COS 31-8: Demographic variability, scale, and evaluation of niche theory
Jeffrey M. Diez, Lincoln University and H. Ronald Pulliam, University of Georgia.
Many studies describe demographic variability in natural populations but very few link basic vital rates and overall population growth rates to abiotic driving variables. Establishing these links to the abiotic environment is crucial, however, for testing niche theory and making predictions of species responses to environmental change. Moreover, quantification of the associated variability and uncertainty of these relationships is critical for proper assessment of both theory and predictions. In this study we integrate 6 years of demographic and abiotic monitoring to estimate the responses of survival, growth, reproduction and overall population growth to environmental heterogeneity at different spatial scales. Using hierarchical Bayesian methods for parameter estimation and prediction across a range of environmental conditions we show how light and soil moisture influence vital rates and overall population growth rates of a terrestrial orchid, Goodyera pubescens, native to eastern North America. Niche theory and the related concepts of dispersal limitation and source-sink dynamics suggest the possibility of substantial population sizes even in habitat that is not suitable enough to maintain the population, as well as potentially sizable absences from suitable habitat. Comparisons with observed distributions suggest a lack of correspondence between distribution and suitability that changes across spatial scales. Supportive of predictions of source-sink theory and dispersal limitation we find this species absent from substantial areas of predicted suitable habitat and present in some predicted unsuitable habitats. This pattern is most evident at very local spatial scales, while the correspondence between abundance and suitability increases with increasing spatial scale. We also discuss how the uncertainty associated with estimates influences the evaluation of theory and helps inform predictions of species responses to abiotic gradients.