Direct comparison of four methods to construct xylem vulnerability curves: Differences among techniques are linked to vessel network characteristics.
Identifieur interne : 000A24 ( Main/Exploration ); précédent : 000A23; suivant : 000A25Direct comparison of four methods to construct xylem vulnerability curves: Differences among techniques are linked to vessel network characteristics.
Auteurs : Martin D. Venturas [États-Unis] ; R Brandon Pratt [États-Unis] ; Anna L. Jacobsen [États-Unis] ; Viridiana Castro [États-Unis] ; Jaycie C. Fickle [États-Unis] ; Uwe G. Hacke [Canada]Source :
- Plant, cell & environment [ 1365-3040 ] ; 2019.
Descripteurs français
- KwdFr :
- MESH :
- métabolisme : Eau, Populus.
- méthodes : Microtomographie aux rayons X, Tomodensitométrie.
- physiologie : Populus, Xylème.
- Modèles biologiques, Optique et photonique, Phénomènes biomécaniques.
English descriptors
- KwdEn :
- MESH :
- chemical , metabolism : Water.
- metabolism : Populus.
- methods : Tomography, X-Ray Computed, X-Ray Microtomography.
- physiology : Populus, Xylem.
- Biomechanical Phenomena, Models, Biological, Optics and Photonics.
Abstract
During periods of dehydration, water transport through xylem conduits can become blocked by embolism formation. Xylem embolism compromises water supply to leaves and may lead to losses in productivity or plant death. Vulnerability curves (VCs) characterize plant losses in conductivity as xylem pressures decrease. VCs are widely used to characterize and predict plant water use at different levels of water availability. Several methodologies for constructing VCs exist and sometimes produce different results for the same plant material. We directly compared four VC construction methods on stems of black cottonwood (Populus trichocarpa), a model tree species: dehydration, centrifuge, X-ray-computed microtomography (microCT), and optical. MicroCT VC was the most resistant, dehydration and centrifuge VCs were intermediate, and optical VC was the most vulnerable. Differences among VCs were not associated with how cavitation was induced but were related to how losses in conductivity were evaluated: measured hydraulically (dehydration and centrifuge) versus evaluated from visual information (microCT and optical). Understanding how and why methods differ in estimating vulnerability to xylem embolism is important for advancing knowledge in plant ecophysiology, interpreting literature data, and using accurate VCs in water flux models for predicting plant responses to drought.
DOI: 10.1111/pce.13565
PubMed: 30997689
Affiliations:
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Venturas</name><affiliation wicri:level="2"><nlm:affiliation>School of Biological Sciences, University of Utah, Salt Lake City, 84112, Utah, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>School of Biological Sciences, University of Utah, Salt Lake City, 84112, Utah</wicri:regionArea><placeName><region type="state">Utah</region></placeName></affiliation></author><author><name sortKey="Pratt, R Brandon" sort="Pratt, R Brandon" uniqKey="Pratt R" first="R Brandon" last="Pratt">R Brandon Pratt</name><affiliation wicri:level="2"><nlm:affiliation>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Jacobsen, Anna L" sort="Jacobsen, Anna L" uniqKey="Jacobsen A" first="Anna L" last="Jacobsen">Anna L. Jacobsen</name><affiliation wicri:level="2"><nlm:affiliation>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Castro, Viridiana" sort="Castro, Viridiana" uniqKey="Castro V" first="Viridiana" last="Castro">Viridiana Castro</name><affiliation wicri:level="2"><nlm:affiliation>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Fickle, Jaycie C" sort="Fickle, Jaycie C" uniqKey="Fickle J" first="Jaycie C" last="Fickle">Jaycie C. Fickle</name><affiliation wicri:level="2"><nlm:affiliation>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California</wicri:regionArea><placeName><region type="state">Californie</region></placeName></affiliation></author><author><name sortKey="Hacke, Uwe G" sort="Hacke, Uwe G" uniqKey="Hacke U" first="Uwe G" last="Hacke">Uwe G. Hacke</name><affiliation wicri:level="1"><nlm:affiliation>Department of Renewable Resources, University of Alberta, Edmonton, Alberta, T6G 2E3, Canada.