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Using multiple lines of evidence to assess the risk of ecosystem collapse

Identifieur interne : 002B44 ( Pmc/Curation ); précédent : 002B43; suivant : 002B45

Using multiple lines of evidence to assess the risk of ecosystem collapse

Auteurs : Lucie M. Bland [Australie] ; Tracey J. Regan [Australie] ; Minh Ngoc Dinh [Australie] ; Renata Ferrari [Australie] ; David A. Keith [Australie] ; Rebecca Lester [Australie] ; David Mouillot [France, Australie] ; Nicholas J. Murray [Australie] ; Hoang Anh Nguyen [Australie] ; Emily Nicholson [Australie]

Source :

RBID : PMC:5627190

Abstract

Effective ecosystem risk assessment relies on a conceptual understanding of ecosystem dynamics and the synthesis of multiple lines of evidence. Risk assessment protocols and ecosystem models integrate limited observational data with threat scenarios, making them valuable tools for monitoring ecosystem status and diagnosing key mechanisms of decline to be addressed by management. We applied the IUCN Red List of Ecosystems criteria to quantify the risk of collapse of the Meso-American Reef, a unique ecosystem containing the second longest barrier reef in the world. We collated a wide array of empirical data (field and remotely sensed), and used a stochastic ecosystem model to backcast past ecosystem dynamics, as well as forecast future ecosystem dynamics under 11 scenarios of threat. The ecosystem is at high risk from mass bleaching in the coming decades, with compounding effects of ocean acidification, hurricanes, pollution and fishing. The overall status of the ecosystem is Critically Endangered (plausibly Vulnerable to Critically Endangered), with notable differences among Red List criteria and data types in detecting the most severe symptoms of risk. Our case study provides a template for assessing risks to coral reefs and for further application of ecosystem models in risk assessment.


