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Advances in Ecological Statistics

Author:
Bartley, Meridith
Published:
[University Park, Pennsylvania] : Pennsylvania State University, 2021.
Physical Description:
1 electronic document
Additional Creators:
Hanks, Ephraim Mont
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Restricted (PSU Only).
Summary:
In this dissertation I will outline and discuss three research projects to be completed as part of my dissertation. In Chapter 2 I develop a novel penalized stochastic process within a Hidden Markov model framework. I apply this model to high resolution ant feeding interaction data. In Chapter 3 I extend previous work that identified extrapolation by applying the predictive variance from the univariate setting to the multivariate case. I illustrate this approach through an analysis of jointly modeled lake nutrients and indicators of algal biomass and water clarity in over 7000 inland lakes from across the Northeast and Mid-west US. The use of Multivariate Predictive Variance (MVPV) measures and multiple cutoff values when exploring the validity of predictions made from multivariate statistical models can help guide ecological inferences. In Chapter 4 I develop analytical approaches to combine individual tracking data of migrating birds tracked using the ARGOS system with population- and community-level relative abundance obtained from observations in eBird. With this data fusion approach researchers subdivide bird populations into subpopulations with distinct migratory patterns. Results will guide future bird sampling efforts of threatened and endangered species while also improving our understanding of migratory connectivity. This research is necessary for advancements in the fields of bird migration and animal movement modelling.
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Dissertation Note:
Ph.D. Pennsylvania State University 2021.
Technical Details:
The full text of the dissertation is available as an Adobe Acrobat .pdf file ; Adobe Acrobat Reader required to view the file.
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