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Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions.

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Title: Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions.
Authors: Delaney JT; U.S. Geological Survey, La Crosse, Wisconsin, USA., Larson DM; U.S. Geological Survey, La Crosse, Wisconsin, USA.
Source: Conservation biology : the journal of the Society for Conservation Biology [Conserv Biol] 2024 Jun; Vol. 38 (3), pp. e14203. Date of Electronic Publication: 2024 Jan 18.
Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
Journal Info: Publisher: Blackwell Publishing, Inc. on behalf of the Society for Conservation Biology Country of Publication: United States NLM ID: 9882301 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1523-1739 (Electronic) Linking ISSN: 08888892 NLM ISO Abbreviation: Conserv Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Availability: 0
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An: 37817744
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions.
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  Data: <searchLink fieldCode="AU" term="%22Delaney+JT%22">Delaney JT</searchLink>; U.S. Geological Survey, La Crosse, Wisconsin, USA.<br /><searchLink fieldCode="AU" term="%22Larson+DM%22">Larson DM</searchLink>; U.S. Geological Survey, La Crosse, Wisconsin, USA.
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  Data: <searchLink fieldCode="JN" term="%229882301%22">Conservation biology : the journal of the Society for Conservation Biology</searchLink> [Conserv Biol] 2024 Jun; Vol. 38 (3), pp. e14203. <i>Date of Electronic Publication: </i>2024 Jan 18.
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  Data: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Blackwell+Publishing%2C+Inc%2E+on+behalf+of+the+Society+for+Conservation+Biology%22">Blackwell Publishing, Inc. on behalf of the Society for Conservation Biology </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>9882301 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1523-1739 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2208888892%22">08888892 </searchLink><i>NLM ISO Abbreviation: </i>Conserv Biol <i>Subsets: </i>MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=37817744
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        Value: 10.1111/cobi.14203
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      – Code: eng
        Text: English
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        StartPage: e14203
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      – TitleFull: Using explainable machine learning methods to evaluate vulnerability and restoration potential of ecosystem state transitions.
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            NameFull: Delaney JT
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            NameFull: Larson DM
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              Text: 2024 Jun
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              Y: 2024
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              Value: 1523-1739
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              Value: 38
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            – TitleFull: Conservation biology : the journal of the Society for Conservation Biology
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