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dc.contributor.authorBowker, Matthew A.
dc.contributor.authorBelnap, Jayne
dc.contributor.authorMiller, Mark E.
dc.date.accessioned2020-09-05T07:38:07Z
dc.date.available2020-09-05T07:38:07Z
dc.date.issued2006-09-01
dc.identifier.citationBowker, M. A., Belnap, J., & Miller, M. E. (2006). Spatial modeling of biological soil crusts to support rangeland assessment and monitoring. Rangeland Ecology & Management, 59(5), 519-529.
dc.identifier.issn0022-409X
dc.identifier.doi10.2111/05-179R1.1
dc.identifier.urihttp://hdl.handle.net/10150/643103
dc.description.abstractBiological soil crusts are a diverse soil surface community, prevalent in semiarid regions, which function as ecosystem engineers and perform numerous important ecosystem services. Loss of crusts has been implicated as a factor leading to accelerated soil erosion and other forms of land degradation. To support assessment and monitoring efforts aimed at ensuring the sustainability of rangeland ecosystems, managers require spatially explicit information concerning potential cover and composition of biological soil crusts. We sampled low disturbance sites in Grand Staircase-Escalante National Monument (Utah, USA) to determine the feasibility of modeling the potential cover and composition of biological soil crusts in a large area. We used classification and regression trees to model cover of four crust types (light cyanobacterial, dark cyanobacterial, moss, lichen) and 1 cyanobacterial biomass proxy (chlorophyll a), based upon a parsimonious set of GIS (Geographic Information Systems) data layers (soil types, precipitation, and elevation). Soil type was consistently the best predictor, although elevation and precipitation were both invoked in the various models. Predicted and observed values for the dark cyanobacterial, moss, and lichen models corresponded moderately well (R2 = 0.49, 0.64, 0.55, respectively). Cover of late successional crust elements (moss + lichen + dark cyanobacterial) was also successfully modeled (R2 = 0.64). We were less successful with models of light cyanobacterial cover (R2 = 0.22) and chlorophyll a (R2 = 0.09). We believe that our difficulty modeling chlorophyll a concentration is related to a severe drought and subsequent cyanobacterial mortality during the course of the study. These models provide the necessary reference conditions to facilitate the comparison between the actual cover and composition of biological soil crusts at a given site and their potential cover and composition condition so that sites in poor condition can be identified and management actions can be taken. 
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.subjectdegradation thresholds
dc.subjectdrylands
dc.subjectcryptobiotic soil crusts
dc.subjectlichens
dc.subjectmosses
dc.subjectrangeland health
dc.titleSpatial Modeling of Biological Soil Crusts to Support Rangeland Assessment and Monitoring
dc.typetext
dc.typeArticle
dc.identifier.journalRangeland Ecology & Management
dc.description.collectioninformationThe Rangeland Ecology & 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.description.admin-noteLegacy DOIs that must be preserved: 10.2458/azu_jrm_v59i5_bowker
dc.source.volume59
dc.source.issue5
dc.source.beginpage519-529
refterms.dateFOA2020-09-05T07:38:07Z


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