The Effects Of Climate Change On The Population Dynamics Of Trumpeter Swans

Abstract

Survey data for trumpeter swans were collected throughout Alaska since 1968, but due to design difficulties and past analytical limitations, previous analyses were limited to simple summary statistics. The main purpose of my work was to rigorously analyze these data using advanced methods and determine rates of population change, the effects of environmental change on habitat use, and the influences of habitat features on habitat occupancy. I estimated that the adult population grew at a rate of 5.9% (95% credible interval = 5.2% to 6.6%) and production of cygnets increased at 5.3% (95% credible interval = 2.2% to 8.0%) annually. I also found evidence that variation in occupancy was positively related to average annual temperature, indicating that climate warming positively affects trumpeter swans. However, I found no evidence that small levels of pond shrinkage (-3% on average), another effect of climate change, was affecting swan occupancy in the Cordova area. Habitat occupancy was dependent on wetland type and increased with wetland size, history of fire, and warmer springs. Increased elevation and the presence of transportation infrastructure negatively affected occupancy. An additional goal for this project was to further develop analytical methods for analyzing survey and survival data in general. To accomplish this I developed Bayesian hierarchical models that: account for missing data, provide estimates of goodness-of-fit, and use multiple random effects to help explain heterogeneity in the data. These problems have proven to be difficult or impossible to overcome using previously available methods and can cause misleading results if inadequately addressed. I also show that previous methods can lead to underestimates of survival in the presence of overdispersion. The Bayesian survival model that I present explicitly accounts for overdispersion and provides an estimate of goodness-of-fit for the survival of nests and young. These features improve estimates for data of this type by reducing bias and providing an estimate of model adequacy. Overall this work advances our understanding of how the ecology of a vertebrate avian species is affected by climate change and provides advances in methods for analyzing complex data streams with problems commonly encountered in studies of wildlife populations.