Url:
DOI: 10.1098/rspb.2017.0660
PubMed: 28931744
PubMed Central: 5627190

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PMC:5627190

Le document en format XML

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<p>Effective ecosystem risk assessment relies on a conceptual understanding of ecosystem dynamics and the synthesis of multiple lines of evidence. Risk assessment protocols and ecosystem models integrate limited observational data with threat scenarios, making them valuable tools for monitoring ecosystem status and diagnosing key mechanisms of decline to be addressed by management. We applied the IUCN Red List of Ecosystems criteria to quantify the risk of collapse of the Meso-American Reef, a unique ecosystem containing the second longest barrier reef in the world. We collated a wide array of empirical data (field and remotely sensed), and used a stochastic ecosystem model to backcast past ecosystem dynamics, as well as forecast future ecosystem dynamics under 11 scenarios of threat. The ecosystem is at high risk from mass bleaching in the coming decades, with compounding effects of ocean acidification, hurricanes, pollution and fishing. The overall status of the ecosystem is Critically Endangered (plausibly Vulnerable to Critically Endangered), with notable differences among Red List criteria and data types in detecting the most severe symptoms of risk. Our case study provides a template for assessing risks to coral reefs and for further application of ecosystem models in risk assessment.</p>
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<pmc-dir>properties open_access</pmc-dir>
<front>
<journal-meta>
<journal-id journal-id-type="nlm-ta">Proc Biol Sci</journal-id>
<journal-id journal-id-type="iso-abbrev">Proc. Biol. Sci</journal-id>
<journal-id journal-id-type="publisher-id">RSPB</journal-id>
<journal-id journal-id-type="hwp">royprsb</journal-id>
<journal-title-group>
<journal-title>Proceedings of the Royal Society B: Biological Sciences</journal-title>
</journal-title-group>
<issn pub-type="ppub">0962-8452</issn>
<issn pub-type="epub">1471-2954</issn>
<publisher>
<publisher-name>The Royal Society</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">28931744</article-id>
<article-id pub-id-type="pmc">5627190</article-id>
<article-id pub-id-type="doi">10.1098/rspb.2017.0660</article-id>
<article-id pub-id-type="publisher-id">rspb20170660</article-id>
<article-categories>
<subj-group subj-group-type="hwp-journal-coll">
<subject>1001</subject>
<subject>60</subject>
<subject>69</subject>
</subj-group>
<subj-group subj-group-type="heading">
<subject>Global Change and Conservation</subject>
</subj-group>
<subj-group subj-group-type="leader">
<subject>Research Article</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Using multiple lines of evidence to assess the risk of ecosystem collapse</article-title>
<alt-title alt-title-type="short">Modelling the risk of ecosystem collapse</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<contrib-id contrib-id-type="orcid" authenticated="false">http://orcid.org/0000-0003-0739-114X</contrib-id>
<name>
<surname>Bland</surname>
<given-names>Lucie M.</given-names>
</name>
<xref ref-type="aff" rid="af1">1</xref>
<xref ref-type="aff" rid="af2">2</xref>
<xref ref-type="corresp" rid="cor1"></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Regan</surname>
<given-names>Tracey J.</given-names>
</name>
<xref ref-type="aff" rid="af3">3</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Dinh</surname>
<given-names>Minh Ngoc</given-names>
</name>
<xref ref-type="aff" rid="af4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ferrari</surname>
<given-names>Renata</given-names>
</name>
<xref ref-type="aff" rid="af5">5</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Keith</surname>
<given-names>David A.</given-names>
</name>
<xref ref-type="aff" rid="af6">6</xref>
<xref ref-type="aff" rid="af7">7</xref>
<xref ref-type="aff" rid="af8">8</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lester</surname>
<given-names>Rebecca</given-names>
</name>
<xref ref-type="aff" rid="af9">9</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Mouillot</surname>
<given-names>David</given-names>
</name>
<xref ref-type="aff" rid="af10">10</xref>
<xref ref-type="aff" rid="af11">11</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Murray</surname>
<given-names>Nicholas J.</given-names>
</name>
<xref ref-type="aff" rid="af6">6</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Nguyen</surname>
<given-names>Hoang Anh</given-names>
</name>
<xref ref-type="aff" rid="af4">4</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Nicholson</surname>
<given-names>Emily</given-names>
</name>
<xref ref-type="aff" rid="af1">1</xref>
</contrib>
</contrib-group>
<aff id="af1">
<label>1</label>
<institution>Deakin University, Australia, School of Life and Environmental Sciences, Centre for Integrative Ecology</institution>
,
<addr-line>Burwood, 3121, Victoria</addr-line>
,
<country>Australia</country>
</aff>
<aff id="af2">
<label>2</label>
<institution>School of BioSciences, The University of Melbourne</institution>
,
<addr-line>Parkville, 3010, Victoria</addr-line>
,
<country>Australia</country>
</aff>
<aff id="af3">
<label>3</label>
<institution>The Arthur Rylah Institute for Environmental Research, the Department of Environment, Land, Water and Planning</institution>
,
<addr-line>123 Brown Street, Heidelberg, 3084, Victoria</addr-line>
,
<country>Australia</country>
