compared: 1) unstratified; 2) poststratified by habitat; and 3) poststratified by habitat and fish density (high fish density and low fish density) in nearby years. Poststratification by habitat gave more precise and (or) less design-biased estimates than an unstratified estimator for all species in all years. Poststratification by habitat and fish density produced the most precise and representative estimates when the sample size in the high fish-density and low fish-density strata were sufficient (in this study, n≥20 in the high fish-density stratum, n≥9 in the low fish-density stratum). Because of the complexities of statistically testing the annual stratified data, we compared three indices of abundance for determining statistically significant changes in annual abundance. Each of the indices closely approximated the annual differences of the poststratified estimates. Selection of the most appropriate index was dependent upon the species’ density distribution within habitat and the sample size in the different habitat areas. The methods used in this study are particularly useful for estimating individual species abundance from multispecies surveys and for retrospective st
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Survey- and fishery-derived biomass estimates have indicated that the harvest indices for Pacific cod (Gadus macrocephalus) within a portion of Steller sea lion (Eumetopias jubatus) critical habitat in February and March 2001 were five to 16 times greater than the annual rate for the entire Bering Sea-Aleutian Islands stock. A bottom trawl survey yielded a cod biomass estimate of 49,032 metric tons (t) for the entire area surveyed, of which less than half (23,329 t) was located within the area used primarily by the commercial fishery, which caught 11,631 t of Pacific cod. Leslie depletion analyses of fishery data yielded biomass estimates of approximately 14,500 t (95% confidence intervals of approximately 9,000–25,000 t), which are within the 95% confidence interval on the fished area survey estimate (12,846–33,812 t). These data indicate that Leslie analyses may be useful in estimating local fish biomass and harvest indices for certain marine fisheries that are well constrained spatially and relatively short in duration (weeks). In addition, fishery effects on prey availability within the time and space scales relevant to foraging sea lions may be much greater than the effects indicated by annual harvest rates estimated from stock assessments averaged across the range of the target spec
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Predicting and under-standing the dynamics of a population requires knowledge of vital rates such as survival, growth, and reproduction. However, these variables are influenced by individual behavior, and when managing exploited populations, it is now generally realized that knowledge of a species’ behavior and life history strategies is required. However, predicting and understanding a response to novel conditions—such as increased fishing-induced mortality, changes in environmental conditions, or specific management strategies—also require knowing the endogenous or exogenous cues that induce phenotypic changes and knowing whether these behaviors and life history patterns are plastic. Although a wide variety of patterns of sex change have been observed in the wild, it is not known how the specific sex-change rule and cues that induce sex change affect stock dynamics. Using an individual based model, we examined the effect of the sex-change rule on the predicted stock dynamics, the effect of mating group size, and the performance of traditional spawning-per-recruit (SPR) measures in a protogynous stock. We considered four different patterns of sex change in which the probability of sex change is determined by 1) the absolute size of the individual, 2) the relative length of individuals at the mating site, 3) the frequency of smaller individuals at the mating site, and 4) expected reproductive success. All four pat-terns of sex change have distinct stock dynamics. Although each sex-change rule leads to the prediction that the stock will be sensitive to the size-selective fishing pattern and may crash if too many reproductive size classes are fished, the performance of traditional spawning-per-recruit measures, the fishing pattern that leads to the greatest yield, and the effect of mating group size all differ distinctly for the four sex-change rules. These results indicate that the management of individual species requires knowledge of whether sex change occurs, as well as an understanding of the endogenous or exogenous cues that induce sex change.
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The objective of this study was to investigate the spatial patterns in green sea urchin (Strongylocentrotus droebachiensis) density off the coast of Maine, using data from a fishery-independent survey program, to estimate the exploitable biomass of this species. The dependence of sea urchin variables on the environment, the lack of stationarity, and the presence of discontinuities in the study area made intrinsic geostatistics inappropriate for the study; therefore, we used triangulated irregular networks (TINs) to characterize the large-scale patterns in sea urchin density. The resulting density surfaces were modified to include only areas of the appropriate substrate type and depth zone, and were used to calculate total biomass. Exploitable biomass was estimated by using two different sea urchin density threshold values, which made different assumptions about the fishing industry. We observed considerable spatial variability on both small and large scales, including large-scale patterns in sea urchin density related to depth and fishing pressure. We conclude that the TIN method provides a reasonable spatial approach for generating biomass estimates for a fishery unsuited to geostatistics, but we suggest further studies into uncertainty estimation and the selection of threshold density values.
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Abstract—Fisheries often target individuals based on size. Size-selective fishing can create selection differentials on life-history traits and, when those traits have a genetic basis, may cause evolution. The evolution of life history traits affects potential yield and sustainability of fishing, and it is therefore an issue for fishery management. Yet fishery managers usually disregard the possibility of evolution, because little guidance is available to predict evolutionary consequences of management strategies. We attempt to provide some generic guidance. We develop an individual-based model of a population with overlapping generations and continuous reproduction. We simulate model populations under size-selective fishing to generate and quantify selection differentials on growth. The analysis comprises a variety of common life-history and fishery characteristics: variability in growth, correlation between von Bertalanffy growth parameters (K and L∞), maturity rate, natural mortality rate (M), M/K ratio, duration of spawning season, fishing mortality rate (F), maximum size limit, slope of selectivity curve, age at 50% selectivity, and duration of fishing season. We found that each characteristic affected the magnitude of selection differentials. The most vulnerable stocks were those with a short spawning or fishing season. Under almost all life-history and fishery characteristics examined, selection differentials created by realistic fishing mortality rates are considerable.
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Fish bioenergetics models estimate relationships between energy budgets and environmental and physiological variables. This study presents a generic rockfish (Sebastes) bioenergetics model and estimates energy consumption by northern California blue rockf ish (S. mystinus) under average (baseline) and El Niño conditions. Compared to males, female S. mystinus required more energy because they were larger and had greater reproductive costs. When El Niño conditions (warmer temperatures; lower growth, condition, and fecundity) were experienced every 3−7 years, energy consumption decreased on an individual and a per-recruit basis in relation to baseline conditions, but the decrease was minor (<4% at the individual scale, <7% at the per-recruit scale) compared to decreases in female egg production (12−19% at the individual scale, 15−23% at the per-recruit scale). When mortality in per-recruit models was increased by adding fishing, energy consumption in El Niño models grew more similar to that seen in the baseline model. However, egg production decreased significantly — an effect exacerbated by the frequency of El Niño events. Sensitivity analyses showed that energy consumption estimates were most sensitive to respiration parameters, energy density, and female fecundity, and that estimated consumption increased as parameter uncertainty increased. This model provides a means of understanding rockfish trophic ecology in the context of community structure and environmental change by synthesizing metabolic, demographic, and environmental information. Future research should focus on acquiring such information so that models like the bioenergetics model can be used to estimate the effect of climate change, community shifts, and different harvesting strategies on rockfish energy demands.