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dc.contributor.authorWinder, Samantha
dc.date.accessioned2019-01-11T01:50:21Z
dc.date.available2019-01-11T01:50:21Z
dc.date.issued2018-05
dc.identifier.urihttp://hdl.handle.net/11122/9735
dc.descriptionMaster's Project (M.S.) University of Alaska Fairbanks, 2018en_US
dc.description.abstractSpecies distribution models (SDMs) describe the relationship between where a species occurs and underlying environmental conditions. For this project, I created SDMs for the five tree species that occur in Yukon-Charley Rivers National Preserve (YUCH) in order to gain insight into which environmental covariates are important for each species, and what effect each environmental condition has on that species' expected occurrence or abundance. I discuss some of the issues involved in creating SDMs, including whether or not to incorporate spatially explicit error terms, and if so, how to do so with generalized linear models (GLMs, which have discrete responses). I ran a total of 10 distinct geostatistical SDMs using Markov Chain Monte Carlo (Bayesian methods), and discuss the results here. I also compare these results from YUCH with results from a similar analysis conducted in Denali National Park and Preserve (DNPP).en_US
dc.language.isoen_USen_US
dc.subjectTreesen_US
dc.subjectEnvironmental aspectsen_US
dc.subjectAlaskaen_US
dc.subjectYukon-Charley Rivers National Preserveen_US
dc.subjectGeographical distributionen_US
dc.titleAnalyzing tree distribution and abundance in Yukon-Charley Rivers National Preserve: developing geostatistical Bayesian models with count dataen_US
dc.typeOtheren_US
dc.type.degreems
dc.identifier.departmentDepartment of Mathematics and Statistics
dc.contributor.chairShort, Margaret
dc.contributor.committeeRoland, Carl
dc.contributor.committeeGoddard, Scott
dc.contributor.committeeMcIntyre, Julie
refterms.dateFOA2020-03-06T01:34:07Z


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