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dc.contributor.authorSeidel, Dominik
dc.contributor.authorAnnighöfer, Peter
dc.contributor.authorAmmer, Christian
dc.contributor.authorEhbrecht, Martin
dc.contributor.authorWillim, Katharina
dc.contributor.authorBannister, Jan R.
dc.contributor.authorSoto, Daniel P.
dc.date.accessioned2021-04-21T16:17:03Z
dc.date.available2021-04-21T16:17:03Z
dc.date.issued2021
dc.identifier.citationSeidel, D.; Annighöfer, P.; Ammer, C.; Ehbrecht, M.; Willim, K.; Bannister, J.; Soto, D.P. Quantifying Understory Complexity in Unmanaged Forests Using TLS and Identifying Some of Its Major Drivers. Remote Sens. 2021, 13, 1513. https:// doi.org/10.3390/rs13081513es_CL
dc.identifier.otherhttps://doi.org/10.3390/rs13081513
dc.identifier.urihttps://bibliotecadigital.infor.cl/handle/20.500.12220/30437
dc.description.abstractThe structural complexity of the understory layer of forests or shrub layer vegetationin open shrublands affects many ecosystem functions and services provided by these ecosystems. We investigated how the basal area of the overstory layer, annual and seasonal precipitation, annual mean temperature, as well as light availability affect the structural complexity of the understory layer along a gradient from closed forests to open shrubland with only scattered trees. Using terrestrial laser scanning data and the understory complexity index (UCI), we measured the structural complexity of sites across a wide range of precipitation and temperature, also covering a gradient in light availability and basal area. We found significant relationships between the UCI and tree basal area as well as canopy openness. Structural equation models (SEMs) confirmed significant direct effects of seasonal precipitation on the UCI without mediation through basal area or canopy openness. However, annual precipitation and temperature effects on the UCI are mediated through canopy openness and basal area, respectively. Understory complexity is, despite clear dependencies on the available light and overall stand density, significantly and directly driven by climatic parameters, particularly the amount of precipitation during the driest month.es_CL
dc.language.isoenes_CL
dc.publisherMDPIes_CL
dc.subjectCARACTERISTICAS DEL RODALes_CL
dc.subjectSOTOBOSQUEes_CL
dc.subjectAREA BASALes_CL
dc.subjectPRECIPITACION ATMOSFERICAes_CL
dc.subjectTEMPERATURAes_CL
dc.subjectLUZ DEL DIAes_CL
dc.subjectFACTORES AMBIENTALESes_CL
dc.subjectDENSIDAD DEL RODALes_CL
dc.titleQuantifying understory complexity in unmanaged forests using TLS and identifying some of its major driverses_CL
dc.typeArtículo de revistaes_CL
infor.publicadoenRemote Sensing 2021, 13, 1513es_CL
infor.sedeSede Los Ríoses_CL
infor.operadorplves_CL


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