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Metadata Access | Data from: Using an Ultraviolet Light Test to Improve Sagebrush Identification and Predict Forage Quality for Wildlife

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  <identifier identifierType="DOI">10.7923/Y123-YH55</identifier>
  <creators>
    <creator>
      <creatorName nameType="Personal">Rosentreter, Roger</creatorName>
      <givenName>Roger</givenName>
      <familyName>Rosentreter</familyName>
    </creator>
    <creator>
      <creatorName nameType="Personal">Robb, Brecken</creatorName>
      <givenName>Brecken</givenName>
      <familyName>Robb</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="https://orcid.org">https://orcid.org/0000-0001-9016-249X</nameIdentifier>
      <affiliation affiliationIdentifier="https://ror.org/02e3zdp86" affiliationIdentifierScheme="ROR" schemeURI="https://ror.org">Boise State University</affiliation>
    </creator>
    <creator>
      <creatorName nameType="Personal">Sorensen Forbey, Jennifer</creatorName>
      <givenName>Jennifer</givenName>
      <familyName>Sorensen Forbey</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="https://orcid.org">https://orcid.org/0000-0001-6069-4049</nameIdentifier>
      <affiliation affiliationIdentifier="https://ror.org/02e3zdp86" affiliationIdentifierScheme="ROR" schemeURI="https://ror.org">Boise State University</affiliation>
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  <titles>
    <title xml:lang="en">Data From: Using an Ultraviolet Light Test to Improve Sagebrush Identification and Predict Forage Quality for Wildlife</title>
  </titles>
  <publisher>University of Idaho</publisher>
  <publicationYear>2021</publicationYear>
  <resourceType resourceTypeGeneral="Dataset">Dataset</resourceType>
  <subjects>
    <subject subjectScheme="Fields of Science and Technology (FOS)" schemeURI="http://www.oecd.org/science/inno" valueURI="http://www.oecd.org/science/inno/38235147.pdf">FOS: Biological sciences</subject>
    <subject subjectScheme="Fields of Science and Technology (FOS)" schemeURI="http://www.oecd.org/science/inno" valueURI="http://www.oecd.org/science/inno/38235147.pdf">FOS: Chemical sciences</subject>
    <subject subjectScheme="Fields of Science and Technology (FOS)" schemeURI="http://www.oecd.org/science/inno" valueURI="http://www.oecd.org/science/inno/38235147.pdf">FOS: Environmental engineering</subject>
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  <language>en</language>
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  <descriptions>
    <description xml:lang="en" descriptionType="Abstract">Sagebrush identification can be improved by using a relatively easy ultraviolet (UV) light test on specimens. Sagebrush produces a variety of water-soluble polyphenols called coumarins, which fluoresce a blue color under UV light and can help differentiate species, subspecies, and hybrids. We tested 16 different sagebrush taxa (including species and subspecies) from herbarium specimens and found 3 taxa (low sagebrush, Artemisia arbuscula; Wyoming sagebrush, A. tridentata wyomingensis; and basin sagebrush, A. t. tridentata) that were often misidentified. We show that the UV light test can greatly improve identification of these species. Moreover, given that the UV+ chemicals that discriminate taxa are also considered an indirect biomarker of sagebrush palatability for some herbivores, the UV light test can be used to predict forage quality for threatened species like sage-grouse (Centrocercus spp.) and pygmy rabbits (Brachylagus idahoensis). Collecting voucher specimens of sagebrush at wildlife study sites and comparing their UV intensity to historical herbarium specimens could help identify both current and changing availability of palatable sagebrush for wildlife. We found that even herbarium specimens >80 years old still fluoresce under UV light.</description>
  </descriptions>
  <geoLocations>
    <geoLocation>
      <geoLocationPlace>Intermountain West, USA</geoLocationPlace>
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    <fundingReference>
      <funderName>National Science Foundation</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">https://doi.org/10.13039/100000001</funderIdentifier>
      <awardNumber awardURI="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1757324">OIA-1757324</awardNumber>
      <awardTitle>RII Track-1: Linking Genome to Phenome to Predict Adaptive Responses of Organisms to Changing Landscapes</awardTitle>
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    <fundingReference>
      <funderName>National Science Foundation</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">https://doi.org/10.13039/100000001</funderIdentifier>
      <awardNumber awardURI="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1826801&HistoricalAwards=false">OIA-1826801</awardNumber>
      <awardTitle>RII Track-2 FEC: Genomics Underlying Toxin Tolerance (GUTT): Identifying Molecular Innovations that Predict Phenotypes of Toxin Tolerance in Wild Vertebrate Herbivores</awardTitle>
    </fundingReference>
    <fundingReference>
      <funderName>U.S. Bureau of Land Management</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">https://doi.org/10.13039/100007149</funderIdentifier>
      <awardNumber>L16AC00137</awardNumber>
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      <funderName>U.S. Bureau of Land Management</funderName>
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