Development of a spatially-distributed hydroecological model to simulate cottonwood seedling recruitment along rivers.
Identifieur interne : 002292 ( Main/Exploration ); précédent : 002291; suivant : 002293Development of a spatially-distributed hydroecological model to simulate cottonwood seedling recruitment along rivers.
Auteurs : Rohan Benjankar [États-Unis] ; Michael Burke [États-Unis] ; Elowyn Yager [États-Unis] ; Daniele Tonina [États-Unis] ; Gregory Egger [Autriche] ; Stewart B. Rood [Canada] ; Norm Merz [États-Unis]Source :
- Journal of environmental management [ 1095-8630 ] ; 2014.
Descripteurs français
- KwdFr :
- Dispersion des graines (MeSH), Dynamique des populations (MeSH), Idaho (MeSH), Inondations (MeSH), Logique floue (MeSH), Modèles biologiques (MeSH), Mouvements de l'eau (MeSH), Plant (croissance et développement), Plant (physiologie), Populus (croissance et développement), Populus (physiologie), Rivières (MeSH), Saisons (MeSH).
- MESH :
- croissance et développement : Plant, Populus.
- physiologie : Plant, Populus.
- Dispersion des graines, Dynamique des populations, Idaho, Inondations, Logique floue, Modèles biologiques, Mouvements de l'eau, Rivières, Saisons.
English descriptors
- KwdEn :
- MESH :
- growth & development : Populus, Seedlings.
- physiology : Populus, Seedlings.
- Floods, Fuzzy Logic, Idaho, Models, Biological, Population Dynamics, Rivers, Seasons, Seed Dispersal, Water Movements.
Abstract
Dam operations have altered flood and flow patterns and prevented successful cottonwood seedling recruitment along many rivers. To guide reservoir flow releases to meet cottonwood recruitment needs, we developed a spatially-distributed, GIS-based model that analyzes the hydrophysical requirements for cottonwood recruitment. These requirements are indicated by five physical parameters: (1) annual peak flow timing relative to the interval of seed dispersal, (2) shear stress, which characterizes disturbance, (3) local stage recession after seedling recruitment, (4) recruitment elevation above base flow stage, and (5) duration of winter flooding, which may contribute to seedling mortality. The model categorizes the potential for cottonwood recruitment in four classes and attributes a suitability value at each individual spatial location. The model accuracy was estimated with an error matrix analysis by comparing simulated and field-observed recruitment success. The overall accuracies of this Spatially-Distributed Cottonwood Recruitment model were 47% for a braided reach and 68% for a meander reach along the Kootenai River in Idaho, USA. Model accuracies increased to 64% and 72%, respectively, when fewer favorability classes were considered. The model predicted areas of similarly favorable recruitment potential for 1997 and 2006, two recent years with successful cottonwood recruitment. This model should provide a useful tool to quantify impacts of human activities and climatic variability on cottonwood recruitment, and to prescribe instream flow regimes for the conservation and restoration of riparian woodlands.
DOI: 10.1016/j.jenvman.2014.06.027
PubMed: 25086325
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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Front Street, Boise, ID 83702, USA. Electronic address: rohanb@uidaho.edu.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Ecohydraulics Research, University of Idaho, 322 E. 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To guide reservoir flow releases to meet cottonwood recruitment needs, we developed a spatially-distributed, GIS-based model that analyzes the hydrophysical requirements for cottonwood recruitment. These requirements are indicated by five physical parameters: (1) annual peak flow timing relative to the interval of seed dispersal, (2) shear stress, which characterizes disturbance, (3) local stage recession after seedling recruitment, (4) recruitment elevation above base flow stage, and (5) duration of winter flooding, which may contribute to seedling mortality. The model categorizes the potential for cottonwood recruitment in four classes and attributes a suitability value at each individual spatial location. The model accuracy was estimated with an error matrix analysis by comparing simulated and field-observed recruitment success. The overall accuracies of this Spatially-Distributed Cottonwood Recruitment model were 47% for a braided reach and 68% for a meander reach along the Kootenai River in Idaho, USA. Model accuracies increased to 64% and 72%, respectively, when fewer favorability classes were considered. The model predicted areas of similarly favorable recruitment potential for 1997 and 2006, two recent years with successful cottonwood recruitment. This model should provide a useful tool to quantify impacts of human activities and climatic variability on cottonwood recruitment, and to prescribe instream flow regimes for the conservation and restoration of riparian woodlands. </div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">25086325</PMID><DateCompleted><Year>2015</Year><Month>07</Month><Day>09</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1095-8630</ISSN><JournalIssue CitedMedium="Internet"><Volume>145</Volume><PubDate><Year>2014</Year><Month>Dec</Month><Day>01</Day></PubDate></JournalIssue><Title>Journal of environmental management</Title><ISOAbbreviation>J Environ Manage</ISOAbbreviation></Journal><ArticleTitle>Development of a spatially-distributed hydroecological model to simulate cottonwood seedling recruitment along rivers.