979 resultados para cognitive approach to translation
Resumo:
(1) A total of 45 sites was sampled, each being fished using the semi-quantitative and quantitative techniques. (2) A significant relationship existed between the semi-quantitative and Quantitative results for all age groups of salmonids (R2 83.4% to 96.1%, p < 0.0001). (3) The results from each site were categorised according to an existing classification system for quantitative and semi-quantitative data. The semi-quantitative component of this system was modified using the results of this investigation. The degree of error associated with sites classified semi-quantitatively was found to be slightly less when using the modified system for 0+ salmon, > 0+ salmon and 0+ trout, ranging from 10.5% to 30%. (4) Insufficient data points were available for the analysis of coarse fish data.
Resumo:
Solomon Islands has recently developed substantial policy aiming to support inshore fisheries management, conservation, climate change adaptation and ecosystem approaches to resource management. A large body of experience in community based approaches to management has developed but “upscaling” and particularly the implementation of nation-wide approaches has received little attention so far. With the emerging challenges posed by climate change and the need for ecosystem wide and integrated approaches attracting serious donor attention, a national debate on the most effective approaches to implementation is urgently needed. This report discusses potential implementation of “a cost-effective and integrated approach to resource management that is consistent with national policy and needs” based on a review of current policy and institutional structures and examination of a recent case study from Lau, Malaita using stakeholder, transaction and financial cost analyses.
Resumo:
Quantifying scientific uncertainty when setting total allowable catch limits for fish stocks is a major challenge, but it is a requirement in the United States since changes to national fisheries legislation. Multiple sources of error are readily identifiable, including estimation error, model specification error, forecast error, and errors associated with the definition and estimation of reference points. Our focus here, however, is to quantify the influence of estimation error and model specification error on assessment outcomes. These are fundamental sources of uncertainty in developing scientific advice concerning appropriate catch levels and although a study of these two factors may not be inclusive, it is feasible with available information. For data-rich stock assessments conducted on the U.S. west coast we report approximate coefficients of variation in terminal biomass estimates from assessments based on inversion of the assessment of the model’s Hessian matrix (i.e., the asymptotic standard error). To summarize variation “among” stock assessments, as a proxy for model specification error, we characterize variation among multiple historical assessments of the same stock. Results indicate that for 17 groundfish and coastal pelagic species, the mean coefficient of variation of terminal biomass is 18%. In contrast, the coefficient of variation ascribable to model specification error (i.e., pooled among-assessment variation) is 37%. We show that if a precautionary probability of overfishing equal to 0.40 is adopted by managers, and only model specification error is considered, a 9% reduction in the overfishing catch level is indicated.
A sequential Monte Carlo EM approach to the transcription factor binding site identification problem
Resumo:
We developed a habitat suitability index (HSI) model to understand and identify the optimal habitat and potential fishing grounds for neon f lying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean. Remote sensing data, including sea surface temperature, sea surface salinity, sea surface height, and chlorophyll-a concentrations, as well as fishery data from Chinese mainland squid f leets in the main fishing ground (150–165°E longitude) from August to October, from 1999 to 2004, were used. The HSI model was validated by using fishery data from 2005. The arithmetic mean modeling with three of the environmental variables—sea surface temperature, sea surface height anomaly, and chlorophyll- a concentrations—was defined as the most parsimonious HSI model. In 2005, monthly HSI values >0.6 coincided with productive fishing grounds and high fishing effort from August to October. This result implies that the model can reliably predict potential f ishing grounds for O. bartramii. Because spatially explicit fisheries and environmental data are becoming readily available, it is feasible to develop a dynamic, near real-time habitat model for improving the process of identifying potential fishing areas for and optimal habitats of neon flying squid.
Resumo:
Horseshoe crab (Limulus polyphemus) is harvested commercially, used by the biomedical industry, and provides food for migrating shorebirds, particularly in Delaware Bay. Recently, decreasing crab population trends in this region have raised concerns that the stock may be insufficient to fulfill the needs of these diverse user groups. To assess the Delaware Bay horseshoe crab population, we used surplus production models (programmed in ASPIC), which incorporated data from fishery-independent surveys, fishery-dependent catch-per-unit-of-effort data, and regional harvest. Results showed a depleted population (B2003/=0.03−0.71) BMSY and high relative fishing mortality /FMSY=0.9−9.5). Future harvest (F2002strategies for a 15-year period were evaluated by using population projections with ASPICP software. Under 2003 harvest levels (1356 t), population recovery to BMSY would take at least four years, and four of the seven models predicted that the population would not reach BMSY within the 15year period. Production models for horseshoe crab assessment provided management benchmarks for a species with limited data and no prior stock assessment
Resumo:
A simple approach is introduced to estimate the natural mortality rate (M) of fish stocks. The approach is based on the age at maximum cohort biomass, or critical length (L*) concept. The ratio of the critical length to the asymptotic length ( = L*/L8) is relatively constant in 141 fish stocks at 0.62 (CV = 21.4 per cent) and the relationship M = 3K(1- )/ is derived and could be used to estimate M, where K is the growth coefficient of the von Bertalanffy growth function. Average values of are given for the various Families of fish in order to estimate M based on closely related species.