988 resultados para fisheries model


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Several runs of the BEAM4 model were carried out, combining several sets of input parameters from von Bertalanffy's growth curve (Lt = L-x[1 - e(-k(-to))]) and the natural mortality (M), with sets or parameters from the length-weight relationship (W=aL(b)). Further simulations were made with variations of +/- 20%, in the input parameters: recruitment (R), catchability coefficient (q), and the lengths at which 50 and 75% of the fishes are retained by the net (L-50%, and L-75%). The data used were those of the pair trawl fisheries for corvina Micropogonias furnieri, off southeastern Brazil. Results showed variations in the output (landed weight) ranging from - 62 to 147% associated with the diverse sets of VBGF and LWR parameters, and lower variations associated with the other input parameters tested. (C) 2001 Elsevier B.V. B.V. All rights reserved.

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The aim of this paper is to explain under which circumstances using TACs as instrument to manage a fishery along with fishing periods may be interesting from a regulatory point of view. In order to do this, the deterministic analysis of Homans and Wilen (1997)and Anderson (2000) is extended to a stochastic scenario where the resource cannot be measured accurately. The resulting endogenous stochastic model is numerically solved for finding the optimal control rules in the Iberian sardine stock. Three relevant conclusions can be highligted from simulations. First, the higher the uncertainty about the state of the stock is, the lower the probability of closing the fishery is. Second, the use of TACs as management instrument in fisheries already regulated with fishing periods leads to: i) An increase of the optimal season length and harvests, especially for medium and high number of licences, ii) An improvement of the biological and economic variables when the size of the fleet is large; and iii) Eliminate the extinction risk for the resource. And third, the regulator would rather select the number of licences and do not restrict the season length.

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The paper discusses simple methods of estimating fish yield from small reservoirs and establishes 2 indices of fish yield based on: 1) the relationship between the catch per boat in artisanal commercial fish landings and the catch per unit effort in experimental gill-net survey; and also, 2) the relationship between standing crop of fish in reservoirs and catch per unit effort in experimental gill-net survey. The paper then elaborates on the methods of utilizing these simple relationships in managing small reservoirs in Nigeria based on the principle of exclusive fishing right licence with the objective of attracting investors into this viable inland fishery investment project hitherto untapped

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This paper presents a model for Fisheries Social Impact Assessment (SIA) that lays the groundwork for development of fisheries-focused, quantitative social assessments with a clear conceptual model. The usefulness of current fisheries SIA’s has been called into question by some as incompatible with approaches taken by fisheries biologists and economists when assessing potential effects of management actions. Our model’s approach is closer to the economists’ and biologists’ assessments and is therefore more useful for Fishery Management Council members. The paper was developed by anthropologists initially brought together in 2004 for an SIA Modeling Workshop by the National Marine Fisheries Service, NOAA. Opinions and conclusions expressed or implied are solely those of the authors and do not necessarily reflect the views or policy of the National Marine Fisheries Service, NOAA.

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Tag release and recapture data of bigeye (Thunnus obesus) and yellowfin tuna (T. albacares) from the Hawaii Tuna Tagging Project (HTTP) were analyzed with a bulk transfer model incorporating size-specific attrition to infer population dynamics and transfer rates between various fishery components. For both species, the transfer rate estimates from the offshore handline fishery areas to the longline fishery area were higher than the estimates of transfer from those same areas into the inshore fishery areas. Natural and fishing mortality rates were estimated over three size classes: yellowfin 20–45, 46–55, and ≥56 cm and bigeye 29–55, 56–70, and ≥71 cm. For both species, the estimates of natural mortality were highest in the smallest size class. For bigeye tuna, the estimates decreased with increasing size and for yellowfin tuna there was a slight increase in the largest size class. In the Cross Seamount fishery, the fishing mortality rate of bigeye tuna was similar for all three size classes and represented roughly 12% of the gross attrition rate (includes fishing and natural mortality and emigration rates). For yellowfin tuna, fishing mortality ranged between 7% and 30%, the highest being in the medium size class. For both species, the overall attrition rate from the entire fishery area was nearly the same. However, in the specific case of the Cross Seamount fishery, the attrition rate for yellowfin tuna was roughly twice that for bigeye. This result indicates that bigeye tuna are more resident at the Seamount than yellowfin tuna, and larger bigeye tunas tend to reside longer than smaller individuals. This may result in larger fish being more vulnerable to capture in the Seamount fishery. The relatively low level of exchange between the Sea-mount and the inshore and longline fisheries suggests that the fishing activity at the Seamount need not be of great management concern for either species. However, given that the current exploitation rates are considered moderate (10–30%), and that Seamount aggregations of yellowfin and bigeye tuna are highly vulnerable to low-cost gear types, it is recommended that further increases in fishing effort for these species be monitored at Cross Seamount.

