Multi-criteria analysis for rapid vulnerability assessment of marine species to climate change

Champion, C; Lawson, JR; Pardoe, J; Cruz, DO; Fowler, AM; Jaine, F; Schilling, HT; Coleman, MA

Multi-criteria analysis for rapid vulnerability assessment of marine species to climate change

Champion, C Lawson, JR Pardoe, J Cruz, DO Fowler, AM Jaine, F Schilling, HT Coleman, MA

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Publisher:: Springer Nature
Publication Type:: Journal Article
Citation:: Climatic Change, 2023, 176, (8), pp. 99
Issue Date:: 2023-08-01

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Field	Value	Language
dc.contributor.author	Champion, C
dc.contributor.author	Lawson, JR
dc.contributor.author	Pardoe, J
dc.contributor.author	Cruz, DO
dc.contributor.author	Fowler, AM
dc.contributor.author	Jaine, F
dc.contributor.author	Schilling, HT
dc.contributor.author	Coleman, MA
dc.date.accessioned	2024-01-17T05:32:46Z
dc.date.available	2024-01-17T05:32:46Z
dc.date.issued	2023-08-01
dc.identifier.citation	Climatic Change, 2023, 176, (8), pp. 99
dc.identifier.issn	0165-0009
dc.identifier.issn	1573-1480
dc.identifier.uri	http://hdl.handle.net/10453/174704
dc.description.abstract	The accelerating pace of climate-induced stress to global ecosystems threatens the sustainable management and conservation of biodiversity. To effectively respond, researchers and managers require rapid vulnerability assessment tools that can be readily implemented using diverse and existing knowledge sources. Here we demonstrate the application of multi-criteria analysis (MCA) for this purpose using a group of coastal-pelagic fishes from south-eastern Australia as a case-study. We show that MCA has the capacity to formally structure diverse knowledge sources, ranging from peer-reviewed information (which informed 29.2% of criteria among models) to expert knowledge (which informed 22.6% of criteria among models), to quantify the sensitivity of species to biophysical conditions. By integrating MCA models with spatial climate data over historical and future periods, we demonstrate the application of MCA for rapidly assessing the vulnerability of marine species to climate change. Spatial analyses revealed an apparent trend among case-study species towards increasing or stable vulnerability to projected climate change throughout the northern (i.e. equatorward) extent of the study domain and the emergence of climate refugia throughout southern (i.e. poleward) regions. Results from projections using the MCA method were consistent with past analyses of the redistribution of suitable habitat for coastal-pelagic fishes off eastern Australia under climate change. By demonstrating the value of MCA for rapidly assessing the vulnerability of marine species to climate change, we highlight the opportunity to develop user-friendly software infrastructures integrated with marine climate projection data to support the interdisciplinary application of this method.
dc.language	en
dc.publisher	Springer Nature
dc.relation.ispartof	Climatic Change
dc.relation.isbasedon	10.1007/s10584-023-03577-2
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Meteorology & Atmospheric Sciences
dc.title	Multi-criteria analysis for rapid vulnerability assessment of marine species to climate change
dc.type	Journal Article
utslib.citation.volume	176
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
utslib.copyright.status	open_access	*
dc.date.updated	2024-01-17T05:32:44Z
pubs.issue	8
pubs.publication-status	Published
pubs.volume	176
utslib.citation.issue	8

Abstract:

The accelerating pace of climate-induced stress to global ecosystems threatens the sustainable management and conservation of biodiversity. To effectively respond, researchers and managers require rapid vulnerability assessment tools that can be readily implemented using diverse and existing knowledge sources. Here we demonstrate the application of multi-criteria analysis (MCA) for this purpose using a group of coastal-pelagic fishes from south-eastern Australia as a case-study. We show that MCA has the capacity to formally structure diverse knowledge sources, ranging from peer-reviewed information (which informed 29.2% of criteria among models) to expert knowledge (which informed 22.6% of criteria among models), to quantify the sensitivity of species to biophysical conditions. By integrating MCA models with spatial climate data over historical and future periods, we demonstrate the application of MCA for rapidly assessing the vulnerability of marine species to climate change. Spatial analyses revealed an apparent trend among case-study species towards increasing or stable vulnerability to projected climate change throughout the northern (i.e. equatorward) extent of the study domain and the emergence of climate refugia throughout southern (i.e. poleward) regions. Results from projections using the MCA method were consistent with past analyses of the redistribution of suitable habitat for coastal-pelagic fishes off eastern Australia under climate change. By demonstrating the value of MCA for rapidly assessing the vulnerability of marine species to climate change, we highlight the opportunity to develop user-friendly software infrastructures integrated with marine climate projection data to support the interdisciplinary application of this method.

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http://hdl.handle.net/10453/174704