</nlm:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Department of Renewable Resources, University of Alberta, Edmonton, Alberta, T6G 2E3</wicri:regionArea><wicri:noRegion>T6G 2E3</wicri:noRegion></affiliation></author></analytic><series><title level="j">Plant, cell & environment</title><idno type="eISSN">1365-3040</idno><imprint><date when="2019" type="published">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Biomechanical Phenomena (MeSH)</term><term>Models, Biological (MeSH)</term><term>Optics and Photonics (MeSH)</term><term>Populus (metabolism)</term><term>Populus (physiology)</term><term>Tomography, X-Ray Computed (methods)</term><term>Water (metabolism)</term><term>X-Ray Microtomography (methods)</term><term>Xylem (physiology)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Eau (métabolisme)</term><term>Microtomographie aux rayons X (méthodes)</term><term>Modèles biologiques (MeSH)</term><term>Optique et photonique (MeSH)</term><term>Phénomènes biomécaniques (MeSH)</term><term>Populus (métabolisme)</term><term>Populus (physiologie)</term><term>Tomodensitométrie (méthodes)</term><term>Xylème (physiologie)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Water</term></keywords><keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Populus</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Tomography, X-Ray Computed</term><term>X-Ray Microtomography</term></keywords><keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Eau</term><term>Populus</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Microtomographie aux rayons X</term><term>Tomodensitométrie</term></keywords><keywords scheme="MESH" qualifier="physiologie" xml:lang="fr"><term>Populus</term><term>Xylème</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Populus</term><term>Xylem</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Biomechanical Phenomena</term><term>Models, Biological</term><term>Optics and Photonics</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Modèles biologiques</term><term>Optique et photonique</term><term>Phénomènes biomécaniques</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">During periods of dehydration, water transport through xylem conduits can become blocked by embolism formation. Xylem embolism compromises water supply to leaves and may lead to losses in productivity or plant death. Vulnerability curves (VCs) characterize plant losses in conductivity as xylem pressures decrease. VCs are widely used to characterize and predict plant water use at different levels of water availability. Several methodologies for constructing VCs exist and sometimes produce different results for the same plant material. We directly compared four VC construction methods on stems of black cottonwood (Populus trichocarpa), a model tree species: dehydration, centrifuge, X-ray-computed microtomography (microCT), and optical. MicroCT VC was the most resistant, dehydration and centrifuge VCs were intermediate, and optical VC was the most vulnerable. Differences among VCs were not associated with how cavitation was induced but were related to how losses in conductivity were evaluated: measured hydraulically (dehydration and centrifuge) versus evaluated from visual information (microCT and optical). Understanding how and why methods differ in estimating vulnerability to xylem embolism is important for advancing knowledge in plant ecophysiology, interpreting literature data, and using accurate VCs in water flux models for predicting plant responses to drought.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">30997689</PMID><DateCompleted><Year>2020</Year><Month>05</Month><Day>18</Day></DateCompleted><DateRevised><Year>2020</Year><Month>05</Month><Day>18</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1365-3040</ISSN><JournalIssue CitedMedium="Internet"><Volume>42</Volume><Issue>8</Issue><PubDate><Year>2019</Year><Month>08</Month></PubDate></JournalIssue><Title>Plant, cell & environment</Title><ISOAbbreviation>Plant Cell Environ</ISOAbbreviation></Journal><ArticleTitle>Direct comparison of four methods to construct xylem vulnerability curves: Differences among techniques are linked to vessel network characteristics.</ArticleTitle><Pagination><MedlinePgn>2422-2436</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1111/pce.13565</ELocationID><Abstract><AbstractText>During periods of dehydration, water transport through xylem conduits can become blocked by embolism formation. Xylem embolism compromises water supply to leaves and may lead to losses in productivity or plant death. Vulnerability curves (VCs) characterize plant losses in conductivity as xylem pressures decrease. VCs are widely used to characterize and predict plant water use at different levels of water availability. Several methodologies for constructing VCs exist and sometimes produce different results for the same plant material. We directly compared four VC construction methods on stems of black cottonwood (Populus trichocarpa), a model tree species: dehydration, centrifuge, X-ray-computed microtomography (microCT), and optical. MicroCT VC was the most resistant, dehydration and centrifuge VCs were intermediate, and optical VC was the most vulnerable. Differences among VCs were not associated with how cavitation was induced but were related to how losses in conductivity were evaluated: measured hydraulically (dehydration and centrifuge) versus evaluated from visual information (microCT and optical). Understanding how and why methods differ in estimating vulnerability to xylem embolism is important for advancing knowledge in plant ecophysiology, interpreting literature data, and using accurate VCs in water flux models for predicting plant responses to drought.