8 resultados para stationary signals
em Aquatic Commons
Resumo:
A new method is described and evaluated for visually sampling reef fish community structure in environments with highly diverse and abundant reef fish populations. The method is based on censuses of reef fishes taken within a cylinder of 7.5 m radius by a diver at randomly selected, stationary points. The method provides quantitative data on frequency of occnrrence, fish length, abundance, and community composition, and is simple, fast, objective, and repeatable. Species are accumulated rapidly for listing purposes, and large numbers of samples are easily obtained for statistical treatment. The method provides an alternative to traditional visual sampling methods. Observations showed that there were no significant differences in total numbers of species or individuals censused when visibility ranged between 8 and 30 m. The reefs and habitats sampled were significant sources of variation in number of species and individuals censused, but the diver was not a significant influence. Community similarity indices were influenced significantly by the specific sampling site and the reef sampled, but were not significantly affected by the habitat or diver (PDF file contains 21 pages.)
Resumo:
Light traps are one of a number of different gears used to sample pelagic larval and juvenile fishes. In contrast to conventional towed nets, light traps primarily collect larger size classes, including settlement-size larvae (Choat et al., 1993; Hickford and Schiel, 1999 ; Hernandez and Shaw, 2003), and, therefore, have become important tools for discerning recruitment dynamics (Sponaugle and Cowen, 1996; Wilson, 2001). The relative ease with which multiple synoptic light trap samples can be taken means that larval distribution patterns can be mapped with greater spatial resolution (Doherty, 1987). Light traps are also useful for sampling shallow or structurally complex habitats where towed nets are ineffective or prohibited (Gregory and Powles, 1985; Brogan, 1994; Hernandez and Shaw, 2003).
Resumo:
EXTRACT (SEE PDF FOR FULL ABSTRACT): Data were extracted from the U.S. Navy Fleet Numerical Oceanographic Center Master Oceanographic Observation Data Set for a 200 km to 300 km wide coastal strip on the west coast of the United States. These data were averaged for the September through February (winter) and March through August (summer) intervals. The resulting winter temperature anomaly values show the El Nino signal in the CCC [Coastal California Current] as positive temperature anomalies from the surface to at least 300 m.
Resumo:
Empirical orthogonal function (EOF) analysis and regression analysis are used to investigate zonally averaged seasonal temperature anomaly patterns and trends in the lower stratosphere and upper troposphere. The first four EOFs explain 64 percent of the temperature variance and can be related, respectively, to the solar flux (SF) and El Niño/Southern Oscillation (ENSO), to the quasi-biennial oscillation (QBO), to atmospheric carbon dioxide (CO2) and turbidity (TB), and to ENSO. The signal of the fourth EOF is modulated in January to March by the solar flux, with the sense of the modulation determined by the phase of the quasi-biennial oscillation.
Resumo:
Fluctuations in primary productivity at two subalpine lakes reveal both meteorological and biological influences. At Castle Lake, California, large-scale climate events such as the El Niño/Southern Oscillation affect total annual production and, combined with human fishing activity, modify the seasonal pattern of productivity. At Lake Tahoe, California-Nevada, local spring weather conditions modulate annual production and its seasonality by determining the depth of mixing and resulting internal nutrient load. Climatic conditions also contribute to deviations from the long-term trend in productivity by increasing the incidence of forest fires and through anomalous external nutrient loads during precipitation extremes. A 3-year cycle in productivity of as yet unknown origin has also been detected at Lake Tahoe.