Search

Biodiversity and ecosystem function is a contemporary topic at the forefront of ecology. It is driven by the fundamental need to understand how the loss of biodiversity, which is occurring all around the world, affects goods and services obtained from ecosystems. The scientific literature indicates functional attributes of species strongly influence ecosystem properties; however, a lack of understanding exists regarding the relationship among functional diversity, taxonomic diversity, and community structure. As a result, this dissertation contributes to our understanding of the relationship between biodiversity and ecosystem function by analyzing the organization of stream-fish assemblages from a functional and taxonomic perspective and by synthesizing the relationship between the two aspects of biodiversity. I used a combination of previously published data, which covered broad biogeographic areas, and my own field work to address various issues on multiple spatial and temporal scales. I focused exclusively on stream-fish assemblages because they are one of the most underrepresented groups of animals in biodiversity and ecosystem function research and because they play an important role in aquatic ecosystems by removing other plants and animals from the community, actively produce fragments or feces containing the bodies of their prey, and by mechanically disturbing substrates, thereby increasing suspension of materials in the water column. In general, I found functional redundancy within stream-fish assemblages, with functional groups dividing niche space more evenly than species whether looking at the entire state, ecoregions, river basins, or individual locations, and the spatial and temporal structure of stream-fish assemblages is similar for functional and taxonomic perspectives. These results indicate the need for future studies on biodiversity and ecosystem function to explicitly examine functional diversity, or at least incorporate functional attributes of individuals, in order to gain a holistic understanding.

Search tactics are cognitive processes, or decision mechanisms, that organisms utilize to elicit a group of related and sequential behaviors that allow them to locate available resources such as food, mates, refugia, and habitats. However, our knowledge of the actual tactics that animals utilize while searching for resources is limited, and very little empirical evidence has been gathered. As a result, a suite of models of theoretical search tactics was developed to emulate the searching behaviors of mobile individuals so that inferences might be made about their decision mechanisms, and to determine whether individuals are capable of searching with a globally optimal solution. The theoretical tactics included four deterministic tactics (maximum-distance search, minimum-distance search, nearest-neighbor search, and trajectory-directed search) and five probabilistic tactics (reciprocal-distance search, inverse-squared-distance search, uniformly random search, Pearson random walk, and Levy random walk). These tactics included variations of random walks and systematic searches in an attempt to characterize biologically realistic searching behaviors. The theoretical search tactics were simulated with hypothetical predators finding and consuming the same sets of resources, assuming no satiation or learning, so that comparisons among the resulting search paths could be made. Correlated measures of path length, consistency of movement, path linearity and turn rate were used to characterize the geometry of the resulting search paths. Classieal multivariate analysis, including discriminant function analysis (DFA) and non-linear artificial neural networks (ANN), were used to discriminate among the theoretical tactics and to classify "unknown" search paths into one of the underlying search tactics, both based on the geometry of the resulting paths. Both linear and non-linear discriminatory anah ses revealed a strong overlap between the nearest-neighbor search and the minimum-distance search tactics. This overlap implies that it is possible for animals to utilize search tactics that mirror the globally optimal solution without having complete knowledge of the specific location of available resources. Furthermore, both methods of analyses demonstrated that inferences could be made about the actual tactics that animals utilize while searching for resources based on the geometry of the search paths, but with varying degrees of reliability.