Thesis (PhD)--University of South Australia, 2002.

Thesis (M.S.)--West Virginia University, 2004. / Title from document title page. Document formatted into pages; contains v, 50 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 35-38).

Thesis (Ph.D.) - University of St Andrews, May 2008.

Thesis (Ph. D.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 139-149). Also available on the World Wide Web.

Structure, in its many forms, is a central theme in theoretical population ecology. At a mathematical level, it arises as nonuniformities in the topology of nonlinear dynamical systems. I investigate a mechanism wherein a chaotic time series can have episodes of nearly periodic dynamics interspersed with more 'typical' irregular dynamics. This phenomenon frequently appears in biological models, and may explain patterns of alternating biennial and irregular dynamics in measles epidemics. I investigate the interaction between spatial structure and density-dependent population regulation with a simple model of two logistic maps coupled by diffusive migration. I examine two different consequences of spatial structure: scale-dependent interactions ("nonlocal interactions") and spatial variation in resource quality ("environmental heterogeneity"). Nonlocal interactions allow three general dynamical regimes: in-phase, out-of-phase, and uncorrelated. With environmental heterogeneity, the dynamics of the total population size can be approximated by a logistic map with the mean growth parameter of the two patches; the dynamics within a single patch are often less regular. Adding environmental heterogeneity to non-local interactions has little qualitative effect on the dynamics when the differences between patches are small; when the differences are large, uncorrelated dynamics are most likely to be seen, and there are interesting consequences for the stability of source-sink systems. A third type of structure arises when individuals differ from one another. Accurate prediction of extinction risk in small populations requires that a distinction be made between demographic stochasticity (variation among individuals) and environmental stochasticity (variation among years or sites). I describe and evaluate two tests to determine whether all the variation in population survivorship can be explained by demographic stochasticity alone. Both tests have appropriate probabilities of type I error, unless the survival probability is very low or very high. Small amounts of environmental stochasticity are often not detected by the tests, but the hypothesis of demographic stochasticity alone is consistently rejected when environmental stochasticity is large. I also show how to factor out deterministic sources of variability, such as density-dependence. I illustrate these tests with data on a population of Acorn Woodpeckers.

Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (leaves 119-134).

Thesis (Ph. D.)--Ohio State University, 2009. / Title from first page of PDF file. Includes bibliographical references (p. 119-137).

Environmental heterogeneity has often been suggested as a general explanation for patterns of diversity at scales ranging from individuals within populations to communities within landscapes. I evaluate this proposition using laboratory experiments with two microbial species, the unicellular chlorophyte Chlamydomonas reinhardtii and the common bacterium Pseudomonas fluorescens. These experiments contrast the fate of diversity following selection in heterogeneous and homogeneous environments. Specifically, I show that (1) an individual's breadth of adaptation evolves to match the amount of environmental variation, specialists evolving in environments that remain constant through time and generalists evolving in environments that vary through time irrespective of the scale at which environmental variation occurs relative to the lifetime of an individual; (2) the maintenance of diversity in a spatially heterogeneous environment is context-dependent, diversity being more readily maintained when environmental conditions are very different and genotypes are widely divergent; (3) selection in heterogeneous environments represents a plausible mechanism for two well-known patterns of diversity at large spatial scales, namely that between species diversity and both productivity and disturbance. This thesis thus demonstrates that environmental heterogeneity is a plausible, and perhaps very general, factor responsible for the diversity of natural communities.

Determining the factors responsible for the origin and maintenance of diversity remains a difficult problem in evolutionary biology. There is extensive theoretical work which suggests that environmental heterogeneity plays a major role. This theory argues that diversification is ultimately due to divergent natural selection for alternative resources. In this thesis I investigate adaptation and the evolution of diversity in experimental populations of the asexual bacterium Pseudomonas fluorescens. In all experiments I introduce clonal isolates of Pseudomonas to a novel environment and allow evolution to occur through the substitution of random mutations. Adaptation can then be quantified by comparing evolved genotypes to the ancestor. These experiments show that when Pseudomonas is selected in a complex environment containing several resources, sympatric genotypes adapt to use different resources, leading to the evolution of genetically diverse populations. In environments containing just a single resource, most genotypes adapt to use the same resource and no such diversity is observed. Adaptation in the experimental populations is caused by the fixation of beneficial mutations of intermediate fitness effect. My results highlight the value of microbial model systems for answering evolutionary questions and provide strong evidence for the role of ecological factors in the origin of diversity.

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