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Rule-based predictive models are not cost-effective alternatives to bird monitoring on farmland

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Title: Rule-based predictive models are not cost-effective alternatives to bird monitoring on farmland
Authors: Chamberlain, D.E.1 dan.chamberlain@bto.org, Gough, S.2, Vickery, J.A.2, Firbank, L.G.3, Petit, S.3, Pywell, R.4, Bradbury, R.B.5
Source: Agriculture, Ecosystems & Environment. Jan2004, Vol. 101 Issue 1, p1. 8p.
Subject Terms: *Birds, *Species, *Habitats, Skylark
Abstract: Monitoring bird populations is labour-intensive and requires expert knowledge. Development of more cost-effective methods of bird species monitoring is therefore desirable. Simple rule-based (RB) models were developed that predicted the presence of birds in lowland arable farmland in the breeding season. These were based on the presence of key habitat elements required by the birds identified from the literature. Habitat data and bird data were collected independently from 525 transects each of which ran along a field margin. Model performance was tested in five species: grey partridge Perdix perdix, skylark Alauda arvensis, linnet Carduelis cannabina, corn bunting Miliaria calandra and yellowhammer Emberiza citrinella. RB models were not good predictors of species presence. Model performance did not vary appreciably between early or late breeding season or according to geographic region. Skylark had the best performing model, but even in this case the predictive power was low. Prediction of species presence from habitat survey data is therefore unlikely to be a cost-effective method of monitoring birds on British farmland. [Copyright &y& Elsevier]
Copyright of Agriculture, Ecosystems & Environment 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
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Header DbId: 8gh
DbLabel: GreenFILE
An: 11769330
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Rule-based predictive models are not cost-effective alternatives to bird monitoring on farmland
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  Data: <searchLink fieldCode="AR" term="%22Chamberlain%2C+D%2EE%2E%22">Chamberlain, D.E.</searchLink><relatesTo>1</relatesTo><i> dan.chamberlain@bto.org</i><br /><searchLink fieldCode="AR" term="%22Gough%2C+S%2E%22">Gough, S.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Vickery%2C+J%2EA%2E%22">Vickery, J.A.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Firbank%2C+L%2EG%2E%22">Firbank, L.G.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Petit%2C+S%2E%22">Petit, S.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Pywell%2C+R%2E%22">Pywell, R.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Bradbury%2C+R%2EB%2E%22">Bradbury, R.B.</searchLink><relatesTo>5</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Agriculture%2C+Ecosystems+%26+Environment%22">Agriculture, Ecosystems & Environment</searchLink>. Jan2004, Vol. 101 Issue 1, p1. 8p.
– Name: Subject
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  Data: *<searchLink fieldCode="DE" term="%22Birds%22">Birds</searchLink><br />*<searchLink fieldCode="DE" term="%22Species%22">Species</searchLink><br />*<searchLink fieldCode="DE" term="%22Habitats%22">Habitats</searchLink><br /><searchLink fieldCode="DE" term="%22Skylark%22">Skylark</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Monitoring bird populations is labour-intensive and requires expert knowledge. Development of more cost-effective methods of bird species monitoring is therefore desirable. Simple rule-based (RB) models were developed that predicted the presence of birds in lowland arable farmland in the breeding season. These were based on the presence of key habitat elements required by the birds identified from the literature. Habitat data and bird data were collected independently from 525 transects each of which ran along a field margin. Model performance was tested in five species: grey partridge Perdix perdix, skylark Alauda arvensis, linnet Carduelis cannabina, corn bunting Miliaria calandra and yellowhammer Emberiza citrinella. RB models were not good predictors of species presence. Model performance did not vary appreciably between early or late breeding season or according to geographic region. Skylark had the best performing model, but even in this case the predictive power was low. Prediction of species presence from habitat survey data is therefore unlikely to be a cost-effective method of monitoring birds on British farmland. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Agriculture, Ecosystems & Environment 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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        Value: 10.1016/S0167-8809(03)00277-9
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        Text: English
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              Text: Jan2004
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