8 resultados para Asymptotic Variance of Estimate

em Aquatic Commons


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To bring out the relative efficiency of various types of fishing gears, in the analysis of catch data, a combination of Tukey's test, consequent transformation and graphical analysis for outlier elimination has been introduced, which can be advantageously used for applying ANOVA techniques, Application of these procedures to actual sets of data showed that nonadditivity in the data was caused by either the presence of outliers, or the absence of a suitable transformation or both. As a corollary, the concurrent model: X sub(ij) = µ + α sub(i) + β sub(j) + λ α sub(i) β sub(j) + E sub(ij) adequately fits the data.

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We report a Monte Carlo representation of the long-term inter-annual variability of monthly snowfall on a detailed (1 km) grid of points throughout the southwest. An extension of the local climate model of the southwestern United States (Stamm and Craig 1992) provides spatially based estimates of mean and variance of monthly temperature and precipitation. The mean is the expected value from a canonical regression using independent variables that represent controls on climate in this area, including orography. Variance is computed as the standard error of the prediction and provides site-specific measures of (1) natural sources of variation and (2) errors due to limitations of the data and poor distribution of climate stations. Simulation of monthly temperature and precipitation over a sequence of years is achieved by drawing from a bivariate normal distribution. The conditional expectation of precipitation. given temperature in each month, is the basis of a numerical integration of the normal probability distribution of log precipitation below a threshold temperature (3°C) to determine snowfall as a percent of total precipitation. Snowfall predictions are tested at stations for which long-term records are available. At Donner Memorial State Park (elevation 1811 meters) a 34-year simulation - matching the length of instrumental record - is within 15 percent of observed for mean annual snowfall. We also compute resulting snowpack using a variation of the model of Martinec et al. (1983). This allows additional tests by examining spatial patterns of predicted snowfall and snowpack and their hydrologic implications.

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Demersal groundfish densities were estimated by conducting a visual strip-transect survey via manned submersible on the continental shelf off Cape Flattery, Washington. The purpose of this study was to evaluate the statistical sampling power of the submersible survey as a tool to discriminate density differences between trawlable and untrawlable habitats. A geophysical map of the study area was prepared with side-scan sonar imagery, multibeam bathymetry data, and known locations of historical NMFS trawl survey events. Submersible transects were completed at randomly selected dive sites located in each habitat type. Significant differences in density between habitats were observed for lingcod (Ophiodon elongatus), yelloweye rockfish (Sebastes ruberrimus), and tiger rockfish (S. nigrocinctus) individually, and for “all rockfish” and “all flatfish” in the aggregate. Flatfish were more than ten times as abundant in the trawlable habitat samples than in the untrawlable samples, whereas rockfish as a group were over three times as abundant in the untrawlable habitat samples. Guidelines for sample sizes and implications for the estimation of the continental shelf trawl-survey habitat-bias are considered. We demonstrate an approach that can be used to establish sample size guidelines for future work by illustrating the interplay between statistical sampling power and 1) habitat specific-density differences, 2) variance of density differences, and 3) the proportion of untrawlable area in a habitat.

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Longitudinal surveys of anglers or boat owners are widely used in recreational fishery management to estimate total catch over a fishing season. Survey designs with repeated measures of the same random sample over time are effective if the goal is to show statistically significant differences among point estimates for successive time intervals. However, estimators for total catch over the season that are based on longitudinal sampling will be less precise than stratified estimators based on successive independent samples. Conventional stratified variance estimators would be negatively biased if applied to such data because the samples for different time strata are not independent. We formulated new general estimators for catch rate, total catch, and respective variances that sum across time strata but also account for correlation stratum samples. A case study of the Japanese recreational fishery for ayu (Plecoglossus altivelis) showed that the conventional stratified variance estimate of total catch was about 10% of the variance estimated by our new method. Combining the catch data for each angler or boat owners throughout the season reduced the variance of the total catch estimate by about 75%. For successive independent surveys based on random independent samples, catch, and variance estimators derived from combined data would be the same as conventional stratified estimators when sample allocation is proportional to strata size. We are the first to report annual catch estimates for ayu in a Japanese river by formulating modified estimators for day-permit anglers.

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We have formulated a model for analyzing the measurement error in marine survey abundance estimates by using data from parallel surveys (trawl haul or acoustic measurement). The measurement error is defined as the component of the variability that cannot be explained by covariates such as temperature, depth, bottom type, etc. The method presented is general, but we concentrate on bottom trawl catches of cod (Gadus morhua). Catches of cod from 10 parallel trawling experiments in the Barents Sea with a total of 130 paired hauls were used to estimate the measurement error in trawl hauls. Based on the experimental data, the measurement error is fairly constant in size on the logarithmic scale and is independent of location, time, and fish density. Compared with the total variability of the winter and autumn surveys in the Barents Sea, the measurement error is small (approximately 2–5%, on the log scale, in terms of variance of catch per towed distance). Thus, the cod catch rate is a fairly precise measure of fish density at a given site at a given time.

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Analysis of the length-frequency data on Copadichromis likomae (Cichlidae) from Lake Niassa, Mozambique, suggests an asymptotic length of SL∞=14 cm associated with a K value of 0.93 yearˉ¹. Total and natural mortalities were estimated as 3.2 yearˉ¹ and 1.9 yearˉ¹, respectively. Yield-per-recruit analysis suggests that E=0.36 in this fishery.

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For bacterial sampling of raw unprocessed fish and frozen fishery products, spread plate method is preferable to pour plate method; incubation of plates at 30°C gives a higher count than incubation at 37°C. Analysis of variance of the data shows that sample variation between different types of fishes is highly significant whereas the variations between triplicate plates are not significant at 5 % level.

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A preliminary statistical analysis was undertaken to evaluate whether the effect of El Nino events is apparent in variables related to hydrologic behavior. Annual precipitation, temperature and streamflow were used for three locations in Oregon representing coastal, Willamette Valley/Cascade and eastern Oregon regions. The mean and variance for periods of El Nino occurrence vs. those with no El Nino were computed. Numerical differences were observed but were not consistent across all stations. The coastal area showed a decrease in mean precipitation and increase in mean streamflow during El Nino events. Other stations showed a positive increase in mean for both precipitation and streamflow for El Nino events. Variance of precipitation was greater in the coastal area but smaller in other areas and vice versa for streamflow during El Nino events. Statistical analyses indicated no significant differences of means, variances or distributions using nonparametric tests for El Nino vs. non-El Nino series.