Using multiple lines of evidence to assess the risk of ecosystem collapse.
Identifieur interne : 000486 ( PubMed/Corpus ); précédent : 000485; suivant : 000487Using multiple lines of evidence to assess the risk of ecosystem collapse.
Auteurs : Lucie M. Bland ; Tracey J. Regan ; Minh Ngoc Dinh ; Renata Ferrari ; David A. Keith ; Rebecca Lester ; David Mouillot ; Nicholas J. Murray ; Hoang Anh Nguyen ; Emily NicholsonSource :
- Proceedings. Biological sciences [ 1471-2954 ] ; 2017.
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.
DOI: 10.1098/rspb.2017.0660
PubMed: 28931744
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Regan</name><affiliation><nlm:affiliation>The Arthur Rylah Institute for Environmental Research, the Department of Environment, Land, Water and Planning, 123 Brown Street, Heidelberg, 3084, Victoria, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Dinh, Minh Ngoc" sort="Dinh, Minh Ngoc" uniqKey="Dinh M" first="Minh Ngoc" last="Dinh">Minh Ngoc Dinh</name><affiliation><nlm:affiliation>Research Computing Centre, University of Queensland, St Lucia, 4072, Queensland, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Ferrari, Renata" sort="Ferrari, Renata" uniqKey="Ferrari R" first="Renata" last="Ferrari">Renata Ferrari</name><affiliation><nlm:affiliation>Coastal and Marine Ecosystems Group, School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Keith, David A" sort="Keith, David A" uniqKey="Keith D" first="David A" last="Keith">David A. Keith</name><affiliation><nlm:affiliation>Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Kensington, 2052, New South Wales, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Lester, Rebecca" sort="Lester, Rebecca" uniqKey="Lester R" first="Rebecca" last="Lester">Rebecca Lester</name><affiliation><nlm:affiliation>Deakin University, Australia, Centre for Regional and Rural Futures, Geelong, 3220, Victoria, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Mouillot, David" sort="Mouillot, David" uniqKey="Mouillot D" first="David" last="Mouillot">David Mouillot</name><affiliation><nlm:affiliation>UMR 5119-Écologie des Systèmes marins côtiers, Université Montpellier 2, Montpellier Cedex 5, France.</nlm:affiliation></affiliation></author><author><name sortKey="Murray, Nicholas J" sort="Murray, Nicholas J" uniqKey="Murray N" first="Nicholas J" last="Murray">Nicholas J. Murray</name><affiliation><nlm:affiliation>Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Kensington, 2052, New South Wales, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Nguyen, Hoang Anh" sort="Nguyen, Hoang Anh" uniqKey="Nguyen H" first="Hoang Anh" last="Nguyen">Hoang Anh Nguyen</name><affiliation><nlm:affiliation>Research Computing Centre, University of Queensland, St Lucia, 4072, Queensland, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Nicholson, Emily" sort="Nicholson, Emily" uniqKey="Nicholson E" first="Emily" last="Nicholson">Emily Nicholson</name><affiliation><nlm:affiliation>Deakin University, Australia, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, 3121, Victoria, Australia.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2017">2017</date><idno type="RBID">pubmed:28931744</idno><idno type="pmid">28931744</idno><idno type="doi">10.1098/rspb.2017.0660</idno><idno type="wicri:Area/PubMed/Corpus">000486</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000486</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Using multiple lines of evidence to assess the risk of ecosystem collapse.</title><author><name sortKey="Bland, Lucie M" sort="Bland, Lucie M" uniqKey="Bland L" first="Lucie M" last="Bland">Lucie M. Bland</name><affiliation><nlm:affiliation>Deakin University, Australia, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, 3121, Victoria, Australia l.bland@deakin.edu.au.</nlm:affiliation></affiliation></author><author><name sortKey="Regan, Tracey J" sort="Regan, Tracey J" uniqKey="Regan T" first="Tracey J" last="Regan">Tracey J. Regan</name><affiliation><nlm:affiliation>The Arthur Rylah Institute for Environmental Research, the Department of Environment, Land, Water and Planning, 123 Brown Street, Heidelberg, 3084, Victoria, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Dinh, Minh Ngoc" sort="Dinh, Minh Ngoc" uniqKey="Dinh M" first="Minh Ngoc" last="Dinh">Minh Ngoc Dinh</name><affiliation><nlm:affiliation>Research Computing Centre, University of Queensland, St Lucia, 4072, Queensland, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Ferrari, Renata" sort="Ferrari, Renata" uniqKey="Ferrari R" first="Renata" last="Ferrari">Renata Ferrari</name><affiliation><nlm:affiliation>Coastal and Marine Ecosystems Group, School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Keith, David A" sort="Keith, David A" uniqKey="Keith D" first="David A" last="Keith">David A. Keith</name><affiliation><nlm:affiliation>Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Kensington, 2052, New South Wales, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Lester, Rebecca" sort="Lester, Rebecca" uniqKey="Lester R" first="Rebecca" last="Lester">Rebecca Lester</name><affiliation><nlm:affiliation>Deakin University, Australia, Centre for Regional and Rural Futures, Geelong, 3220, Victoria, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Mouillot, David" sort="Mouillot, David" uniqKey="Mouillot D" first="David" last="Mouillot">David Mouillot</name><affiliation><nlm:affiliation>UMR 5119-Écologie des Systèmes marins côtiers, Université Montpellier 2, Montpellier Cedex 5, France.