Bi-dimensional null model analysis of presence-absence binary matrices.
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| Title: | Bi-dimensional null model analysis of presence-absence binary matrices. |
|---|---|
| Authors: | Strona, Giovanni1 giovanni.strona@ec.europa.eu, Ulrich, Werner2, Gotelli, Nicholas J.3 |
| Source: | Ecology. Jan2018, Vol. 99 Issue 1, p103-115. 13p. |
| Subjects: | Null models (Ecology), Ecology simulation methods, Ecological research, Biodiversity research, Ecology projects |
| Abstract: | Comparing the structure of presence/absence (i.e., binary) matrices with those of randomized counterparts is a common practice in ecology. However, differences in the randomization procedures (null models) can affect the results of the comparisons, leading matrix structural patterns to appear either 'random' or not. Subjectivity in the choice of one particular null model over another makes it often advisable to compare the results obtained using several different approaches. Yet, available algorithms to randomize binary matrices differ substantially in respect to the constraints they impose on the discrepancy between observed and randomized row and column marginal totals, which complicates the interpretation of contrasting patterns. This calls for new strategies both to explore intermediate scenarios of restrictiveness in-between extreme constraint assumptions, and to properly synthesize the resulting information. Here we introduce a new modeling framework based on a flexible matrix randomization algorithm (named the 'Tuning Peg' algorithm) that addresses both issues. The algorithm consists of a modified swap procedure in which the discrepancy between the row and column marginal totals of the target matrix and those of its randomized counterpart can be 'tuned' in a continuous way by two parameters (controlling, respectively, row and column discrepancy). We show how combining the Tuning Peg with a wise random walk procedure makes it possible to explore the complete null space embraced by existing algorithms. This exploration allows researchers to visualize matrix structural patterns in an innovative bi-dimensional landscape of significance/effect size. We demonstrate the rational and potential of our approach with a set of simulated and real matrices, showing how the simultaneous investigation of a comprehensive and continuous portion of the null space can be extremely informative, and possibly key to resolving longstanding debates in the analysis of ecological matrices. [ABSTRACT FROM AUTHOR] |
| Copyright of Ecology 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: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 127113206 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Bi-dimensional null model analysis of presence-absence binary matrices. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Strona%2C+Giovanni%22">Strona, Giovanni</searchLink><relatesTo>1</relatesTo><i> giovanni.strona@ec.europa.eu</i><br /><searchLink fieldCode="AR" term="%22Ulrich%2C+Werner%22">Ulrich, Werner</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Gotelli%2C+Nicholas+J%2E%22">Gotelli, Nicholas J.</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Ecology%22">Ecology</searchLink>. Jan2018, Vol. 99 Issue 1, p103-115. 13p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Null+models+%28Ecology%29%22">Null models (Ecology)</searchLink><br /><searchLink fieldCode="DE" term="%22Ecology+simulation+methods%22">Ecology simulation methods</searchLink><br /><searchLink fieldCode="DE" term="%22Ecological+research%22">Ecological research</searchLink><br /><searchLink fieldCode="DE" term="%22Biodiversity+research%22">Biodiversity research</searchLink><br /><searchLink fieldCode="DE" term="%22Ecology+projects%22">Ecology projects</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Comparing the structure of presence/absence (i.e., binary) matrices with those of randomized counterparts is a common practice in ecology. However, differences in the randomization procedures (null models) can affect the results of the comparisons, leading matrix structural patterns to appear either 'random' or not. Subjectivity in the choice of one particular null model over another makes it often advisable to compare the results obtained using several different approaches. Yet, available algorithms to randomize binary matrices differ substantially in respect to the constraints they impose on the discrepancy between observed and randomized row and column marginal totals, which complicates the interpretation of contrasting patterns. This calls for new strategies both to explore intermediate scenarios of restrictiveness in-between extreme constraint assumptions, and to properly synthesize the resulting information. Here we introduce a new modeling framework based on a flexible matrix randomization algorithm (named the 'Tuning Peg' algorithm) that addresses both issues. The algorithm consists of a modified swap procedure in which the discrepancy between the row and column marginal totals of the target matrix and those of its randomized counterpart can be 'tuned' in a continuous way by two parameters (controlling, respectively, row and column discrepancy). We show how combining the Tuning Peg with a wise random walk procedure makes it possible to explore the complete null space embraced by existing algorithms. This exploration allows researchers to visualize matrix structural patterns in an innovative bi-dimensional landscape of significance/effect size. We demonstrate the rational and potential of our approach with a set of simulated and real matrices, showing how the simultaneous investigation of a comprehensive and continuous portion of the null space can be extremely informative, and possibly key to resolving longstanding debates in the analysis of ecological matrices. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Ecology 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/ecy.2043 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 103 Subjects: – SubjectFull: Null models (Ecology) Type: general – SubjectFull: Ecology simulation methods Type: general – SubjectFull: Ecological research Type: general – SubjectFull: Biodiversity research Type: general – SubjectFull: Ecology projects Type: general Titles: – TitleFull: Bi-dimensional null model analysis of presence-absence binary matrices. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Strona, Giovanni – PersonEntity: Name: NameFull: Ulrich, Werner – PersonEntity: Name: NameFull: Gotelli, Nicholas J. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: Jan2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 00129658 Numbering: – Type: volume Value: 99 – Type: issue Value: 1 Titles: – TitleFull: Ecology Type: main |
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