Zusammenfassung: The characterization of an heterogeneous geological media can be approached by means of an statistical treatment of the field data. This lets us know its spatial variability behaviour, in probability terms. The algorithms presented in this work belongs to the scope of simulation of geological heterogeneous random fields. The aim of that characterization is related with the reseach studies of nuclear waste repositories in deep geological structures. Several stochastic generation algorithms are presented, based in the geostatistical regionalized variable, fractal geometry, and spectral Fourier theories. Some of them are deeply exposed here to their understanding. As a result of the paper, some comparative schemes are showed with numerical, geostatistical and spectral analysis of the implicit autorregresive generation methods.

Zusammenfassung: Standard 0-group indices and distribution maps are now produced based on hand-drawn maps using AutoCad with some additional procedures. This paper briefly describes the method. The paper further describes ways of importing coastlines and survey data directly into standard computer programs such as AutoCad and SAS. Standard methods are used for gridding data, producing isolines and further calculation of abundance indices and presentation of distributions. Interactive editing of distribution maps are made, which makes corresponding automatic updating of indices possible.

Zusammenfassung: Because of the simplicity of calculation and the availability of evaluating the precision of the estimates, a partial likelihood approach has been used for estimating fish mortality rates from tag recoveries and the stock composition in the mixed population based on genetic data. We compare the partial likelihood estimator with the full likelihood estimator, and find that under some conditions, both estimators are the same. The above applications meet the conditions and hence the estimates using the partial likelihood are the same as the ones using the full likelihood. In this case, the partial likelihood approach is quite useful.

Zusammenfassung: For several decades, aquatic ecologists have debated differing viewpoints on the factors that control ecosystem productivity. Much of the controversy centers on the interpretation of empirical relationships between factors that limit the amount of energy transferred among trophic levels in aquatic ecosystems. The primary statistical tool used has been regression analysis, but such models often fail to explain a substantial portion of the variability observed. The suggestion has been made in the literature of aquatic ecology that regression models may be inappropriate, and that limiting factors may be better related to the maximum rather than mean response. Statistical models that account for the large variability in relationships between limiting factors and response variables at higher trophic levels and shift the focus from description of expected values to description of upper boundaries have not been developed. The goal of this project was to develop statistical models for the relationships between limiting factors and the maximum output of biological processes. A number of models may be formulated, one of the primary being Y sub(i) – gamma x sub(i)U sub(i) + sigma epsilon sub(i), where gamma > 0, U sub(i) similar to iid Beta ( alpha , beta ), the x's are considered fixed values on the real line, and the error terms, epsilon sub(i), are centered iid random variables. This model describes a triangular array of points lying between zero and a straight line with positive slope, a data pattern seen numerous times in the ecological literature. The response variable Y is an identifiable mixture of the random variable U, with the model representing a situation in which Y is observed but U is unobserved. Maximum likelihood estimates for the parameters ( alpha , beta , gamma , sigma ) may be computed using the EM algorithm. Estimation is based on maximization of the expected full-data likelihood where the expectation is taken with respect to the conditional density of U given Y. A portion of the dissertation is devoted to the confirmation of asymptotic properties as the response variable, Y sub(i)'s, are not identically distributed. A set of conditions depending on the identically distributed error terms is given for consistency and asymptotic normality of MLE's. The model specific conditions are met by a number of error densities. (DBO)

Zusammenfassung: A simple analytical technique is developed for estimating the predictability of recruitment, that is, correlations between recruitment and stage-specific mortalities or abundances. The method requires the input of estimates of the variability of stage-specific mortalities, which may be calculated from mean stage-specific mortalities by applying a published regression. It is shown that modification of this regression to compensate for sampling error in field measurements of abundance significantly reduces the estimated standard deviation of log-recruitment, which is an important factor in the predictability calculations. It is concluded that the prospects for predicting recruitment from egg or larval surveys or from environmental variables are quite poor for fish stocks showing the typical distribution of mortality across stages.