Zusammenfassung: Studies of predator-prey interactions have been limited to laboratories or relatively small scale field experiments because of logistic difficulties in large scale field experiments. Much evidence has suggested that predictions based on small scale experiments on predator-prey interactions may not be simply extended to large scales, e.g. whole system. This study was designed to examine predation effects on a prey fish assemblage at the whole lake scale. After a year of premanipulation study, northern pike (Esox lucius) were introduced into a small piscivore-free lake inhabited by 14 species of fishes. In the third and fourth years, the lake was divided by a large mesh fence and northern pike were introduced into one half of the lake. Predation effects on individual prey population were estimated for both direct effects (i.e., consumption of prey species) and indirect effects, including habitat changes associated with predator avoidance behavior, increase of emigration rates and changes of population size structure. The relative importance of direct versus indirect effects was examined using randomized intervention analysis along with a model that quantifies the indirect effects. Decreases of prey fish biomass due to increased emigration was at least as great as that due to the direct effect of consumption when prey biomass was high (>40 kg/ha) but not when prey biomass was low (<30 kg/ha). Significant indirect effects included dramatically decreased abundance of the dominant species (northern redbelly dace, Phoxinus eos), increase of some rare species (sunfish, Lepomis spp. and creek chub, Semotilus atromaculatus), and decreased mean sizes of redbelly dace. Indirect effects occurred rapidly and were most apparent immediately following the introduction of northern pike. Community responses to northern pike predation included changes of species composition, species diversity and community stabilities. The fish communities were significantly different among the pre-pike period, pike period and post-pike period. The greatest variance was related to abundances of redbelly dace and sunfish. However, predation effects on the prey fish community depended on the observational scales used to determine community structure. (DBO)

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)