</AbstractText><CopyrightInformation>© 2019 John Wiley & Sons Ltd.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Venturas</LastName><ForeName>Martin D</ForeName><Initials>MD</Initials><Identifier Source="ORCID">0000-0001-5972-9064</Identifier><AffiliationInfo><Affiliation>School of Biological Sciences, University of Utah, Salt Lake City, 84112, Utah, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pratt</LastName><ForeName>R Brandon</ForeName><Initials>RB</Initials><Identifier Source="ORCID">0000-0001-7537-7644</Identifier><AffiliationInfo><Affiliation>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jacobsen</LastName><ForeName>Anna L</ForeName><Initials>AL</Initials><Identifier Source="ORCID">0000-0001-7830-5590</Identifier><AffiliationInfo><Affiliation>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Castro</LastName><ForeName>Viridiana</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Fickle</LastName><ForeName>Jaycie C</ForeName><Initials>JC</Initials><AffiliationInfo><Affiliation>Department of Biology, California State University Bakersfield, Bakersfield, 93311, California, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hacke</LastName><ForeName>Uwe G</ForeName><Initials>UG</Initials><AffiliationInfo><Affiliation>Department of Renewable Resources, University of Alberta, Edmonton, Alberta, T6G 2E3, Canada.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2019</Year><Month>06</Month><Day>12</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Plant Cell Environ</MedlineTA><NlmUniqueID>9309004</NlmUniqueID><ISSNLinking>0140-7791</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>059QF0KO0R</RegistryNumber><NameOfSubstance UI="D014867">Water</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D001696" MajorTopicYN="N">Biomechanical Phenomena</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008954" MajorTopicYN="N">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D055095" MajorTopicYN="N">Optics and Photonics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName><QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName><QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D014057" MajorTopicYN="N">Tomography, X-Ray Computed</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D014867" MajorTopicYN="N">Water</DescriptorName><QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D055114" MajorTopicYN="N">X-Ray Microtomography</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D052584" MajorTopicYN="N">Xylem</DescriptorName><QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">Populus</Keyword><Keyword MajorTopicYN="Y">X-ray microtomography</Keyword><Keyword MajorTopicYN="Y">centrifugation</Keyword><Keyword MajorTopicYN="Y">dehydration</Keyword><Keyword MajorTopicYN="Y">droughts</Keyword><Keyword MajorTopicYN="Y">plant stems</Keyword><Keyword MajorTopicYN="Y">poplar</Keyword><Keyword MajorTopicYN="Y">trees</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year><Month>02</Month><Day>15</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2019</Year><Month>04</Month><Day>12</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2019</Year><Month>04</Month><Day>15</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2019</Year><Month>4</Month><Day>19</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>5</Month><Day>19</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2019</Year><Month>4</Month><Day>19</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">30997689</ArticleId><ArticleId IdType="doi">10.1111/pce.13565</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Canada</li><li>États-Unis</li></country><region><li>Californie</li><li>Utah</li></region></list><tree><country name="États-Unis"><region name="Utah"><name sortKey="Venturas, Martin D" sort="Venturas, Martin D" uniqKey="Venturas M" first="Martin D" last="Venturas">Martin D. Venturas</name></region><name sortKey="Castro, Viridiana" sort="Castro, Viridiana" uniqKey="Castro V" first="Viridiana" last="Castro">Viridiana Castro</name><name sortKey="Fickle, Jaycie C" sort="Fickle, Jaycie C" uniqKey="Fickle J" first="Jaycie C" last="Fickle">Jaycie C. Fickle</name><name sortKey="Jacobsen, Anna L" sort="Jacobsen, Anna L" uniqKey="Jacobsen A" first="Anna L" last="Jacobsen">Anna L. Jacobsen</name><name sortKey="Pratt, R Brandon" sort="Pratt, R Brandon" uniqKey="Pratt R" first="R Brandon" last="Pratt">R Brandon Pratt</name></country><country name="Canada"><noRegion><name sortKey="Hacke, Uwe G" sort="Hacke, Uwe G" uniqKey="Hacke U" first="Uwe G" last="Hacke">Uwe G. Hacke</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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