Modelling Hurricane Exposure and Wind Speed on a Mesoclimate Scale: A Case Study from Cusuco NP, Honduras
Identifieur interne : 000223 ( Pmc/Curation ); précédent : 000222; suivant : 000224Modelling Hurricane Exposure and Wind Speed on a Mesoclimate Scale: A Case Study from Cusuco NP, Honduras
Auteurs : Sven P. Batke [Irlande (pays), Royaume-Uni] ; Merlijn Jocque [Belgique, Royaume-Uni, États-Unis] ; Daniel L. Kelly [Irlande (pays), Royaume-Uni]Source :
- PLoS ONE [ 1932-6203 ] ; 2014.
Abstract
High energy weather events are often expected to play a substantial role in biotic community dynamics and large scale diversity patterns but their contribution is hard to prove. Currently, observations are limited to the documentation of accidental records after the passing of such events. A more comprehensive approach is synthesising weather events in a location over a long time period, ideally at a high spatial resolution and on a large geographic scale. We provide a detailed overview on how to generate hurricane exposure data at a meso-climate level for a specific region. As a case study we modelled landscape hurricane exposure in Cusuco National Park (CNP), Honduras with a resolution of 50 m×50 m patches. We calculated actual hurricane exposure vulnerability site scores (EVVS) through the combination of a wind pressure model, an exposure model that can incorporate simple wind dynamics within a 3-dimensional landscape and the integration of historical hurricanes data. The EVSS was calculated as a weighted function of sites exposure, hurricane frequency and maximum wind velocity. Eleven hurricanes were found to have affected CNP between 1995 and 2010. The highest EVSS’s were predicted to be on South and South-East facing sites of the park. Ground validation demonstrated that the South-solution (i.e. the South wind inflow direction) explained most of the observed tree damage (90% of the observed tree damage in the field). Incorporating historical data to the model to calculate actual hurricane exposure values, instead of potential exposure values, increased the model fit by 50%.
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DOI: 10.1371/journal.pone.0091306
PubMed: 24614168
PubMed Central: 3948866
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Batke</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Department of Botany and Trinity Centre for Biodiversity Research, Trinity College Dublin, Dublin, Ireland</addr-line></nlm:aff><country xml:lang="fr">Irlande (pays)</country><wicri:regionArea>Department of Botany and Trinity Centre for Biodiversity Research, Trinity College Dublin, Dublin</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff3"><addr-line>Operation Wallacea, Old Bolingbroke, United Kingdom</addr-line></nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Operation Wallacea, Old Bolingbroke</wicri:regionArea></affiliation></author><author><name sortKey="Jocque, Merlijn" sort="Jocque, Merlijn" uniqKey="Jocque M" first="Merlijn" last="Jocque">Merlijn Jocque</name><affiliation wicri:level="1"><nlm:aff id="aff2"><addr-line>Koninklijk Belgisch Instituut voor Natuurwetenschappen, Brussels, Belgium</addr-line></nlm:aff><country xml:lang="fr">Belgique</country><wicri:regionArea>Koninklijk Belgisch Instituut voor Natuurwetenschappen, Brussels</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff3"><addr-line>Operation Wallacea, Old Bolingbroke, United Kingdom</addr-line></nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Operation Wallacea, Old Bolingbroke</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff4"><addr-line>Department of Biological Sciences, Rutgers University, Newark, New Jersey, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biological Sciences, Rutgers University, Newark, New Jersey</wicri:regionArea></affiliation></author><author><name sortKey="Kelly, Daniel L" sort="Kelly, Daniel L" uniqKey="Kelly D" first="Daniel L." last="Kelly">Daniel L. 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Batke</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Department of Botany and Trinity Centre for Biodiversity Research, Trinity College Dublin, Dublin, Ireland</addr-line></nlm:aff><country xml:lang="fr">Irlande (pays)</country><wicri:regionArea>Department of Botany and Trinity Centre for Biodiversity Research, Trinity College Dublin, Dublin</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff3"><addr-line>Operation Wallacea, Old Bolingbroke, United Kingdom</addr-line></nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Operation Wallacea, Old Bolingbroke</wicri:regionArea></affiliation></author><author><name sortKey="Jocque, Merlijn" sort="Jocque, Merlijn" uniqKey="Jocque M" first="Merlijn" last="Jocque">Merlijn Jocque</name><affiliation wicri:level="1"><nlm:aff id="aff2"><addr-line>Koninklijk Belgisch Instituut voor