7 resultados para Reduced physical models

em Aquatic Commons


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Foreword [pdf, < 0.1 MB] Acknowledgements PHASE 1 [pdf, 0.2 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (July 19–20, 2007, Seattle, U.S.A.) Background Links to Other Programs Workshop Format Session I. Status of climate change scenarios in the PICES region Session II. What are the expected impacts of climate change on regional oceanography and what are some scenarios for these drivers for the next 10 years? Session III. Recruitment forecasting Session IV. What models are out there? How is climate linked to the model? Session V. Assumptions regarding future fishing scenarios and enhancement activities Session VI Where do we go from here? References Appendix 1.1 List of Participants PHASE 2 [pdf, 0.7 MB] Summary of the PICES/NPRB Workshop on Forecasting Climate Impacts on Future Production of Commercially Exploited Fish and Shellfish (October 30, 2007, Victoria, Canada) Background Workshop Agenda Forecast Feasibility Format of Information Modeling Approaches Coupled bio-physical models Stock assessment projection models Comparative approaches Similarities in Data Requests Opportunities for Coordination with Other PICES Groups and International Efforts BACKGROUND REPORTS PREPARED FOR THE PHASE 2 WORKSHOP Northern California Current (U.S.) groundfish production by Melissa Haltuch Changes in sablefish (Anoplopoma fimbria) recruitment in relation to oceanographic conditions by Michael J. Schirripa Northern California Current (British Columbia) Pacific cod (Gadus macrocephalus) production by Caihong Fu and Richard Beamish Northern California Current (British Columbia) sablefish (Anoplopoma fimbria) production by Richard Beamish Northern California Current (British Columbia) pink (Oncorhynchus gorbuscha) and chum (O. keta) salmon production by Richard Beamish Northern California Current (British Columbia) ocean shrimp (Pandalus jordani) production by Caihong Fu Alaska salmon production by Anne Hollowed U.S. walleye pollock (Theragra chalcogramma) production in the eastern Bering Sea and Gulf of Alaska by Kevin Bailey and Anne Hollowed U.S. groundfish production in the eastern Bering Sea by Tom Wilderbuer U.S. crab production in the eastern Bering Sea by Gordon H. Kruse Forecasting Japanese commercially exploited species by Shin-ichi Ito, Kazuaki Tadokoro and Yasuhiro Yamanka Russian fish production in the Japan/East Sea by Yury Zuenko, Vladimir Nuzhdin and Natalia Dolganova Chum salmon (Oncorhynchus keta) production in Korea by Sukyung Kang, Suam Kim and Hyunju Seo Jack mackerel (Trachurus japonicus) production in Korea by Jae Bong Lee and Chang-Ik Zhang Chub mackerel (Scomber japonicus) production in Korea by Jae Bong Lee, Sukyung Kang, Suam Kim, Chang-Ik Zhang and Jin Yeong Kim References Appendix 2.1 List of Participants PHASE 3 [pdf, < 0.1 MB] Summary of the PICES Workshop on Linking Global Climate Model Output to (a) Trends in Commercial Species Productivity and (b) Changes in Broader Biological Communities in the World’s Oceans (May 18, 2008, Gijón, Spain) Appendix 3.1 List of Participants Appendix 3.2 Workshop Agenda (Document contains 101 pages)

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When drafting a new model of a towed technical system for fisheries (trawl, towed TV gear or similar), and also when measuring an existing and already tested system it is not easy to foresee of practical behaviour, which depends of various parameters. The measuring programme for recording all data needs a lot of time and money, and also has some limitations. Therefore we developed for such systems mathematical-physical models, which allow a complex calculation. Their real value, however, results only from practical verification. During the cruise no. 222 of “Walther Herwig III” in November 2000 comparative investigations for 2concrete systems were carried out. This was done in cooperation with the University in Rostock, where such models are being developed and computerized. One of the systems mesasured was a pelagic herring trawl and the other one the towed TV gear for underwater observations of the Institute for Fishery Technology and Fish Quality. The correspondence between model calculation and measurements was very high for both systems.

