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Article: Population dynamics can be more important than physiological limits for determining range shifts under climate change

TitlePopulation dynamics can be more important than physiological limits for determining range shifts under climate change
Authors
KeywordsMarine biodiversity conservation
Marine species distribution model
Mechanistic model
Demographic processes
Abalone
Source-sink dynamics
Population viability analysis
Metapopulation dynamics
Ecological niche model
Extinction risk
Issue Date2013
Citation
Global Change Biology, 2013, v. 19, n. 10, p. 3224-3237 How to Cite?
AbstractEvidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal-limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate-related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate-dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non-linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source-sink dynamics and dispersal-limitation. © 2013 John Wiley & Sons Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/213356
ISSN
2021 Impact Factor: 13.211
2020 SCImago Journal Rankings: 4.146
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorFordham, Damien A.-
dc.contributor.authorMellin, Camille-
dc.contributor.authorRussell, Bayden D.-
dc.contributor.authorAkçakaya, Reşit H.-
dc.contributor.authorBradshaw, Corey J A-
dc.contributor.authorAiello-Lammens, Matthew E.-
dc.contributor.authorCaley, Julian M.-
dc.contributor.authorConnell, Sean D.-
dc.contributor.authorMayfield, Stephen-
dc.contributor.authorShepherd, Scoresby A.-
dc.contributor.authorBrook, Barry W.-
dc.date.accessioned2015-07-28T04:07:00Z-
dc.date.available2015-07-28T04:07:00Z-
dc.date.issued2013-
dc.identifier.citationGlobal Change Biology, 2013, v. 19, n. 10, p. 3224-3237-
dc.identifier.issn1354-1013-
dc.identifier.urihttp://hdl.handle.net/10722/213356-
dc.description.abstractEvidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal-limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate-related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate-dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non-linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source-sink dynamics and dispersal-limitation. © 2013 John Wiley & Sons Ltd.-
dc.languageeng-
dc.relation.ispartofGlobal Change Biology-
dc.subjectMarine biodiversity conservation-
dc.subjectMarine species distribution model-
dc.subjectMechanistic model-
dc.subjectDemographic processes-
dc.subjectAbalone-
dc.subjectSource-sink dynamics-
dc.subjectPopulation viability analysis-
dc.subjectMetapopulation dynamics-
dc.subjectEcological niche model-
dc.subjectExtinction risk-
dc.titlePopulation dynamics can be more important than physiological limits for determining range shifts under climate change-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/gcb.12289-
dc.identifier.pmid23907833-
dc.identifier.scopuseid_2-s2.0-84883524917-
dc.identifier.volume19-
dc.identifier.issue10-
dc.identifier.spage3224-
dc.identifier.epage3237-
dc.identifier.eissn1365-2486-
dc.identifier.isiWOS:000323844200027-
dc.identifier.issnl1354-1013-

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