Data-driven fuzzy habitat suitability models for brown trout in Spanish Mediterranean rivers
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| Title: | Data-driven fuzzy habitat suitability models for brown trout in Spanish Mediterranean rivers |
|---|---|
| Authors: | Mouton, A.M.1,2 Ans.Mouton@INBO.be, Alcaraz-Hernández, J.D.3, De Baets, B.4, Goethals, P.L.M.2, Martínez-Capel, F.3 |
| Source: | Environmental Modelling & Software. May2011, Vol. 26 Issue 5, p615-622. 8p. |
| Subject Terms: | *Habitats, *Rivers, Fuzzy systems, Mathematical models, Brown trout, Distribution (Probability theory), Algorithms, Statistical decision making |
| Geographic Terms: | Mediterranean Region, Spain |
| Abstract: | Abstract: In recent years, fuzzy models have been acknowledged as a suitable approach for species distribution modelling due to their transparency and their ability to incorporate the ecological gradient theory. Specifically, the overlapping class boundaries of a fuzzy model are similar to the transitions between different environmental conditions. However, the need for ecological expert knowledge is an important constraint when applying fuzzy species distribution models. Moreover, the consistency of the ecological preferences of some fish species across different rivers has been widely contested. Recent research has shown that data-driven fuzzy models may solve this ‘knowledge acquisition bottleneck’ and this paper is a further contribution. The aim was to analyse the brown trout (Salmo trutta fario L.) habitat preferences based on a data-driven fuzzy modelling technique and to compare the resulting fuzzy models with a commonly applied modelling technique, Random Forests. A heuristic nearest ascent hill-climbing algorithm for fuzzy rule optimisation and Random Forests were applied to analyse the ecological preferences of brown trout in 93 mesohabitats. No significant differences in model performance were observed between the optimal fuzzy model and the Random Forests model and both approaches selected river width, the cover index and flow velocity as the most important variables describing brown trout habitat suitability. Further, the fuzzy model combined ecological relevance with reasonable interpretability, whereas the transparency of the Random Forests model was limited. This paper shows that fuzzy models may be a valid approach for species distribution modelling and that their performance is comparable to that of state-of-the-art modelling techniques like Random Forests. Fuzzy models could therefore be a valuable decision support tool for river managers and enhance communication between stakeholders. [Copyright &y& Elsevier] |
| Copyright of Environmental Modelling & Software is the property of Elsevier B.V. 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: 57684302 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Data-driven fuzzy habitat suitability models for brown trout in Spanish Mediterranean rivers – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mouton%2C+A%2EM%2E%22">Mouton, A.M.</searchLink><relatesTo>1,2</relatesTo><i> Ans.Mouton@INBO.be</i><br /><searchLink fieldCode="AR" term="%22Alcaraz-Hernández%2C+J%2ED%2E%22">Alcaraz-Hernández, J.D.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22De+Baets%2C+B%2E%22">De Baets, B.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Goethals%2C+P%2EL%2EM%2E%22">Goethals, P.L.M.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Martínez-Capel%2C+F%2E%22">Martínez-Capel, F.</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Environmental+Modelling+%26+Software%22">Environmental Modelling & Software</searchLink>. May2011, Vol. 26 Issue 5, p615-622. 8p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Habitats%22">Habitats</searchLink><br />*<searchLink fieldCode="DE" term="%22Rivers%22">Rivers</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+systems%22">Fuzzy systems</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Brown+trout%22">Brown trout</searchLink><br /><searchLink fieldCode="DE" term="%22Distribution+%28Probability+theory%29%22">Distribution (Probability theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+decision+making%22">Statistical decision making</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Mediterranean+Region%22">Mediterranean Region</searchLink><br /><searchLink fieldCode="DE" term="%22Spain%22">Spain</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Abstract: In recent years, fuzzy models have been acknowledged as a suitable approach for species distribution modelling due to their transparency and their ability to incorporate the ecological gradient theory. Specifically, the overlapping class boundaries of a fuzzy model are similar to the transitions between different environmental conditions. However, the need for ecological expert knowledge is an important constraint when applying fuzzy species distribution models. Moreover, the consistency of the ecological preferences of some fish species across different rivers has been widely contested. Recent research has shown that data-driven fuzzy models may solve this ‘knowledge acquisition bottleneck’ and this paper is a further contribution. The aim was to analyse the brown trout (Salmo trutta fario L.) habitat preferences based on a data-driven fuzzy modelling technique and to compare the resulting fuzzy models with a commonly applied modelling technique, Random Forests. A heuristic nearest ascent hill-climbing algorithm for fuzzy rule optimisation and Random Forests were applied to analyse the ecological preferences of brown trout in 93 mesohabitats. No significant differences in model performance were observed between the optimal fuzzy model and the Random Forests model and both approaches selected river width, the cover index and flow velocity as the most important variables describing brown trout habitat suitability. Further, the fuzzy model combined ecological relevance with reasonable interpretability, whereas the transparency of the Random Forests model was limited. This paper shows that fuzzy models may be a valid approach for species distribution modelling and that their performance is comparable to that of state-of-the-art modelling techniques like Random Forests. Fuzzy models could therefore be a valuable decision support tool for river managers and enhance communication between stakeholders. [Copyright &y& Elsevier] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Environmental Modelling & Software is the property of Elsevier B.V. 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: 10.1016/j.envsoft.2010.12.001 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 8 StartPage: 615 Subjects: – SubjectFull: Habitats Type: general – SubjectFull: Rivers Type: general – SubjectFull: Fuzzy systems Type: general – SubjectFull: Mathematical models Type: general – SubjectFull: Brown trout Type: general – SubjectFull: Distribution (Probability theory) Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Statistical decision making Type: general – SubjectFull: Mediterranean Region Type: general – SubjectFull: Spain Type: general Titles: – TitleFull: Data-driven fuzzy habitat suitability models for brown trout in Spanish Mediterranean rivers Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mouton, A.M. – PersonEntity: Name: NameFull: Alcaraz-Hernández, J.D. – PersonEntity: Name: NameFull: De Baets, B. – PersonEntity: Name: NameFull: Goethals, P.L.M. – PersonEntity: Name: NameFull: Martínez-Capel, F. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 05 Text: May2011 Type: published Y: 2011 Identifiers: – Type: issn-print Value: 13648152 Numbering: – Type: volume Value: 26 – Type: issue Value: 5 Titles: – TitleFull: Environmental Modelling & Software Type: main |
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