Show simple item record

dc.contributor.authorJensen, M. E.
dc.contributor.authorDibenedetto, J. P.
dc.contributor.authorBarber, J. A.
dc.contributor.authorMontagne, C.
dc.contributor.authorBourgeron, P. S.
dc.date.accessioned2020-09-18T04:55:52Z
dc.date.available2020-09-18T04:55:52Z
dc.date.issued2001-09-01
dc.identifier.citationJensen, M. E., Dibenedetto, J. P., Barber, J. A., Montagne, C., & Bourgeron, P. S. (2001). Spatial modeling of rangeland potential vegetation environments. Journal of Range Management, 54(5), 528-536.
dc.identifier.issn0022-409X
dc.identifier.doi10.2307/4003581
dc.identifier.doi10.2458/azu_jrm_v54i5_jensen
dc.identifier.urihttp://hdl.handle.net/10150/643587
dc.description.abstractPotential vegetation environments (e.g., habitat types, range sites, ecological sites) are important to land managers because they provide a conceptual basis for the description of resource potentials and ecological integrity. Efficient use of potential vegetation classifications in regional or subregional scale assessments of ecosystem health has been limited to date, however, because traditional ecological unit mapping procedures often treat such classifications as ancillary information in the map unit description. Accordingly, it is difficult, if not impossible, to describe the precise location, patch size, and spatial arrangement of potential vegetation environments from most traditional ecological unit maps. Recent advances in remote sensing, geographic information systems (GIS), terrain modeling, and climate interpolation facilitate the direct mapping of potential vegetation through a predictive process based on gradient analysis and ecological niche theory. In this paper, we describe how a predictive vegetation mapping process was used to develop a 30 m raster-based map of 4 grassland, 5 shrubland, and 6 woodland habitat types across the Little Missouri National Grasslands, North Dakota. Discriminant analysis was used in developing this potential vegetation map based on 6 primary geographic information system themes. Geoclimatic subsections and remotely sensed vegetation lifeform maps were used in predictive model stratification. Terrain indices, LANDSAT satellite imagery, and interpolated climate information were used as independent (predictor) variables in model construction. A total of 616 field plots with known habitat type membership were used as dependent variables and assessed by a jackknife discriminant analysis procedure. Accuracy values of our map ranged from 54 to 77% in grasslands, 62 to 100% in shrublands, and 70 to 100% in woodlands dependent on geoclimatic subsection setting. Techniques are also described for generalizing the 30 m pixel resolution habitat type map to appropriate ecological unit maps (e.g., landtype associations) for use in ecosystem health assessments and land use planning.
dc.language.isoen
dc.publisherSociety for Range Management
dc.relation.urlhttps://rangelands.org/
dc.rightsCopyright © Society for Range Management.
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectLittle Missouri National Grasslands
dc.subjectsatellite surveys
dc.subjectmapping
dc.subjectLandsat
dc.subjectshrublands
dc.subjectland use planning
dc.subjecthabitats
dc.subjecttopography
dc.subjectsatellite imagery
dc.subjectgrasslands
dc.subjectprediction
dc.subjectrange condition
dc.subjectplant communities
dc.subjectwoodlands
dc.subjectclimatic factors
dc.subjectgrazing
dc.subjectNorth Dakota
dc.subjecthabitat types
dc.subjectecological sites
dc.subjectrange sites
dc.subjectecological classification
dc.subjectgeographic information systems
dc.subjectremote sensing
dc.subjectvegetation mapping
dc.subjectecological units
dc.titleSpatial modeling of rangeland potential vegetation environments
dc.typetext
dc.typeArticle
dc.identifier.journalJournal of Range Management
dc.description.collectioninformationThe Journal of Range Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact lbry-journals@email.arizona.edu for further information.
dc.eprint.versionFinal published version
dc.description.admin-noteMigrated from OJS platform August 2020
dc.source.volume54
dc.source.issue5
dc.source.beginpage528-536
refterms.dateFOA2020-09-18T04:55:52Z


Files in this item

Thumbnail
Name:
9651-9532-1-PB.pdf
Size:
277.4Kb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record