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Regional data refine local abundance models: modeling plant species abundance distributions on the Central Plains

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dc.contributor.authorYoung, Nicholas E., author
dc.contributor.authorStohlgren, Thomas J., advisor
dc.contributor.authorKelly, Eugene Francis, committee member
dc.contributor.authorGraham, James J., committee member
dc.contributor.authorEvangelista, Paul Harrison, committee member
dc.coverage.spatialColorado
dc.date.accessioned2007-01-03T04:55:13Z
dc.date.available2007-01-03T04:55:13Z
dc.date.issued2010
dc.description.abstractSpecies distribution models are frequently used to predict species occurrences in novel conditions, yet few studies have examined the effects of extrapolating locally collected data to regional scale landscapes. Using boosted regression trees, I examined the issues of spatial scale and errors associated with extrapolating species distribution models developed using locally collected abundance data to regional extents for a native and alien plant species across a portion of the central plains in Colorado. Topographic, remotely sensed, land cover and soil taxonomic predictor variables were used to develop the models. Predicted means and ranges were compared among models and predictions were compared to observed values between local and regional extent models. All models had significant predictive ability (p < 0.001). My results suggested: (1) extrapolating local models to regional extents may restrict predictions; (2) modeling species abundance may prove more useful than models of species presence; (3) multiple sources of predictors may improve model results at different extents; and (4) regional data can help refine and improve local model predictions. Regional sampling designed in concert with large sampling frameworks such as the National Ecological Observatory Network, Inc (NEON) may improve our ability to monitor changes in local species abundance.
dc.format.mediumborn digital
dc.format.mediummasters theses
dc.identifierYoung_colostate_0053N_10228.pdf
dc.identifierETDF2010100009FRWS
dc.identifier.urihttp://hdl.handle.net/10217/45982
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectabundance
dc.subjectextrapolation
dc.subjectcentral plains
dc.subjectboosted regression trees
dc.subject.lcshPlant ecology -- Colorado
dc.subject.lcshPhytogeography -- Colorado
dc.subject.lcshPlants -- Habitat -- Research -- Methods
dc.subject.lcshSpatial ecology -- Colorado
dc.titleRegional data refine local abundance models: modeling plant species abundance distributions on the Central Plains
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineForest, Rangeland, and Watershed Stewardship
thesis.degree.grantorColorado State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.S.)

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