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In many lower-income countries, the establishment of marine protected areas (MPAs) involves significant opportunity costs for artisanal fishers, reflected in changes in how they allocate their labor in response to the MPA. The resource economics literature rarely addresses such labor allocation decisions of artisanal fishers and how, in turn, these contribute to the impact of MPAs on fish stocks, yield, and income. This paper develops a spatial bio-economic model of a fishery adjacent to a village of people who allocate their labor between fishing and on-shore wage opportunities to establish a spatial Nash equilibrium at a steady state fish stock in response to various locations for no-take zone MPAs and managed access MPAs. Villagers’ fishing location decisions are based on distance costs, fishing returns, and wages. Here, the MPA location determines its impact on fish stocks, fish yield, and villager income due to distance costs, congestion, and fish dispersal. Incorporating wage labor opportunities into the framework allows examination of the MPA’s impact on rural incomes, with results determining that win-wins between yield and stocks occur in very different MPA locations than do win-wins between income and stocks. Similarly, villagers in a high-wage setting face a lower burden from MPAs than do those in low-wage settings. Motivated by issues of central importance in Tanzania and Costa Rica, we impose various policies on this fishery – location specific no-take zones, increasing on-shore wages, and restricting MPA access to a subset of villagers – to analyze the impact of an MPA on fish stocks and rural incomes in such settings.

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Understanding the fluctuations in population abundance is a central question in fisheries. Sardine fisheries is of great importance to Portugal and is data-rich and of primary concern to fisheries managers. In Portugal, sub-stocks of Sardina pilchardus (sardine) are found in different regions: the Northwest (IXaCN), Southwest (IXaCS) and the South coast (IXaS-Algarve). Each of these sardine sub-stocks is affected differently by a unique set of climate and ocean conditions, mainly during larval development and recruitment, which will consequently affect sardine fisheries in the short term. Taking this hypothesis into consideration we examined the effects of hydrographic (river discharge), sea surface temperature, wind driven phenomena, upwelling, climatic (North Atlantic Oscillation) and fisheries variables (fishing effort) on S. pilchardus catch rates (landings per unit effort, LPUE, as a proxy for sardine biomass). A 20-year time series (1989-2009) was used, for the different subdivisions of the Portuguese coast (sardine sub-stocks). For the purpose of this analysis a multi-model approach was used, applying different time series models for data fitting (Dynamic Factor Analysis, Generalised Least Squares), forecasting (Autoregressive Integrated Moving Average), as well as Surplus Production stock assessment models. The different models were evaluated, compared and the most important variables explaining changes in LPUE were identified. The type of relationship between catch rates of sardine and environmental variables varied across regional scales due to region-specific recruitment responses. Seasonality plays an important role in sardine variability within the three study regions. In IXaCN autumn (season with minimum spawning activity, larvae and egg concentrations) SST, northerly wind and wind magnitude were negatively related with LPUE. In IXaCS none of the explanatory variables tested was clearly related with LPUE. In IXaS-Algarve (South Portugal) both spring (period when large abundances of larvae are found) northerly wind and wind magnitude were negatively related with LPUE, revealing that environmental effects match with the regional peak in spawning time. Overall, results suggest that management of small, short-lived pelagic species, such as sardine quotas/sustainable yields, should be adapted to a regional scale because of regional environmental variability.

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Fishers are faced with multiple risks, including unpredictability of future catch rates, prices and costs. While the latter are largely beyond the control of fisheries managers, effective fisheries management should reduce uncertainty about future catches. Different management instruments are likely to have different impacts on the risk perception of fishers, and this should manifest itself in their implicit discount rate. Assuming licence and quota values represent the net present value of the flow of expected future profits, then a proxy for the implicit discount rate of vessels in a fishery can be derived by the ratio of the average level of profits to the average licence/quota value. From this, an indication of the risk perception can be derived, assuming higher discount rates reflect higher levels of systematic risk. In this paper, we apply the capital asset pricing model (CAPM) to determine the risk premium implicit in the discount rates for a range of Australian fisheries, and compare this with the set of management instruments in place. We test the assumption that rights based management instruments lower perceptions of risk in fisheries. We find little evidence to support this assumption. although the analysis was based on only limited data.

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Capacity reduction programs in the form of buybacks or decommissioning programs have had relatively widespread application in fisheries in the US, Europe and Australia. A common criticism of such programs is that they remove the least efficient vessels first, resulting in an increase in average efficiency of the remaining fleet. The effective fishing power of the fleet, therefore, does not decrease in proportion to the number of vessels removed. Further, reduced crowding may increase efficiency of the remaining vessels. In this paper, the effects of a buyback program on average technical efficiency in Australia’s Northern Prawn Fishery are examined using a multi-output distance function approach with an explicit inefficiency model. The results indicate that average efficiency of the remaining vessels was greater than that of the removed vessels, and that average efficiency of remaining vessels also increased as a result of reduced crowding.