Natuurwetenschappen, Brussels, Belgium</addr-line></nlm:aff><country xml:lang="fr">Belgique</country><wicri:regionArea>Koninklijk Belgisch Instituut voor Natuurwetenschappen, Brussels</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff3"><addr-line>Operation Wallacea, Old Bolingbroke, United Kingdom</addr-line></nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Operation Wallacea, Old Bolingbroke</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff4"><addr-line>Department of Biological Sciences, Rutgers University, Newark, New Jersey, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biological Sciences, Rutgers University, Newark, New Jersey</wicri:regionArea></affiliation></author><author><name sortKey="Kelly, Daniel L" sort="Kelly, Daniel L" uniqKey="Kelly D" first="Daniel L." last="Kelly">Daniel L. Kelly</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Department of Botany and Trinity Centre for Biodiversity Research, Trinity College Dublin, Dublin, Ireland</addr-line></nlm:aff><country xml:lang="fr">Irlande (pays)</country><wicri:regionArea>Department of Botany and Trinity Centre for Biodiversity Research, Trinity College Dublin, Dublin</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff3"><addr-line>Operation Wallacea, Old Bolingbroke, United Kingdom</addr-line></nlm:aff><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Operation Wallacea, Old Bolingbroke</wicri:regionArea></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>High energy weather events are often expected to play a substantial role in biotic community dynamics and large scale diversity patterns but their contribution is hard to prove. Currently, observations are limited to the documentation of accidental records after the passing of such events. A more comprehensive approach is synthesising weather events in a location over a long time period, ideally at a high spatial resolution and on a large geographic scale. We provide a detailed overview on how to generate hurricane exposure data at a meso-climate level for a specific region. As a case study we modelled landscape hurricane exposure in Cusuco National Park (CNP), Honduras with a resolution of 50 m×50 m patches. We calculated actual hurricane exposure vulnerability site scores (EVVS) through the combination of a wind pressure model, an exposure model that can incorporate simple wind dynamics within a 3-dimensional landscape and the integration of historical hurricanes data. The EVSS was calculated as a weighted function of sites exposure, hurricane frequency and maximum wind velocity. Eleven hurricanes were found to have affected CNP between 1995 and 2010. The highest EVSS’s were predicted to be on South and South-East facing sites of the park. Ground validation demonstrated that the South-solution (i.e. the South wind inflow direction) explained most of the observed tree damage (90% of the observed tree damage in the field). 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<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id><journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id><journal-id journal-id-type="publisher-id">plos</journal-id><journal-id journal-id-type="pmc">plosone</journal-id><journal-title-group><journal-title>PLoS ONE</journal-title></journal-title-group><issn pub-type="epub">1932-6203</issn><publisher><publisher-name>Public Library of Science</publisher-name><publisher-loc>San Francisco, USA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">24614168</article-id><article-id pub-id-type="pmc">3948866</article-id><article-id pub-id-type="publisher-id">PONE-D-13-11889</article-id><article-id pub-id-type="doi">10.1371/journal.pone.0091306</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biology</subject><subj-group><subject>Ecology</subject><subj-group><subject>Ecosystems</subject><subj-group><subject>Ecosystem Modeling</subject></subj-group></subj-group><subj-group><subject>Spatial and Landscape Ecology</subject><subject>Terrestrial Ecology</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Computer Science</subject><subj-group><subject>Computer Modeling</subject></subj-group><subj-group><subject>Geoinformatics</subject><subj-group><subject>Environmental Systems Modeling</subject></subj-group></subj-group></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Earth Sciences</subject><subj-group><subject>Atmospheric Science</subject><subj-group><subject>Atmospheric Dynamics</subject><subj-group><subject>Atmospheric Dispersion Modeling</subject><subject>Atmospheric Storms</subject></subj-group></subj-group><subj-group><subject>Climatology</subject><subj-group><subject>Climate Modeling</subject></subj-group></subj-group></subj-group><subj-group><subject>Geography</subject><subj-group><subject>Geoinformatics</subject><subj-group><subject>Environmental Systems Modeling</subject></subj-group></subj-group></subj-group></subj-group></article-categories><title-group><article-title>Modelling Hurricane Exposure and Wind Speed on a Mesoclimate Scale: A Case Study from Cusuco NP, Honduras</article-title><alt-title alt-title-type="running-head">Hurricane Exposure Vulnerability</alt-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Batke</surname><given-names>Sven P.