[Vertical variation and model construction of area and dry mass for a single leaf from six broadleaved trees in mixed broadleaved-Korean pine forests.]
Identifieur interne : 000624 ( Main/Exploration ); précédent : 000623; suivant : 000625[Vertical variation and model construction of area and dry mass for a single leaf from six broadleaved trees in mixed broadleaved-Korean pine forests.]
Auteurs : Meng Ji [République populaire de Chine] ; Yan Jun Wang [République populaire de Chine] ; Guang Ze Jin [République populaire de Chine] ; Zhi Li Liu [République populaire de Chine]Source :
- Ying yong sheng tai xue bao = The journal of applied ecology [ 1001-9332 ] ; 2019.
Descripteurs français
- KwdFr :
- MESH :
- méthodes : Surveillance de l'environnement.
- Arbres, Chine, Feuilles de plante, Forêts, Pinus.
- Wicri :
- geographic : République populaire de Chine.
English descriptors
- KwdEn :
- MESH :
- geographic : China.
- methods : Environmental Monitoring.
- Forests, Pinus, Plant Leaves, Trees.
Abstract
Rapidly and accurately predicting leaf area (LA) and leaf dry mass (LDM) are essential for exploring the response of plant traits to climate change. Empirical models suitable for predicting LA and LDM of a single leaf for various broadleaved tree species at the regional scale have not been proposed. We selected six broadleaved tree species in four mixed broadleaved-Korean pine (Pinus koraiensis) forests in northeastern China, including Betula platyphylla, Tilia amurensis, Populus davidiana, Betula costata, Fraxinus mandshurica and Ulmus laciniata, and measured leaf length, leaf width, leaf thickness, LA and LDM at different canopy layers (top, middle, and low). Using the median of leaf length and width ratio as the classification criterion, the six species were sorted into two groups. We tested whether different canopy layers for each group of broadleaved tree species had significant impacts on the empirical model for predicting LA and LDM. We constructed empirical models suitable for predicting LA and LDM of a single leaf at different canopy layers at the regional scale, and verified their forecast accuracy, and further evaluated their applicability for predicting LA and LDM of same broadleaved tree species in other regions. These results showed that the LA of a single leaf increased significantly with the decreases of canopy height for the six tree species, while the LDM of some broadleaved tree species showed a downward trend. The canopy height had significant impacts on constructing the empirical model for LA and LDM. The average forecast accuracy of empirical model was 95% and 83% for LA and LDM of a single leaf across canopy layers for two groups of broadleaved tree species, respectively. The average forecast accuracy was 94% and 80% for predicting LA and LDM of corresponding broadleaved tree species in other regions, respectively, indicating that the empirical models constructed in this study had a universal applicability in Northeast China.
DOI: 10.13287/j.1001-9332.201905.022
PubMed: 31107024
Affiliations:
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broadleaved trees in mixed broadleaved-Korean pine forests.]</title><author><name sortKey="Ji, Meng" sort="Ji, Meng" uniqKey="Ji M" first="Meng" last="Ji">Meng Ji</name><affiliation wicri:level="1"><nlm:affiliation>Center for Ecological Research, Northeast Forestry University, Harbin 150040, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Center for Ecological Research, Northeast Forestry University, Harbin 150040</wicri:regionArea><wicri:noRegion>Harbin 150040</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Yan Jun" sort="Wang, Yan Jun" uniqKey="Wang Y" first="Yan Jun" last="Wang">Yan Jun Wang</name><affiliation wicri:level="1"><nlm:affiliation>Center for Ecological Research, Northeast Forestry University, Harbin 150040, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Center for Ecological Research, Northeast Forestry University, Harbin 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University, Harbin 150040</wicri:regionArea><wicri:noRegion>Harbin 150040</wicri:noRegion></affiliation></author></analytic><series><title level="j">Ying yong sheng tai xue bao = The journal of applied ecology</title><idno type="ISSN">1001-9332</idno><imprint><date when="2019" type="published">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>China (MeSH)</term><term>Environmental Monitoring (methods)</term><term>Forests (MeSH)</term><term>Pinus (MeSH)</term><term>Plant Leaves (MeSH)</term><term>Trees (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Arbres (MeSH)</term><term>Chine (MeSH)</term><term>Feuilles de plante (MeSH)</term><term>Forêts (MeSH)</term><term>Pinus (MeSH)</term><term>Surveillance de l'environnement (méthodes)</term></keywords><keywords scheme="MESH" type="geographic" xml:lang="en"><term>China</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Environmental Monitoring</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Surveillance de l'environnement</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Forests</term><term>Pinus</term><term>Plant Leaves</term><term>Trees</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Arbres</term><term>Chine</term><term>Feuilles de plante</term><term>Forêts</term><term>Pinus</term></keywords><keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>République populaire de Chine</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Rapidly and accurately predicting leaf area (LA) and leaf dry mass (LDM) are essential for exploring the response of plant traits to climate change. Empirical models suitable for predicting LA and LDM of a single leaf for various broadleaved tree species at the regional scale have not been proposed. We selected six broadleaved tree species in four mixed broadleaved-Korean pine (Pinus koraiensis) forests in northeastern China, including Betula platyphylla, Tilia amurensis, Populus davidiana, Betula costata, Fraxinus mandshurica and Ulmus laciniata, and measured leaf length, leaf width, leaf thickness, LA and LDM at different canopy layers (top, middle, and low). Using the median of leaf length and width ratio as the classification criterion, the six species were sorted into two groups. We tested whether different canopy layers for each group of broadleaved tree species had significant impacts on the empirical model for predicting LA and LDM. We constructed empirical models suitable for predicting LA and LDM of a single leaf at different canopy layers at the regional scale, and verified their forecast accuracy, and further evaluated their applicability for predicting LA and LDM of same broadleaved tree species in other regions. These results showed that the LA of a single leaf increased significantly with the decreases of canopy height for the six tree species, while the LDM of some broadleaved tree species showed a downward trend. The canopy height had significant impacts on constructing the empirical model for LA and LDM. The average forecast accuracy of empirical model was 95% and 83% for LA and LDM of a single leaf across canopy layers for two groups of broadleaved tree species, respectively. The average forecast accuracy was 94% and 80% for predicting LA and LDM of corresponding broadleaved tree species in other regions, respectively, indicating that the empirical models constructed in this study had a universal applicability in Northeast China.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">31107024</PMID><DateCompleted><Year>2019</Year><Month>07</Month><Day>24</Day></DateCompleted><DateRevised><Year>2019</Year><Month>07</Month><Day>24</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">1001-9332</ISSN><JournalIssue CitedMedium="Print"><Volume>30</Volume><Issue>5</Issue><PubDate><Year>2019</Year><Month>May</Month></PubDate></JournalIssue><Title>Ying yong sheng tai xue bao = The journal of applied ecology</Title><ISOAbbreviation>Ying Yong Sheng Tai Xue Bao</ISOAbbreviation></Journal><ArticleTitle>[Vertical variation and model construction of area and dry mass for a single leaf from six broadleaved trees in mixed broadleaved-Korean pine forests.]</ArticleTitle><Pagination><MedlinePgn>1667-1678</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.13287/j.1001-9332.201905.022</ELocationID><Abstract><AbstractText>Rapidly and accurately predicting leaf area (LA) and leaf dry mass (LDM) are essential for exploring the response of plant traits to climate change. Empirical models suitable for predicting LA and LDM of a single leaf for various broadleaved tree species at the regional scale have not been proposed. We selected six broadleaved tree species in four mixed broadleaved-Korean pine (Pinus koraiensis) forests in northeastern China, including Betula platyphylla, Tilia amurensis, Populus davidiana, Betula costata, Fraxinus mandshurica and Ulmus laciniata, and measured leaf length, leaf width, leaf thickness, LA and LDM at different canopy layers (top, middle, and low). Using the median of leaf length and width ratio as the classification criterion, the six species were sorted into two groups. We tested whether different canopy layers for each group of broadleaved tree species had significant impacts on the empirical model for predicting LA and LDM. We constructed empirical models suitable for predicting LA and LDM of a single leaf