</aff>
<aff id="af4">
<label>4</label>
<institution>Research Computing Centre, University of Queensland</institution>
,
<addr-line>St Lucia, 4072, Queensland</addr-line>
,
<country>Australia</country>
</aff>
<aff id="af5">
<label>5</label>
<institution>Coastal and Marine Ecosystems Group, School of Life and Environmental Sciences, The University of Sydney</institution>
,
<addr-line>Sydney, New South Wales</addr-line>
,
<country>Australia</country>
</aff>
<aff id="af6">
<label>6</label>
<institution>Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales</institution>
,
<addr-line>Kensington, 2052, New South Wales</addr-line>
,
<country>Australia</country>
</aff>
<aff id="af7">
<label>7</label>
<institution>New South Wales Office of Environment and Heritage</institution>
,
<addr-line>Hurstville, 2220, New South Wales</addr-line>
,
<country>Australia</country>
</aff>
<aff id="af8">
<label>8</label>
<institution>Long Term Ecological Research Network, Terrestrial Ecosystem Research Network, Australian National University</institution>
,
<addr-line>Canberra, 0200, Australian Capital Territory</addr-line>
,
<country>Australia</country>
</aff>
<aff id="af9">
<label>9</label>
<institution>Deakin University, Australia, Centre for Regional and Rural Futures</institution>
,
<addr-line>Geelong, 3220, Victoria</addr-line>
,
<country>Australia</country>
</aff>
<aff id="af10">
<label>10</label>
<institution>UMR 5119—Écologie des Systèmes marins côtiers, Université Montpellier 2</institution>
,
<addr-line>Montpellier Cedex 5</addr-line>
,
<country>France</country>
</aff>
<aff id="af11">
<label>11</label>
<institution>ARC Centre of Excellence for Coral Reef Studies, James Cook University</institution>
,
<addr-line>Townsville, 4881, Queensland</addr-line>
,
<country>Australia</country>
</aff>
<author-notes>
<corresp id="cor1">e-mail:
<email>l.bland@deakin.edu.au</email>
</corresp>
<fn fn-type="other">
<p>Electronic supplementary material is available online at
<uri xlink:href="https://dx.doi.org/10.6084/m9.figshare.c.3865441">https://dx.doi.org/10.6084/m9.figshare.c.3865441</uri>
.</p>
</fn>
</author-notes>
<pub-date pub-type="ppub">
<day>27</day>
<month>9</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="epub">
<day>20</day>
<month>9</month>
<year>2017</year>
</pub-date>
<pub-date pub-type="pmc-release">
<day>20</day>
<month>9</month>
<year>2017</year>
</pub-date>
<pmc-comment> PMC Release delay is 0 months and 0 days and was based on the . </pmc-comment>
<volume>284</volume>
<issue>1863</issue>
<elocation-id>20170660</elocation-id>
<history>
<date date-type="received">
<day>29</day>
<month>3</month>
<year>2017</year>
</date>
<date date-type="accepted">
<day>10</day>
<month>8</month>
<year>2017</year>
</date>
</history>
<permissions>
<copyright-statement>© 2017 The Authors.</copyright-statement>
<copyright-year>2017</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/">
<license-p>Published by the Royal Society under the terms of the Creative Commons Attribution License
<uri xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</uri>
, which permits unrestricted use, provided the original author and source are credited.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:href="rspb20170660.pdf"></self-uri>
<abstract>
<p>Effective ecosystem risk assessment relies on a conceptual understanding of ecosystem dynamics and the synthesis of multiple lines of evidence. Risk assessment protocols and ecosystem models integrate limited observational data with threat scenarios, making them valuable tools for monitoring ecosystem status and diagnosing key mechanisms of decline to be addressed by management. We applied the IUCN Red List of Ecosystems criteria to quantify the risk of collapse of the Meso-American Reef, a unique ecosystem containing the second longest barrier reef in the world. We collated a wide array of empirical data (field and remotely sensed), and used a stochastic ecosystem model to backcast past ecosystem dynamics, as well as forecast future ecosystem dynamics under 11 scenarios of threat. The ecosystem is at high risk from mass bleaching in the coming decades, with compounding effects of ocean acidification, hurricanes, pollution and fishing. The overall status of the ecosystem is Critically Endangered (plausibly Vulnerable to Critically Endangered), with notable differences among Red List criteria and data types in detecting the most severe symptoms of risk. Our case study provides a template for assessing risks to coral reefs and for further application of ecosystem models in risk assessment.</p>
</abstract>
<kwd-group>
<kwd>ecosystem collapse</kwd>
<kwd>coral reefs</kwd>
<kwd>stochastic model</kwd>
<kwd>indicators</kwd>
<kwd>IUCN Red List of Ecosystems</kwd>
<kwd>Meso-American Reef</kwd>
</kwd-group>
<funding-group>
<award-group>
<funding-source>
<institution-wrap>
<institution>Veski</institution>
</institution-wrap>
</funding-source>
<award-id>Veski Inspiring Women Fellowship</award-id>
</award-group>
<award-group>
<funding-source>
<institution-wrap>
<institution>Australian Research Council</institution>
<institution-id>http://dx.doi.org/10.13039/501100000923</institution-id>
</institution-wrap>
</funding-source>
<award-id>LP 130100435</award-id>
</award-group>
</funding-group>
<custom-meta-group>
<custom-meta>
<meta-name>cover-date</meta-name>
<meta-value>September 27, 2017</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
</pmc>
</record>

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