Ecological and evolutionary analyses of range limits and biodiversity patterns
Behrman, Kathrine Delany
MetadataShow full item record
The goal of this dissertation is to further our understanding of how spatially heterogeneous landscapes may impact the formation of range boundaries that then aggregate to form large-scale biodiversity patterns. These patterns have been analyzed from many different perspectives by ecologists, evolutionary biologist, and physiologists using a variety of different theoretical, statistical, and mechanistic models. For some species, there is an obvious abrupt change in the environment causing a range boundary. Other environments change gradually, and it is unclear why species fail to adapt and expand their range. The first chapter develops a novel theoretical model of how the establishment of new mutations allows for adaptation to an environmental gradient, when there is no genetic variation for the trait that limits the range. Shallow environmental gradients favor mutations that arise nearer to the range margin, have smaller phenotypic effects, and allow for proportionately larger expansions than steep gradients. Mutations that allow for range expansion tend to have large phenotypic effects causing substantial range expansions. Spatial and temporal variation in climatic and environmental variables is important for understanding species response to climate change. The second chapter uses a mechanistic model to simulate switchgrass (Panicum virgatum L.) productivity across the central and eastern U.S. for current and future climate conditions. Florida and the Gulf Coast of Texas and Louisiana have the highest predicted current and future yields. Regions where future temperature and precipitation are anticipated to increase, larger future yields are expected. Large-scale geographic patterns of biodiversity are documented for many taxa. The mechanisms allowing for the coexistence of more of species in certain regions are poorly understood. The third chapter employs a newly developed wavelet lifting technique to extract scale-dependent patterns from irregularly spaced two-dimensional ecological data and analyzes the relationship between breeding avian richness and four energy variables. Evapotranspiration, temperature, and precipitation are significant predictors of richness at intermediate-to-large scales. Net primary production is the only significant predictor across small-to-large scales, and explains the most variation in richness (~40%) at an intermediate scale. Changes in the species-energy relationship with scale, may indicate a shift in the mechanism governing species richness.