5 resultados para Beam parameter product (BPP)

em Aquatic Commons


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(PDF has 75 pages)

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Mollusks were sorted from samples of shell hash (obtained as bycatch during NOAA-sponsored studies of larval and juvenile fish distribution), and analyzed to gain qualitative insights on species composition, distribution and habitat affinities of the molluscan fauna on the continental shelf off Georgia. Samples came from beam trawls at 37 stations located in the immediate vicinity and offshore of the Gray’s Reef National Marine Sanctuary (GRNMS) at depths of 4.9 to 103 m. Two hundred sixty-three (263) taxa of mollusks (~58% as dead shells only) were collected, and nearly all (~99%) were identified to the species level. Ninety-seven of these taxa appeared in samples from one or more of the four stations established near the corners of the GRNMS. Samples were highly variable in terms of appearance, volume and species composition of mollusks, reflecting the extreme patchiness of benthic habitats within this region of the continental shelf. With very few exceptions, the mollusks were generally characteristic of either the Carolinian or Caribbean faunal provinces. The Georgia continental shelf, however, was outside the previously reported ranges for at least 16 of the species reported here. Most of these extralimital species were known previously from the East Coast of Florida, and represented northerly range extensions of 1-5° Latitude (110-560 km). One species represented a more significant range extension from the Bahamas and the southern Caribbean, and two represented southerly range extensions, known previously from only as close as off North Carolina. The high incidence of range extensions found in this study and the potential for discovery of additional species are discussed in the context of the diversity and patchiness of benthic habitats on the continental shelf of the region, and the sensitivity of species recruitment to variability in Gulf Stream patterns and global climate change. (PDF contains 52 pages)

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Changes in sensory and instrumental quality parameter sand in thawing drip, cooking drip and total drip loss of frozen stored Baltic cod fillets (Gadus morhua) at different storage temperatures were investigated. Cod fillets stored at –20 °C and –30 °C exhibited the lowest drip losses and obtained the highest sensory scores. Drip losses were found to be highest in cod fillets stored at –10°C and in double frozen fillets stored at –20 °C. These two experiments also gave the lowest sensory scores. The texture parameters increased during storage parallel with storage time. The waterbinding capacity was lowest at –10 °C and almost constant at –30 °C. There is a good correlation between the sensory scores for “tough” and the instrumental texture measurement for hardness and chewiness.

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This research work involves the determination and modelling of water parameter such as pH, temperature, turbidity, chloride, hardness. The result of the analysis was used as important operating variables to generate a model equation of pH, hardness, temperature, turbidity and chloride. The values obtained from the model equation were compared with those from experiment. On an average bases the values were close. These parameters can be used to monitor the extent of pollution of pond water and to monitor stress and diseases of fish. The experimental data of pH was in the range of 6.7 to 6.9 while the modelled result was also between 6.7 to 7.0. The turbidity experimental value was close to the modelled value also. The chloride value for the experimental data was in the range of 25.32 to 35.0. The total hardness value ranges between 4.5 to 65.1 mg/l while the modelled result ranges between 11.025 to 68.402 mg/l. The result was within the acceptable limit of world health organization standard on water quality parameter.

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Abstract Environmental changes may have an impact on life conditions of the fish, e.g. food supply for the fish. The prevailing environmental conditions apply evenly to all age groups of one stock. Small fish have high growth rates, whereas large fish grow with low rates. But, it can be shown on the basis of the von Bertalanffy-growth model that it is sufficient to know only the growth rate of one single age group to compute the growth rates of all other age groups. The growth rate of a reference fish GRF (e.g. a fish with a body mass of 1 kg) was introduced as a reference growth describing the current food condition of all age groups of the stock. As an example a time series of the reference-growth rate of the northern cod stock (NAFO, 3K) was computed for the time span 1979 to 1999. For the northern cod stock it can be observed that environmental conditions caused growth rates below the long-term mean for seven years in a row. After a prolonged hunger period the fish stock collapsed in 1992 also by the impact of fisheries - and this was probably not a coincidence. Now, with the reference-growth rate GRF a simple and handy parameter was found to summarize the influence of the environmental conditions on growth and other derived models and therefore makes it easier to compute the influence of environmental changes within stock assessment. Zusammenfassung Veränderungen der Umwelt können Auswirkungen auf die Lebensbedingungen der Fische haben, z. B. auf das Nahrungsangebot der Fische. Die vorherrschenden Umgebungsbedingungen wirken gleichmäßig auf alle Altersgruppen eines Bestandes, wobei typischer Weise kleineFische hohe Wachstumsraten haben, während die großen Fische mit niedrigen Raten wachsen. Auf der Grundlage des von Bertalanffy-Wachstumsmodells kann gezeigt werden, dass es ausreicht, nur die Wachstumsrate von einer einzigen Altersgruppe zu kennen, um die Wachstumsraten von allen anderen Altersgruppen berechnen zu können. Die Wachstumsrate eines Referenz-Fisches (z.B. eines Fisches mit einer Körpermasse von 1 kg) wurde als Referenz-Wachstum GRF eingeführt, die den aktuellen Zustand des Nahrungsangebots füralle Altersgruppen des Bestandes beschreibt. Als Beispiel wurde einer Zeitreihe der Referenz-Wachstumsraten des nördlichen Kabeljaubestandes (NAFO, 3K) für die Zeitsraum 1979 bis 1999 berechnet. Für diesen Kabeljaubestand war zu beobachten, dass Umgebungsbedingungen für sieben Jahre in Folge Wachstumsraten unter dem langjährigen Mittelwert verursachten. Nach einer längeren Hungerperiode kollabierte dieser Fischbestand im Jahr 1992 auch durch den Einfluß der Fischerei - und dies war sicher kein Zufall. Jetzt, mit der Referenz-Wachstumsrate GRF, ist ein einfacher und handlicher Parameter gefunden, der es gestattet den Einfluss der Umweltbedingungen auf die Wachstumsbedingungen und andere davon abgeleitete Modelle zusammenzufassen. Dies macht es einfach, den Einfluss von Umweltveränderungen innerhalb der Bestandsabschätzungen zu berechnen.