ConR: An R package to assist large-scale multispecies preliminary conservation assessments using distribution data.
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| Title: | ConR: An R package to assist large-scale multispecies preliminary conservation assessments using distribution data. |
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| Authors: | Dauby, Gilles1,2,3 gildauby@gmail.com, Stévart, Tariq4,5,6, Droissart, Vincent6,7, Cosiaux, Ariane1,8, Deblauwe, Vincent6,9,10, Simo‐Droissart, Murielle8, Sosef, Marc S. M.5, Lowry, Porter P.4,11, Schatz, George E.4, Gereau, Roy E.4, Couvreur, Thomas L. P.1,8 |
| Source: | Ecology & Evolution (20457758). Dec2017, Vol. 7 Issue 24, p11292-11303. 12p. |
| Subject Terms: | *Conservation of natural resources, *Conservation biology, Data analysis, Parameter estimation, Number theory |
| Abstract: | The Red List Categories and the accompanying five criteria developed by the International Union for Conservation of Nature ( IUCN) provide an authoritative and comprehensive methodology to assess the conservation status of organisms. Red List criterion B, which principally uses distribution data, is the most widely used to assess conservation status, particularly of plant species. No software package has previously been available to perform large-scale multispecies calculations of the three main criterion B parameters [extent of occurrence ( EOO), area of occupancy ( AOO) and an estimate of the number of locations] and provide preliminary conservation assessments using an automated batch process. We developed ConR, a dedicated R package, as a rapid and efficient tool to conduct large numbers of preliminary assessments, thereby facilitating complete Red List assessment. ConR (1) calculates key geographic range parameters ( AOO and EOO) and estimates the number of locations sensu IUCN needed for an assessment under criterion B; (2) uses this information in a batch process to generate preliminary assessments of multiple species; (3) summarize the parameters and preliminary assessments in a spreadsheet; and (4) provides a visualization of the results by generating maps suitable for the submission of full assessments to the IUCN Red List. ConR can be used for any living organism for which reliable georeferenced distribution data are available. As distributional data for taxa become increasingly available via large open access datasets, ConR provides a novel, timely tool to guide and accelerate the work of the conservation and taxonomic communities by enabling practitioners to conduct preliminary assessments simultaneously for hundreds or even thousands of species in an efficient and time-saving way. [ABSTRACT FROM AUTHOR] |
| Copyright of Ecology & Evolution (20457758) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | GreenFILE |
| FullText | Text: Availability: 0 |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 126965195 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: ConR: An R package to assist large-scale multispecies preliminary conservation assessments using distribution data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Dauby%2C+Gilles%22">Dauby, Gilles</searchLink><relatesTo>1,2,3</relatesTo><i> gildauby@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Stévart%2C+Tariq%22">Stévart, Tariq</searchLink><relatesTo>4,5,6</relatesTo><br /><searchLink fieldCode="AR" term="%22Droissart%2C+Vincent%22">Droissart, Vincent</searchLink><relatesTo>6,7</relatesTo><br /><searchLink fieldCode="AR" term="%22Cosiaux%2C+Ariane%22">Cosiaux, Ariane</searchLink><relatesTo>1,8</relatesTo><br /><searchLink fieldCode="AR" term="%22Deblauwe%2C+Vincent%22">Deblauwe, Vincent</searchLink><relatesTo>6,9,10</relatesTo><br /><searchLink fieldCode="AR" term="%22Simo‐Droissart%2C+Murielle%22">Simo‐Droissart, Murielle</searchLink><relatesTo>8</relatesTo><br /><searchLink fieldCode="AR" term="%22Sosef%2C+Marc+S%2E+M%2E%22">Sosef, Marc S. M.</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Lowry%2C+Porter+P%2E%22">Lowry, Porter P.</searchLink><relatesTo>4,11</relatesTo><br /><searchLink fieldCode="AR" term="%22Schatz%2C+George+E%2E%22">Schatz, George E.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Gereau%2C+Roy+E%2E%22">Gereau, Roy E.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Couvreur%2C+Thomas+L%2E+P%2E%22">Couvreur, Thomas L. P.</searchLink><relatesTo>1,8</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Ecology+%26+Evolution+%2820457758%29%22">Ecology & Evolution (20457758)</searchLink>. Dec2017, Vol. 7 Issue 24, p11292-11303. 12p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Conservation+of+natural+resources%22">Conservation of natural resources</searchLink><br />*<searchLink fieldCode="DE" term="%22Conservation+biology%22">Conservation biology</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Number+theory%22">Number theory</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The Red List Categories and the accompanying five criteria developed by the International Union for Conservation of Nature ( IUCN) provide an authoritative and comprehensive methodology to assess the conservation status of organisms. Red List criterion B, which principally uses distribution data, is the most widely used to assess conservation status, particularly of plant species. No software package has previously been available to perform large-scale multispecies calculations of the three main criterion B parameters [extent of occurrence ( EOO), area of occupancy ( AOO) and an estimate of the number of locations] and provide preliminary conservation assessments using an automated batch process. We developed ConR, a dedicated R package, as a rapid and efficient tool to conduct large numbers of preliminary assessments, thereby facilitating complete Red List assessment. ConR (1) calculates key geographic range parameters ( AOO and EOO) and estimates the number of locations sensu IUCN needed for an assessment under criterion B; (2) uses this information in a batch process to generate preliminary assessments of multiple species; (3) summarize the parameters and preliminary assessments in a spreadsheet; and (4) provides a visualization of the results by generating maps suitable for the submission of full assessments to the IUCN Red List. ConR can be used for any living organism for which reliable georeferenced distribution data are available. As distributional data for taxa become increasingly available via large open access datasets, ConR provides a novel, timely tool to guide and accelerate the work of the conservation and taxonomic communities by enabling practitioners to conduct preliminary assessments simultaneously for hundreds or even thousands of species in an efficient and time-saving way. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Ecology & Evolution (20457758) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/ece3.3704 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 11292 Subjects: – SubjectFull: Conservation of natural resources Type: general – SubjectFull: Conservation biology Type: general – SubjectFull: Data analysis Type: general – SubjectFull: Parameter estimation Type: general – SubjectFull: Number theory Type: general Titles: – TitleFull: ConR: An R package to assist large-scale multispecies preliminary conservation assessments using distribution data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Dauby, Gilles – PersonEntity: Name: NameFull: Stévart, Tariq – PersonEntity: Name: NameFull: Droissart, Vincent – PersonEntity: Name: NameFull: Cosiaux, Ariane – PersonEntity: Name: NameFull: Deblauwe, Vincent – PersonEntity: Name: NameFull: Simo‐Droissart, Murielle – PersonEntity: Name: NameFull: Sosef, Marc S. M. – PersonEntity: Name: NameFull: Lowry, Porter P. – PersonEntity: Name: NameFull: Schatz, George E. – PersonEntity: Name: NameFull: Gereau, Roy E. – PersonEntity: Name: NameFull: Couvreur, Thomas L. P. IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 12 Text: Dec2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 20457758 Numbering: – Type: volume Value: 7 – Type: issue Value: 24 Titles: – TitleFull: Ecology & Evolution (20457758) Type: main |
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