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dc.contributorHassan, Sawsanen_US
dc.contributorClifton, Kathrynen_US
dc.contributorJohnson, Douglas E.en_US
dc.creatorLouhaichi, Mouniren_US
dc.date2018-10-07en_US
dc.date.accessioned2018-02-14T07:46:21Z
dc.date.available2018-02-14T07:46:21Z
dc.identifierhttps://link.springer.com/article/10.1007/s10457-017-0079-4en_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/KOC1I5D5en_US
dc.identifier.citationMounir Louhaichi, Sawsan Hassan, Kathryn Clifton, Douglas E. Johnson. (7/10/2018). A reliable and non-destructive method for estimating forage shrub cover and biomass in arid environments using digital vegetation charting technique. Agroforestry Systems, 92 (5), pp. 1341-1352.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/7799
dc.description.abstractDespite the importance of fodder shrubs to small ruminant diets and production in arid and semiarid ecosystems, they are often not considered when quantifying grazing land potential. This oversight is mainly due to the time consuming and costly traditional techniques used to estimate shrub biomass. The shrub fodder component should be measured to avoid underestimation of the carrying capacity of rangelands. In this study, we present a fast, reliable and non-destructive method to estimate canopy vegetation cover to obtain aboveground shrub biomass. The experiment was conducted under field conditions in northwest Syria, where seedlings of seven shrub species were monitored for one year: Atriplex leucoclada (Moq.) Boiss., A. halimus L., A. lentiformis (Torr.) S. Watson, A. canescens (Pursh) Nutt., A. nummularia Lindl., Salsola vermiculata L. and Haloxylon aphyllum (C.A. Meyer) Bunge. The experimental layout was a randomized complete block design with five replications. We explored the effectiveness of digital vegetation charting technique (DVCT) for estimating shrub canopy cover. Aboveground shrub biomasswas clipped to estimate the dry matter (DM) weight per species and to determine its relationship to canopy cover. In this study, an estimate of greenness (percent green vegetation cover) was extracted by way of greenness algorithms. Simple linear regressions between vegetation cover and biomass for 210 plots were performed. The cover of the seven species differed (P\0.01): A. leucoclada had the highest vegetation cover (56%) and H. aphyllum the lowest (7%). Vegetation cover and DM biomass were positively correlated (P\0.01) with R-squared ranging from 0.66 (H. aphyllum) to 0.84 (S. vermiculata). Our method provided reasonable estimations of canopy coverage which could predict aboveground phytomass. We conclude that DVCT offers a rapid, reliable and consistent measurement of shrub cover and biomass provided that shrubs have open architecture. This study shows the potential of digital cameras and image processing to determine cover/biomass in a nondestructive, timely and cost efficient way.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherSpringerOpenen_US
dc.rightsCC-BY-4.0en_US
dc.sourceAgroforestry Systems;92,(2017) Pagination 1341,1352en_US
dc.subjectvegmeasureen_US
dc.subjectvegetation coveren_US
dc.titleA reliable and non-destructive method for estimating forage shrub cover and biomass in arid environments using digital vegetation charting techniqueen_US
dc.typeJournal Articleen_US
cg.creator.idLouhaichi, Mounir: 0000-0002-4543-7631en_US
cg.creator.idHassan, Sawsan: 0000-0002-5057-8957en_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocrangelandsen_US
cg.subject.agrovocremote sensingen_US
cg.subject.agrovocimage processingen_US
cg.subject.agrovochalophytesen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerOregon State University - OSU United Statesen_US
cg.contributor.crpCGIAR Research Program on Livestock Agri-Food Systems - LAFSen_US
cg.contributor.funderInternational Livestock Research Institute - ILRIen_US
cg.contributor.projectCGIAR Research Program on Livestock Agri-Food Systemsen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.regionGlobalen_US
cg.coverage.start-date2014-01-07en_US
cg.coverage.end-date2016-09-25en_US
cg.contactm.louhaichi@cgiar.orgen_US
cg.identifier.doihttps://dx.doi.org/10.1007/s10457-017-0079-4en_US
dc.identifier.statusOpen accessen_US
mel.project.openhttps://mel.cgiar.org/projects/237en_US
mel.impact-factor1.201en_US


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