Climate-correlative modeling of phytogeography at the watershed scale.

Persistent Link:
http://hdl.handle.net/10150/191246
Title:
Climate-correlative modeling of phytogeography at the watershed scale.
Author:
Drake, Samuel Edward,1960-
Issue Date:
2000
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
The goal of this research was to develop a watershed-scale model for predicting changes in plant species distribution and abundance (phytogeography) that might occur as a result of changes in climatic factors with global warming. The model was designed: 1) to be spatially explicit and applicable across the entire watershed; 2) to apply to a number of particular species rather than general vegetation types; 3) to predict abundance as well as presence/absence; and 4) to work with simple environmental data, but reflect a biological rationale. Correlations were sought between current phytogeography in the watershed and the synoptic climate variables mean annual temperature, total annual precipitation and cool-/warm-season precipitation ratio. The contribution of edaphic and topographic variables to correlative models was examined and found to be negligible. The correlations established for current conditions were extended to hypothetical future conditions of changed climate in which the values of the variables were manipulated and the model run to produce predictions of altered future phytogeographies. Twenty-seven different hypothetical climate scenarios were modeled, incorporating a 1°C or 2°C rise in temperature with as much as a 10% increase or decrease in seasonal precipitation. Spatial articulation of the model was achieved through raster analysis of gridcell based data layers in a geographic information system. Primary input layers were a series of high-resolution (360x360m) interpolated climate-variable surfaces and a geographically referenced database of plant species presence and abundance derived from an aerial videography sample of the watershed. Logistic regression analysis was used to calculate, for a given set of conditions, the most probable state (present/absent) and abundance class for ten plant species at each grid-cell location in the watershed. Fragmentation of species' distributions before and after change was examined. Results for all studied species showed marked changes in distribution and abundance with temperature rise. Desert species will likely increase in abundance and occupiable area as forest and woodland species decrease, but much depends on the interaction of precipitation with temperature. Model predictions are conservative compared with paleoecological evidence of past changes.
Type:
Dissertation-Reproduction (electronic); text
Keywords:
Hydrology.; Watershed management -- Arizona.
Degree Name:
Ph. D.
Degree Level:
doctoral
Degree Program:
Arid Lands Resource Sciences; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Marsh, Stuart E.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleClimate-correlative modeling of phytogeography at the watershed scale.en_US
dc.creatorDrake, Samuel Edward,1960-en_US
dc.contributor.authorDrake, Samuel Edward,1960-en_US
dc.date.issued2000en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThe goal of this research was to develop a watershed-scale model for predicting changes in plant species distribution and abundance (phytogeography) that might occur as a result of changes in climatic factors with global warming. The model was designed: 1) to be spatially explicit and applicable across the entire watershed; 2) to apply to a number of particular species rather than general vegetation types; 3) to predict abundance as well as presence/absence; and 4) to work with simple environmental data, but reflect a biological rationale. Correlations were sought between current phytogeography in the watershed and the synoptic climate variables mean annual temperature, total annual precipitation and cool-/warm-season precipitation ratio. The contribution of edaphic and topographic variables to correlative models was examined and found to be negligible. The correlations established for current conditions were extended to hypothetical future conditions of changed climate in which the values of the variables were manipulated and the model run to produce predictions of altered future phytogeographies. Twenty-seven different hypothetical climate scenarios were modeled, incorporating a 1°C or 2°C rise in temperature with as much as a 10% increase or decrease in seasonal precipitation. Spatial articulation of the model was achieved through raster analysis of gridcell based data layers in a geographic information system. Primary input layers were a series of high-resolution (360x360m) interpolated climate-variable surfaces and a geographically referenced database of plant species presence and abundance derived from an aerial videography sample of the watershed. Logistic regression analysis was used to calculate, for a given set of conditions, the most probable state (present/absent) and abundance class for ten plant species at each grid-cell location in the watershed. Fragmentation of species' distributions before and after change was examined. Results for all studied species showed marked changes in distribution and abundance with temperature rise. Desert species will likely increase in abundance and occupiable area as forest and woodland species decrease, but much depends on the interaction of precipitation with temperature. Model predictions are conservative compared with paleoecological evidence of past changes.en_US
dc.description.notehydrology collectionen_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.typetexten_US
dc.subjectHydrology.en_US
dc.subjectWatershed management -- Arizona.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineArid Lands Resource Sciencesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairMarsh, Stuart E.en_US
dc.contributor.committeememberMcClaran, Mitchel P.en_US
dc.contributor.committeememberHutchinson, Charles F.en_US
dc.contributor.committeememberGuertin, D. Phillipen_US
dc.contributor.committeememberHuete, Alfredo R.en_US
dc.identifier.oclc213867982en_US
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