</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author"><name><surname>Jocque</surname><given-names>Merlijn</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref><xref ref-type="aff" rid="aff3"><sup>3</sup></xref><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author"><name><surname>Kelly</surname><given-names>Daniel L.</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib></contrib-group><aff id="aff1"><label>1</label><addr-line>Department of Botany and Trinity Centre for Biodiversity Research, Trinity College Dublin, Dublin, Ireland</addr-line></aff><aff id="aff2"><label>2</label><addr-line>Koninklijk Belgisch Instituut voor Natuurwetenschappen, Brussels, Belgium</addr-line></aff><aff id="aff3"><label>3</label><addr-line>Operation Wallacea, Old Bolingbroke, United Kingdom</addr-line></aff><aff id="aff4"><label>4</label><addr-line>Department of Biological Sciences, Rutgers University, Newark, New Jersey, United States of America</addr-line></aff><contrib-group><contrib contrib-type="editor"><name><surname>Añel</surname><given-names>Juan A.</given-names></name><role>Editor</role><xref ref-type="aff" rid="edit1"></xref></contrib></contrib-group><aff id="edit1"><addr-line>University of Oxford, United Kingdom</addr-line></aff><author-notes><corresp id="cor1">* E-mail: <email>batkesp@tcd.ie</email></corresp><fn fn-type="conflict"><p><bold>Competing Interests: </bold>The authors have declared that no competing interests exist.</p></fn><fn fn-type="con"><p>Conceived and designed the experiments: SB DK. Performed the experiments: SB. Analyzed the data: SB. Contributed reagents/materials/analysis tools: SB MJ DK. Wrote the paper: SB MJ DK.</p></fn></author-notes><pub-date pub-type="collection"><year>2014</year></pub-date><pub-date pub-type="epub"><day>10</day><month>3</month><year>2014</year></pub-date><volume>9</volume><issue>3</issue><elocation-id>e91306</elocation-id><history><date date-type="received"><day>22</day><month>3</month><year>2013</year></date><date date-type="accepted"><day>12</day><month>2</month><year>2014</year></date></history><permissions><copyright-year>2014</copyright-year><copyright-holder>Batke et al</copyright-holder><license><license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p></license></permissions><abstract><p>High energy weather events are often expected to play a substantial role in biotic community dynamics and large scale diversity patterns but their contribution is hard to prove. Currently, observations are limited to the documentation of accidental records after the passing of such events. A more comprehensive approach is synthesising weather events in a location over a long time period, ideally at a high spatial resolution and on a large geographic scale. We provide a detailed overview on how to generate hurricane exposure data at a meso-climate level for a specific region. As a case study we modelled landscape hurricane exposure in Cusuco National Park (CNP), Honduras with a resolution of 50 m×50 m patches. We calculated actual hurricane exposure vulnerability site scores (EVVS) through the combination of a wind pressure model, an exposure model that can incorporate simple wind dynamics within a 3-dimensional landscape and the integration of historical hurricanes data. The EVSS was calculated as a weighted function of sites exposure, hurricane frequency and maximum wind velocity. Eleven hurricanes were found to have affected CNP between 1995 and 2010. The highest EVSS’s were predicted to be on South and South-East facing sites of the park. Ground validation demonstrated that the South-solution (i.e. the South wind inflow direction) explained most of the observed tree damage (90% of the observed tree damage in the field). Incorporating historical data to the model to calculate actual hurricane exposure values, instead of potential exposure values, increased the model fit by 50%.</p></abstract><funding-group><funding-statement>This project was funded by Trinity College Dublin, the Rufford Foundation, Operation Wallacea and the Royal Geographic Society London (in collaboration with Dr. Merlijn Jocque). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement></funding-group><counts><page-count count="11"></page-count></counts></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
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| HfdSelect -Kh $EXPLOR_AREA/Data/Pmc/Curation/biblio.hfd \
| NlmPubMed2Wicri -a CheneBelgiqueV1
| This area was generated with Dilib version V0.6.27. |  |