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dc.contributor.authorHasan, Elizabeth L.
dc.date.accessioned2023-02-03T22:07:07Z
dc.date.available2023-02-03T22:07:07Z
dc.date.issued2022-12
dc.identifier.urihttp://hdl.handle.net/11122/13121
dc.descriptionThesis (M.S.) University of Alaska Fairbanks, 2022en_US
dc.description.abstractSpecies distribution models are used to map and predict geographic distributions of animals based on environmental covariates. However, species distribution models often require high resolution habitat data and time-series data on animal locations. In data-limited regions with little animal survey data or habitat information, modeling is more challenging and often ignores important environmental attributes. For sea otters (Enhydra lutris), a federally protected keystone species with variable population trends across their range, predictive modeling of distributions has been successfully conducted in areas with an abundance of sea otter and habitat data. Here, we used open-access data across a single time step and leveraged a presence-only model, Maximum Entropy (MaxEnt), to investigate subtidal habitat associations (substrate and algal cover, bathymetry, and rugosity) of northern sea otters (E. lutris kenyoni) in a data-limited ecosystem, Kachemak Bay, Alaska. These habitat associations corroborated previous findings regarding the importance of bathymetry and understory kelp as predictors of sea otter presence. Novel associations were detected, as filamentous algae and shell litter were positively and negatively associated with sea otter presence, respectively. This study provides a quantitative framework for conducting species distribution modeling with limited temporal and spatial animal distribution and abundance data and utilized drop camera information as a novel approach to better understand habitat requirements of a stable sea otter population.en_US
dc.description.sponsorshipNational Park Service, U.S. Geological Survey, National Oceanic and Atmospheric Administration, U.S. Fish and Wildlife Service, Bureau of Ocean Energy Management, Alaska EPSCoR, Oil Spill Recovery Institute Graduate Research Fellowship, Oil Spill Recovery Institute Two Petes' Award, Coastal Marine Institute Graduate Student Initiative Award, North Pacific Research Board Graduate Student Research Award, Dieter Family Marine Science Research Scholarshipen_US
dc.language.isoen_USen_US
dc.subjectSea otteren_US
dc.subjectKachemak Bayen_US
dc.subjectHabitaten_US
dc.subject.otherMaster of Science in Marine Biologyen_US
dc.titleSpecies distribution modeling of northern sea otters (Enhydra lutris kenyoni) in a data-limited ecosystemen_US
dc.typeThesisen_US
dc.type.degreemsen_US
dc.identifier.departmentDepartment of Marine Biologyen_US
dc.contributor.chairKonar, Brenda
dc.contributor.committeeGorman, Kristen
dc.contributor.committeeColetti, Heather
refterms.dateFOA2023-02-03T22:07:08Z


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