at different canopy layers at the regional scale, and verified their forecast accuracy, and further evaluated their applicability for predicting LA and LDM of same broadleaved tree species in other regions. These results showed that the LA of a single leaf increased significantly with the decreases of canopy height for the six tree species, while the LDM of some broadleaved tree species showed a downward trend. The canopy height had significant impacts on constructing the empirical model for LA and LDM. The average forecast accuracy of empirical model was 95% and 83% for LA and LDM of a single leaf across canopy layers for two groups of broadleaved tree species, respectively. The average forecast accuracy was 94% and 80% for predicting LA and LDM of corresponding broadleaved tree species in other regions, respectively, indicating that the empirical models constructed in this study had a universal applicability in Northeast China.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Ji</LastName><ForeName>Meng</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Center for Ecological Research, Northeast Forestry University, Harbin 150040, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Yan Jun</ForeName><Initials>YJ</Initials><AffiliationInfo><Affiliation>Center for Ecological Research, Northeast Forestry University, Harbin 150040, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jin</LastName><ForeName>Guang Ze</ForeName><Initials>GZ</Initials><AffiliationInfo><Affiliation>Center for Ecological Research, Northeast Forestry University, Harbin 150040, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Zhi Li</ForeName><Initials>ZL</Initials><AffiliationInfo><Affiliation>Center for Ecological Research, Northeast Forestry University, Harbin 150040, China.</Affiliation></AffiliationInfo></Author></AuthorList><Language>chi</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><VernacularTitle>阔叶红松林6种阔叶树单个叶片叶面积和叶干质量的垂直变异及模型构建.</VernacularTitle></Article><MedlineJournalInfo><Country>China</Country><MedlineTA>Ying Yong Sheng Tai Xue Bao</MedlineTA><NlmUniqueID>9425159</NlmUniqueID><ISSNLinking>1001-9332</ISSNLinking></MedlineJournalInfo><MeshHeadingList><MeshHeading><DescriptorName UI="D002681" MajorTopicYN="N" Type="Geographic">China</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004784" MajorTopicYN="N">Environmental Monitoring</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D065928" MajorTopicYN="Y">Forests</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D028223" MajorTopicYN="Y">Pinus</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018515" MajorTopicYN="N">Plant Leaves</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014197" MajorTopicYN="Y">Trees</DescriptorName></MeshHeading></MeshHeadingList><OtherAbstract Type="Publisher" Language="chi"><AbstractText>快捷、准确地测定植物叶片尺度上的叶面积(LA)和叶干质量(LDM)对于探讨植物性状对气候变化的响应机制至关重要,但适于测定区域尺度上不同阔叶植物单个叶片LA和LDM的经验模型尚未提出.本研究以中国东北4个分布区阔叶红松林内的白桦、紫椴、山杨、枫桦、水曲柳和裂叶榆6种阔叶树种为研究对象,分别测定其不同冠层高度(上层、中层和下层)叶片的叶长、叶宽、叶厚、LA及LDM.以叶长与叶宽之比(叶长宽比)的中位数为标准将6种阔叶树分为两组,检验每组树种不同冠层高度对构建预测LA和LDM的经验模型是否存在显著影响;构建适于预测区域尺度上不同冠层单个叶片LA和LDM的经验模型,验证其预测精度;并进一步评估构建的经验模型预测其他区域相同阔叶树种LA和LDM的适用性.结果表明: 整体上6种阔叶树单个叶片的LA随冠层高度的降低呈显著增大趋势,而部分树种的LDM呈下降趋势;冠层高度对构建预测LA和LDM的经验模型具有显著影响;构建的经验模型预测两组阔叶树种不同冠层单个叶片LA和LDM的平均精度分别为95%和83%,且基于这些模型预测其他区域相应树种LA和LDM的平均精度分别为94%和80%,表明本研究构建的经验模型在我国东北区域具有普遍适用性.</AbstractText></OtherAbstract><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">broadleaf plant</Keyword><Keyword MajorTopicYN="N">canopy</Keyword><Keyword MajorTopicYN="N">empirical model</Keyword><Keyword MajorTopicYN="N">leaf area</Keyword><Keyword MajorTopicYN="N">leaf dry mass</Keyword><Keyword MajorTopicYN="N">leaf length and width ratio</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2019</Year><Month>5</Month><Day>21</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2019</Year><Month>5</Month><Day>21</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2019</Year><Month>7</Month><Day>25</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">31107024</ArticleId><ArticleId IdType="doi">10.13287/j.1001-9332.201905.022</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Ji, Meng" sort="Ji, Meng" uniqKey="Ji M" first="Meng" last="Ji">Meng Ji</name></noRegion><name sortKey="Jin, Guang Ze" sort="Jin, Guang Ze" uniqKey="Jin G" first="Guang Ze" last="Jin">Guang Ze Jin</name><name sortKey="Liu, Zhi Li" sort="Liu, Zhi Li" uniqKey="Liu Z" first="Zhi Li" last="Liu">Zhi Li Liu</name><name sortKey="Wang, Yan Jun" sort="Wang, Yan Jun" uniqKey="Wang Y" first="Yan Jun" last="Wang">Yan Jun Wang</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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