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  • 2005-2009  (2)
  • 2005  (2)
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  • 2005-2009  (2)
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  • 2005  (2)
  • 1
    Online Resource
    Online Resource
    Sultan Qaboos University ; 2005
    In:  Sultan Qaboos University Journal for Science [SQUJS] Vol. 10 ( 2005-06-01), p. 1-
    In: Sultan Qaboos University Journal for Science [SQUJS], Sultan Qaboos University, Vol. 10 ( 2005-06-01), p. 1-
    Abstract: Harmful, toxic algae are now considered as one of the important players in the newly emerging environmental risk factors. The apparent global increase in harmful algal blooms (HABs) is becoming a serious problem in both aquaculture and fisheries populations. Not only has the magnitude and intensity of public health and economic impacts of these blooms increased in recent years, but the number of geographic locations experiencing toxic algal blooms has also increased dramatically. There are two primary factors causing HABs outbreaks. The natural processes such as upwelling and relaxation, and the anthropogenic loading resulting in eutrophication. However, the influence of global climate changes on algal bloom phenomenon cannot be ignored. The problem warrants development of effective strategies for the management and mitigation of HABs. Progress made in the routine coastal monitoring programs, development of methods for detection of algal species and toxins and coastal modeling activities for predicting HABs reflect the international concerns regarding the impacts of HABs. Innovative techniques using molecular probes will hopefully result in development of rapid, reliable screening methods for phycotoxins and the causative organisms.            
    Type of Medium: Online Resource
    ISSN: 2414-536X , 1027-524X
    Language: Unknown
    Publisher: Sultan Qaboos University
    Publication Date: 2005
    detail.hit.zdb_id: 3041053-8
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  • 2
    Online Resource
    Online Resource
    Canadian Science Publishing ; 2005
    In:  Canadian Journal of Fisheries and Aquatic Sciences Vol. 62, No. 3 ( 2005-03-01), p. 544-562
    In: Canadian Journal of Fisheries and Aquatic Sciences, Canadian Science Publishing, Vol. 62, No. 3 ( 2005-03-01), p. 544-562
    Abstract: Reducing overfishing and recovering overfished fish stocks is a challenging and important global problem. Rebuilding targets are essential ingredients for guiding overfished stocks to recovery. Having robust estimates of rebuilding targets is likely a necessary condition for effective long-term management of fishery resources. In this paper, we show how Bayesian model averaging can be applied to estimate rebuilding targets under alternative hypotheses about stockrecruitment dynamics. Using alternative hypotheses about stockrecruitment dynamics and environmental variation is important because using only a single hypothesis can lead to substantially different reference points and policy implications. The alternative hypotheses are augmented with prior information collected from meta-analyses of stockrecruitment data to construct a set of age-structured production models. We illustrate our approach using three overfished New England groundfish stocks. We fit alternative model likelihoods to observed data using Bayesian inference techniques. The Schwarz goodness-of-fit criterion was used to calculate model probabilities. Bayesian model averaging was used to estimate rebuilding targets that were robust to model selection uncertainty. Model-averaged estimates suggested that rebuilding targets for overfished stocks can be reasonably well determined if adequate prior information on stock productivity is available. Nonetheless, results had wide confidence intervals that reflected the underlying uncertainty in rebuilding targets.
    Type of Medium: Online Resource
    ISSN: 0706-652X , 1205-7533
    Language: English
    Publisher: Canadian Science Publishing
    Publication Date: 2005
    detail.hit.zdb_id: 7966-2
    detail.hit.zdb_id: 1473089-3
    SSG: 21,3
    SSG: 12
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