</nlm:affiliation></affiliation></author><author><name sortKey="Murray, Nicholas J" sort="Murray, Nicholas J" uniqKey="Murray N" first="Nicholas J" last="Murray">Nicholas J. Murray</name><affiliation><nlm:affiliation>Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Kensington, 2052, New South Wales, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Nguyen, Hoang Anh" sort="Nguyen, Hoang Anh" uniqKey="Nguyen H" first="Hoang Anh" last="Nguyen">Hoang Anh Nguyen</name><affiliation><nlm:affiliation>Research Computing Centre, University of Queensland, St Lucia, 4072, Queensland, Australia.</nlm:affiliation></affiliation></author><author><name sortKey="Nicholson, Emily" sort="Nicholson, Emily" uniqKey="Nicholson E" first="Emily" last="Nicholson">Emily Nicholson</name><affiliation><nlm:affiliation>Deakin University, Australia, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, 3121, Victoria, Australia.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Proceedings. Biological sciences</title><idno type="eISSN">1471-2954</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">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.</div></front></TEI><pubmed><MedlineCitation Status="In-Process" Owner="NLM"><PMID Version="1">28931744</PMID><DateCreated><Year>2017</Year><Month>09</Month><Day>21</Day></DateCreated><DateRevised><Year>2017</Year><Month>10</Month><Day>06</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Electronic">1471-2954</ISSN><JournalIssue CitedMedium="Internet"><Volume>284</Volume><Issue>1863</Issue><PubDate><Year>2017</Year><Month>Sep</Month><Day>27</Day></PubDate></JournalIssue><Title>Proceedings. Biological sciences</Title><ISOAbbreviation>Proc. Biol. Sci.</ISOAbbreviation></Journal><ArticleTitle>Using multiple lines of evidence to assess the risk of ecosystem collapse.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">20170660</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1098/rspb.2017.0660</ELocationID><Abstract><AbstractText>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.</AbstractText><CopyrightInformation>© 2017 The Authors.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Bland</LastName><ForeName>Lucie M</ForeName><Initials>LM</Initials><Identifier Source="ORCID">http://orcid.org/0000-0003-0739-114X</Identifier><AffiliationInfo><Affiliation>Deakin University, Australia, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, 3121, Victoria, Australia l.bland@deakin.edu.au.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>School of BioSciences, The University of Melbourne, Parkville, 3010, Victoria, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Regan</LastName><ForeName>Tracey J</ForeName><Initials>TJ</Initials><AffiliationInfo><Affiliation>The Arthur Rylah Institute for Environmental Research, the Department of Environment, Land, Water and Planning, 123 Brown Street, Heidelberg, 3084, Victoria, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Dinh</LastName><ForeName>Minh Ngoc</ForeName><Initials>MN</Initials><AffiliationInfo><Affiliation>Research Computing Centre, University of Queensland, St Lucia, 4072, Queensland, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ferrari</LastName><ForeName>Renata</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Coastal and Marine Ecosystems Group, School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Keith</LastName><ForeName>David A</ForeName><Initials>DA</Initials><AffiliationInfo><Affiliation>Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Kensington, 2052, New South Wales, Australia.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>New South Wales Office of Environment and Heritage, Hurstville, 2220, New South Wales, Australia.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Long Term Ecological Research Network, Terrestrial Ecosystem Research Network, Australian National University, Canberra, 0200, Australian Capital Territory, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lester</LastName><ForeName>Rebecca</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Deakin University, Australia, Centre for Regional and Rural Futures, Geelong, 3220, Victoria, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Mouillot</LastName><ForeName>David</ForeName><Initials>D</Initials><AffiliationInfo><Affiliation>UMR 5119-Écologie des Systèmes marins côtiers, Université Montpellier 2, Montpellier Cedex 5, France.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>ARC Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, 4881, Queensland, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Murray</LastName><ForeName>Nicholas J</ForeName><Initials>NJ</Initials><AffiliationInfo><Affiliation>Centre for Ecosystem Science, School of Biological, Earth and Environmental Science, University of New South Wales, Kensington, 2052, New South Wales, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Nguyen</LastName><ForeName>Hoang Anh</ForeName><Initials>HA</Initials><AffiliationInfo><Affiliation>Research Computing Centre, University of Queensland, St Lucia, 4072, Queensland, Australia.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Nicholson</LastName><ForeName>Emily</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>Deakin University, Australia, School of Life and Environmental Sciences, Centre for Integrative Ecology, Burwood, 3121, Victoria, Australia.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Proc Biol Sci</MedlineTA><NlmUniqueID>101245157</NlmUniqueID><ISSNLinking>0962-8452</ISSNLinking></MedlineJournalInfo><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Nature. 2012 Jun 06;486(7401):59-67</RefSource><PMID Version="1">22678280</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Curr Biol. 2014 May 5;24(9):1000-5</RefSource><PMID Version="1">24746794</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS One. 2009 Jun 03;4(6):e5712</RefSource><PMID Version="1">19492060</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>PLoS One. 2010 Nov 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