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Capacity reduction programmes, in the form of buybacks or decommissioning, have had relatively widespread application in fisheries in the US, Europe and Australia. A common criticism of such programmes is that they remove the least efficient vessels first, resulting in an increase in average efficiency of the remaining fleet, which tends to increase the effective fishing power of the remaining fleet. In this paper, the effects of a buyback programme on average technical efficiency in Australia’s Northern Prawn Fishery are examined using a multi-output production function approach with an explicit inefficiency model. As expected, the results indicate that average efficiency of the remaining vessels was generally greater than that of the removed vessels. Further, there was some evidence of an increase in average scale efficiency in the fleet as the remaining vessels were closer, on average, to the optimal scale. Key factors affecting technical efficiency included company structure and the number of vessels fishing. In regard to fleet size, our model suggests positive externalities associated with more boats fishing at any point in time (due to information sharing and reduced search costs), but also negative externalities due to crowding, with the latter effect dominating the former. Hence, the buyback resulted in a net increase in the individual efficiency of the remaining vessels due to reduced crowding, as well as raising average efficiency through removal of less efficient vessels.

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The paradigm that mangroves are critical for sustaining production in coastal fisheries is widely accepted, but empirical evidence has been tenuous. This study showed that links between mangrove extent and coastal fisheries production could be detected for some species at a broad regional scale (1000s of kilometres) on the east coast of Queensland, Australia. The relationships between catch-per-unit-effort for different commercially caught species in four fisheries (trawl, line, net and pot fisheries) and mangrove characteristics, estimated from Landsat images were examined using multiple regression analyses. The species were categorised into three groups based on information on their life history characteristics, namely mangrove-related species (banana prawns Penaeus merguiensis, mud crabs Scylla serrata and barramundi Lates calcarifer), estuarine species (tiger prawns Penaeus esculentus and Penaeus semisulcatus, blue swimmer crabs Portunus pelagicus and blue threadfin Eleutheronema tetradactylum) and offshore species (coral trout Plectropomus spp.). For the mangrove-related species, mangrove characteristics such as area and perimeter accounted for most of the variation in the model; for the non-mangrove estuarine species, latitude was the dominant parameter but some mangrove characteristics (e.g. mangrove perimeter) also made significant contributions to the models. In contrast, for the offshore species, latitude was the dominant variable, with no contribution from mangrove characteristics. This study also identified that finer scale spatial data for the fisheries, to enable catch information to be attributed to a particular catchment, would help to improve our understanding of relationships between mangroves and fisheries production.

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Multivariate predictive models are widely used tools for assessment of aquatic ecosystem health and models have been successfully developed for the prediction and assessment of aquatic macroinvertebrates, diatoms, local stream habitat features and fish. We evaluated the ability of a modelling method based on the River InVertebrate Prediction and Classification System (RIVPACS) to accurately predict freshwater fish assemblage composition and assess aquatic ecosystem health in rivers and streams of south-eastern Queensland, Australia. The predictive model was developed, validated and tested in a region of comparatively high environmental variability due to the unpredictable nature of rainfall and river discharge. The model was concluded to provide sufficiently accurate and precise predictions of species composition and was sensitive enough to distinguish test sites impacted by several common types of human disturbance (particularly impacts associated with catchment land use and associated local riparian, in-stream habitat and water quality degradation). The total number of fish species available for prediction was low in comparison to similar applications of multivariate predictive models based on other indicator groups, yet the accuracy and precision of our model was comparable to outcomes from such studies. In addition, our model developed for sites sampled on one occasion and in one season only (winter), was able to accurately predict fish assemblage composition at sites sampled during other seasons and years, provided that they were not subject to unusually extreme environmental conditions (e.g. extended periods of low flow that restricted fish movement or resulted in habitat desiccation and local fish extinctions).

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While the economic and environmental benefits of fisheries management are well accepted, the costs of effective management in low value fisheries, including the research necessary to underpin such management, may be considerable relative to the total economic benefits they may generate. Co-management is often seen as a panacea in low value fisheries. Increasing fisher participation increases legitimacy of management decision in the absence of detailed scientific input. However, where only a small number of operators exist, the potential benefits of co-management are negated by the high transaction cost to the individual fishers engaging in the management process. From an economic perspective, sole ownership has been identified as the management structure which can best achieve biological and economic sustainability. Moving low value fisheries with a small number of participants to a corporate-cooperative management model may come close to achieving these sole ownership benefits, with lower transaction costs. In this paper we look at the applicability of different management models with industry involvement to low value fisheries with a small number of participants. We provide an illustration as to how a fishery could be transitioned to a corporate-cooperative management model that captures the key benefits of sole management at a low cost and is consistent with societal objectives.