</ArticleTitle><Pagination><MedlinePgn>277-88</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.jenvman.2014.06.027</ELocationID><ELocationID EIdType="pii" ValidYN="Y">S0301-4797(14)00328-4</ELocationID><Abstract><AbstractText>Dam operations have altered flood and flow patterns and prevented successful cottonwood seedling recruitment along many rivers. To guide reservoir flow releases to meet cottonwood recruitment needs, we developed a spatially-distributed, GIS-based model that analyzes the hydrophysical requirements for cottonwood recruitment. These requirements are indicated by five physical parameters: (1) annual peak flow timing relative to the interval of seed dispersal, (2) shear stress, which characterizes disturbance, (3) local stage recession after seedling recruitment, (4) recruitment elevation above base flow stage, and (5) duration of winter flooding, which may contribute to seedling mortality. The model categorizes the potential for cottonwood recruitment in four classes and attributes a suitability value at each individual spatial location. The model accuracy was estimated with an error matrix analysis by comparing simulated and field-observed recruitment success. The overall accuracies of this Spatially-Distributed Cottonwood Recruitment model were 47% for a braided reach and 68% for a meander reach along the Kootenai River in Idaho, USA. Model accuracies increased to 64% and 72%, respectively, when fewer favorability classes were considered. The model predicted areas of similarly favorable recruitment potential for 1997 and 2006, two recent years with successful cottonwood recruitment. This model should provide a useful tool to quantify impacts of human activities and climatic variability on cottonwood recruitment, and to prescribe instream flow regimes for the conservation and restoration of riparian woodlands. </AbstractText><CopyrightInformation>Copyright © 2014 Elsevier Ltd. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Benjankar</LastName><ForeName>Rohan</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Center for Ecohydraulics Research, University of Idaho, 322 E. Front Street, Boise, ID 83702, USA. Electronic address: rohanb@uidaho.edu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Burke</LastName><ForeName>Michael</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Inter-Fluve, Hood River, OR 97031, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yager</LastName><ForeName>Elowyn</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>Center for Ecohydraulics Research, University of Idaho, 322 E. Front Street, Boise, ID 83702, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tonina</LastName><ForeName>Daniele</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>Center for Ecohydraulics Research, University of Idaho, 322 E. Front Street, Boise, ID 83702, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Egger</LastName><ForeName>Gregory</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>Environmental Consulting Ltd, Bahnhofstrasse 39, 9020 Klagenfurt, Austria.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Rood</LastName><ForeName>Stewart B</ForeName><Initials>SB</Initials><AffiliationInfo><Affiliation>Department of Biological Sciences, University of Lethbridge, AB T1K 3M4, Canada.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Merz</LastName><ForeName>Norm</ForeName><Initials>N</Initials><AffiliationInfo><Affiliation>Kootenai Tribe of Idaho, Bonners Ferry, ID 83805, USA.</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></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2014</Year><Month>08</Month><Day>02</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>J Environ Manage</MedlineTA><NlmUniqueID>0401664</NlmUniqueID><ISSNLinking>0301-4797</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D055868" MajorTopicYN="Y">Floods</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017143" MajorTopicYN="N">Fuzzy Logic</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007061" MajorTopicYN="N">Idaho</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008954" MajorTopicYN="Y">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011157" MajorTopicYN="N">Population Dynamics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName><QualifierName UI="Q000254" MajorTopicYN="N">growth & development</QualifierName><QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D045483" MajorTopicYN="Y">Rivers</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012621" MajorTopicYN="N">Seasons</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058614" MajorTopicYN="Y">Seed Dispersal</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D036226" MajorTopicYN="N">Seedlings</DescriptorName><QualifierName UI="Q000254" MajorTopicYN="N">growth & development</QualifierName><QualifierName UI="Q000502" MajorTopicYN="N">physiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D014872" MajorTopicYN="Y">Water Movements</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Cottonwood</Keyword><Keyword MajorTopicYN="N">Hydrodynamic model</Keyword><Keyword MajorTopicYN="N">Hydroecological model</Keyword><Keyword MajorTopicYN="N">Recruitment</Keyword><Keyword MajorTopicYN="N">Regulated river</Keyword><Keyword MajorTopicYN="N">Restoration</Keyword><Keyword MajorTopicYN="N">Riparian</Keyword><Keyword MajorTopicYN="N">River management</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2013</Year><Month>09</Month><Day>17</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2014</Year><Month>06</Month><Day>07</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2014</Year><Month>06</Month><Day>27</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2014</Year><Month>8</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2014</Year><Month>8</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2015</Year><Month>7</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">25086325</ArticleId><ArticleId IdType="pii">S0301-4797(14)00328-4</ArticleId><ArticleId IdType="doi">10.1016/j.jenvman.2014.06.027</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Autriche</li><li>Canada</li><li>États-Unis</li></country><region><li>Idaho</li><li>Oregon</li></region></list><tree><country name="États-Unis"><region name="Idaho"><name sortKey="Benjankar, Rohan" sort="Benjankar, Rohan" uniqKey="Benjankar R" first="Rohan" last="Benjankar">Rohan Benjankar</name></region><name sortKey="Burke, Michael" sort="Burke, Michael" uniqKey="Burke M" first="Michael" last="Burke">Michael Burke</name><name sortKey="Merz, Norm" sort="Merz, Norm" uniqKey="Merz N" first="Norm" last="Merz">Norm Merz</name><name sortKey="Tonina, Daniele" sort="Tonina, Daniele" uniqKey="Tonina D" first="Daniele" last="Tonina">Daniele Tonina</name><name sortKey="Yager, Elowyn" sort="Yager, Elowyn" uniqKey="Yager E" first="Elowyn" last="Yager">Elowyn Yager</name></country><country name="Autriche"><noRegion><name sortKey="Egger, Gregory" sort="Egger, Gregory" uniqKey="Egger G" first="Gregory" last="Egger">Gregory Egger</name></noRegion></country><country name="Canada"><noRegion><name sortKey="Rood, Stewart B" sort="Rood, Stewart B" uniqKey="Rood S" first="Stewart B" last="Rood">Stewart B. 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