Hierarchical models for the anlaysis of species distributions and abundances: development and applications

There is a strong need for statistical methods that can maximize the utility of ecological data while providing accurate estimates of species abundances and distributions. This dissertation aims to build on current statistical models using Bayesian hierarchical approaches to advance these methods. Chapters one, two, and three utilize a multi-species modeling framework to estimate species occurrence probabilities. Chapter one presents a model to assess the community response of breeding birds to habitat fragmentation. The results demonstrate the importance of understanding the responses of both individual, and groups of species, to environmental heterogeneity while illustrating the utility of hierarchical models for inference about species richness. Chapter two demonstrates how the multi-species modeling framework can be used to evaluate conservation actions through a component that incorporates species-specific responses to management treatments. In Chapter three, I develop a method for validating predictions generated by the multi-species model that accounts for detection biases in evaluation data. I build competing models using wetland breeding amphibian data and test their abilities to predict occupancy at unsampled locations. Chapters four and five develop count models that are used to estimate population abundances in relation to environmental and climate variables. In Chapter four, I employ a Poisson regression designed to determine how climate affects the annual abundances of migrating monarch butterflies. I incorporate the climate conditions experienced both during a spring migration phase, as well as during summer recruitment. In Chapter five, I analyze sea duck data to characterize the spatial and temporal distributions along the U.S. and Canadian Atlantic coast. I model count data for five species using a zero-inflated negative binomial model that includes latitude, habitat covariates, and the North Atlantic Oscillation. The results from these two chapters demonstrate how Bayesian models can be used to elucidate complicated species-climate relationships. The chapters of this dissertation illustrate creative development and application of advanced statistical methods to complex biological systems. These applications provide a practical framework for dealing with highly aggregated species and uneven species distributions in community analyses, as well as a method for evaluating occurrence estimates that accounts for detection biases. My results highlight the dynamic relationships between population and community structure, habitat, and climate

Keepers of the vision : students\u27 perceptions of themselves as creators and changers.

This qualitative study undertook an exploration into the connections between creativity and change/transformation. Its purpose was to begin to understand how creativity could be used as a tool for empowerment, liberation, and transformation, and how creative techniques could be incorporated into educational efforts. Participants were students who were enrolled in an undergraduate course designed and taught by the researcher, entitled Creativity and Change. Using their coursework and interviews, this research explored how these student/participants perceived of themselves as creative individuals and as persons capable of making change in their lives and in the world, how they connected the two concepts of creativity and change, and how they utilized creative processes in envisioning change strategies. This study broke ground in two areas of creativity research: (1) looking at the effects and benefits of a creativity class from the perspective of the students who were enrolled in it, and (2) expanding on the research on climate for creativity by connecting creativity to personal and social change efforts, again, from the perspective of students. The results of this study are a beginning to better understanding the multiple aspects of creativity--expression, process, products--and their importance ta self-development, empowerment, and liberation in education. The responses of the students who participated in this study were encouraging in supporting the premise that there are multiple connections between creativity and change. They demonstrated the effects of creativity in increasing self-knowledge and self-esteem, making connections between people, envisioning solutions to social problems, expanding perceptions to incorporate different perspectives and viewpoints, breaking boundaries, and taking the risks that transformation demands. These student/participants demonstrated, through the discovery of their own creative, capable selves, a sense of empowerment arising from the knowledge that I CAN. Being able to think outside of conventional structures and paradigms, challenging dualistic thought, and incorporating holistic teaching and learning strategies are some of the strengths and gifts of creativity. This study has shown that the openness and imagination of creative thought and behavior can become a tool to dismantle the injustices of the world and create new, transformative paradigms

Integrated Population Models: Achieving their Potential

Precise and accurate estimates of abundance and demographic rates are primary quantities of interest within wildlife conservation and management. Such quantities provide insight into population trends over time and the associated underlying ecological drivers of the systems. This information is fundamental in managing ecosystems, assessing species conservation status and developing and implementing effective conservation policy. Observational monitoring data are typically collected on wildlife populations using an array of different survey protocols, dependent on the primary questions of interest. For each of these survey designs, a range of advanced statistical techniques have been developed which are typically well understood. However, often multiple types of data may exist for the same population under study. Analyzing each data set separately implicitly discards the common information contained in the other data sets. An alternative approach that aims to optimize the shared information contained within multiple data sets is to use a “model-based data integration” approach, or more commonly referred to as an “integrated model.” This integrated modeling approach simultaneously analyzes all the available data within a single, and robust, statistical framework. This paper provides a statistical overview of ecological integrated models, with a focus on integrated population models (IPMs) which include abundance and demographic rates as quantities of interest. Four main challenges within this area are discussed, namely model specification, computational aspects, model assessment and forecasting. This should encourage researchers to explore further and develop new practical tools to ensure that full utility can be made of IPMs for future studies

spOccupancy: An R package for single-species, multi-species, and integrated spatial occupancy models

Occupancy modeling is a common approach to assess spatial and temporal species distribution patterns, while explicitly accounting for measurement errors common in detection-nondetection data. Numerous extensions of the basic single species occupancy model exist to address dynamics, multiple species or states, interactions, false positive errors, autocorrelation, and to integrate multiple data sources. However, development of specialized and computationally efficient software to fit spatial models to large data sets is scarce or absent. We introduce the spOccupancy R package designed to fit single-species, multi-species, and integrated spatially-explicit occupancy models. Using a Bayesian framework, we leverage P\'olya-Gamma data augmentation and Nearest Neighbor Gaussian Processes to ensure models are computationally efficient for potentially massive data sets. spOccupancy provides user-friendly functions for data simulation, model fitting, model validation (by posterior predictive checks), model comparison (using information criteria and k-fold cross-validation), and out-of-sample prediction. We illustrate the package's functionality via a vignette, simulated data analysis, and two bird case studies, in which we estimate occurrence of the Black-throated Green Warbler (Setophaga virens) across the eastern USA and species richness of a foliage-gleaning bird community in the Hubbard Brook Experimental Forest in New Hampshire, USA. The spOccupancy package provides a user-friendly approach to fit a variety of single and multi-species occupancy models, making it straightforward to address detection biases and spatial autocorrelation in species distribution models even for large data sets.Comment: 20 pages, 2 figure