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The Gainesville Florida Reef, a satellite of the Worldwide Hyperbolic Crochet Coral Reef, project not only shows the beauty of reefs but serves to: • Foster scientific communication through the visual arts • Raise awareness of the fragility of our coral reefs and the entire ecosystem • Support learning by creating physical models of geometric principles • Connect several areas on campus, including fine arts, mathematics and ecology and environmental sciences through collaboration and mutual interest • Encourage local community and alumni involvement through creating, observing and learning

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Interaction of ocean waves, currents and sea bed roughness is a complicated phenomena in fluid dynamic. This paper will describe the governing equations of motions of this phenomena in viscous and nonviscous conditions as well as study and analysis the experimental results of sets of physical models on waves, currents and artificial roughness, and consists of three parts: First, by establishing some typical patterns of roughness, the effects of sea bed roughness on a uniform current has been studied, as well as the manning coefficient of each type is reviewed to find the critical situation due to different arrangement. Second, the effect of roughness on wave parameters changes, such as wave height, wave length, and wave dispersion equations have been studied, third, superimposing, the waves + current + roughness patterns established in a flume, equipped with waves + currents generator, in this stage different analysis has been done to find the governing dimensionless numbers, and present the numbers to define the contortions and formulations of this phenomena. First step of the model is verified by the so called Chinese method, and the Second step by the Kamphius (1975), and third step by the van Rijn (1990) , and Brevik and Ass ( 1980), and in all cases reasonable agreements have been obtained. Finally new dimensionless parameters presented for this complicated phenomena.

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The Sierra Leone River Estuary is a relatively young drowned river valley, it is shallow except for a deep channel which passes close to the Freetown shoreline. The upper reaches merge into a network of creeks and channels fringed by large areas of mangrove swamps. It is a tidal estuary of the semi-mixed type with the saline oceanic water entering it on a diurnal cycle. The climate of Sierra Leone is marked by a very distinct change between a very wet rainy season and a dry season. The tidal range of the Estuary (spring 3.03m; neap 2.28m) does not impede normal use of the harbour. The tidal variations can be felt as far as 42 miles inland along the water courses of the Sierra Leone River and its tributaries. The volume of fresh water entering the Estuary is large during the rainy season and greatly reduced during the dry season. Consequently there is a marked fall in salinity during the rainy season and higher salinities due to the marine influence prevailing during the dry season. The nature of the shores and bottom, the hydrography and chemistry of the estuarine system have been outlined in relation to the prevailing climatic conditions.

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Ichthyoplankton surveys have been used to provide an independent estimate of adult spawning biomass of commercially exploited species and to further our understanding of the recruitment processes in the early life stages. However, predicting recruitment has been difficult because of the complex interaction of physical and biological processes operating at different spatial and temporal scales that can occur at the different life stages. A model of first-year life-stage recruitment was applied to Georges Bank Atlantic cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) stocks over the years 1977–2004 by using environmental and densitydependent relationships. The best lifestage mortality relationships for eggs, larvae, pelagic juveniles, and demersal juveniles were first determined by hindcasting recruitment estimates based on egg and larval abundance and mortality rates derived from two intensive sampling periods, 1977–87 and 1995–99. A wind-driven egg mortality relationship was used to estimate losses due to transport off the bank, and a wind-stress larval mortality relationship was derived from feeding and survival studies. A simple metric for the density-dependent effects of Atlantic cod was used for both Atlantic cod and haddock. These life stage proxies were then applied to the virtual population analysis (VPA) derived annual egg abundances to predict age-1 recruitment. Best models were determined from the correlation of predicted and VPA-derived age-1 abundance. The larval stage was the most quantifiable of any stage from surveys, whereas abundance estimates of the demersal juvenile stage were not available because of undersampling. Attempts to forecast recruitment from spawning stock biomass or egg abundance, however, will always be poor because of variable egg survival.

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Studies were conducted to evaluate the quality of hilsa fish during icing and freezing storage at -20°C by determining organoleptic and bacteriological aspects. The fishes stored in ice were organoleptically in acceptable condition 2 for 20 days. The bacterial load in muscles of 4 days ice stored fish was 2.5x10² CFU/g which gradually increased up to 1.8x10⁵ CFU/g after 20 days when the fishes were organoleptically in acceptable condition. The keeping qualities of different days of ice stored fishes were also evaluated during their subsequent frozen storage at -20°C. Both 4 and 7 days of ice stored fishes were organoleptically in acceptable condition up to 48 weeks but the highest degree of freshness was found for fish stored in ice for 4 days before freezing at -20°C. The result indicates that the longer is the duration of ice storage before freezing, the shorter is the shelf life of the fish. The initial bacterial load prior to freezing of the 4 and 7 days of ice stored samples were 2.5x10³ CFU/g and 3.8x10⁴ CFU/g, respectively which reduced to 2.21x10² CFU/g and 2.38x10² CFU/g, respectively at the end of the 24 weeks of frozen storage. However, after 40 weeks the bacterial load in the frozen stored sample fell below the detection level.