Identifying rice fields at risk from damage by the greater flamingo

1 Since the early 1980s, greater flamingos Phoenicopterus ruber roseus have been reported to cause damage to the rice fields of the Camargue, south‐eastern France. 2 We tested whether some rice fields had landscape features that were more attractive to flamingos than others, using data from the peri...

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Veröffentlicht in:The Journal of applied ecology 2001-02, Vol.38 (1), p.170-179
Hauptverfasser: Tourenq, Christophe, Aulagnier, Stéphane, Durieux, Laurent, Lek, Sovan, Mesléard, François, Johnson, Alan, Martin, Jean‐Louis
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container_issue 1
container_start_page 170
container_title The Journal of applied ecology
container_volume 38
creator Tourenq, Christophe
Aulagnier, Stéphane
Durieux, Laurent
Lek, Sovan
Mesléard, François
Johnson, Alan
Martin, Jean‐Louis
description 1 Since the early 1980s, greater flamingos Phoenicopterus ruber roseus have been reported to cause damage to the rice fields of the Camargue, south‐eastern France. 2 We tested whether some rice fields had landscape features that were more attractive to flamingos than others, using data from the period 1993–97 and from 1978 different paddies. Discriminant function analysis (DFA), logistic regression (LR) and artificial neural networks (ANN) were used to identify the environmental variables best explaining flamingo incursions. 3 The most accurate models (LR) gave 75% prediction success and used as predictors the surface area of rice fields, the presence of contiguous damaged fields, the presence of wooded margins and the distance to natural marshes. 4 Our study suggests that it is possible to identify accurately fields at risk from damage in order to concentrate scaring methods. We also suggest that planting hedges should be promoted, and wood cutting discouraged, in high‐risk areas. Following our study a programme of planting of hedges by the Natural Regional Park of the Camargue started at the beginning of 2000. 5 Our work reveals how presence–absence modelling can have clear applications in managing important species that sometimes cause negative impacts locally.
doi_str_mv 10.1046/j.1365-2664.2001.00581.x
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Discriminant function analysis (DFA), logistic regression (LR) and artificial neural networks (ANN) were used to identify the environmental variables best explaining flamingo incursions. 3 The most accurate models (LR) gave 75% prediction success and used as predictors the surface area of rice fields, the presence of contiguous damaged fields, the presence of wooded margins and the distance to natural marshes. 4 Our study suggests that it is possible to identify accurately fields at risk from damage in order to concentrate scaring methods. We also suggest that planting hedges should be promoted, and wood cutting discouraged, in high‐risk areas. 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Discriminant function analysis (DFA), logistic regression (LR) and artificial neural networks (ANN) were used to identify the environmental variables best explaining flamingo incursions. 3 The most accurate models (LR) gave 75% prediction success and used as predictors the surface area of rice fields, the presence of contiguous damaged fields, the presence of wooded margins and the distance to natural marshes. 4 Our study suggests that it is possible to identify accurately fields at risk from damage in order to concentrate scaring methods. We also suggest that planting hedges should be promoted, and wood cutting discouraged, in high‐risk areas. 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Psychology</subject><subject>Human ecology</subject><subject>landscapes</subject><subject>Life Sciences</subject><subject>marshes</subject><subject>Modeling</subject><subject>neural networks</subject><subject>Oryza sativa</subject><subject>paddies</subject><subject>Phoenicopterus roseus</subject><subject>Phoenicopterus ruber</subject><subject>Phoenicopterus ruber roseus</subject><subject>Phytopathology. Animal pests. 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Psychology</topic><topic>Human ecology</topic><topic>landscapes</topic><topic>Life Sciences</topic><topic>marshes</topic><topic>Modeling</topic><topic>neural networks</topic><topic>Oryza sativa</topic><topic>paddies</topic><topic>Phoenicopterus roseus</topic><topic>Phoenicopterus ruber</topic><topic>Phoenicopterus ruber roseus</topic><topic>Phytopathology. Animal pests. Plant and forest protection</topic><topic>planting</topic><topic>prediction</topic><topic>predictive model</topic><topic>regression analysis</topic><topic>Rice</topic><topic>risk</topic><topic>surface area</topic><topic>Sustainable agriculture</topic><topic>Vertebrates</topic><topic>Waterfowl</topic><topic>wood</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tourenq, Christophe</creatorcontrib><creatorcontrib>Aulagnier, Stéphane</creatorcontrib><creatorcontrib>Durieux, Laurent</creatorcontrib><creatorcontrib>Lek, Sovan</creatorcontrib><creatorcontrib>Mesléard, François</creatorcontrib><creatorcontrib>Johnson, Alan</creatorcontrib><creatorcontrib>Martin, Jean‐Louis</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><collection>Ecology Abstracts</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 1: Biological Sciences &amp; Living Resources</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>The Journal of applied ecology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tourenq, Christophe</au><au>Aulagnier, Stéphane</au><au>Durieux, Laurent</au><au>Lek, Sovan</au><au>Mesléard, François</au><au>Johnson, Alan</au><au>Martin, Jean‐Louis</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identifying rice fields at risk from damage by the greater flamingo</atitle><jtitle>The Journal of applied ecology</jtitle><date>2001-02</date><risdate>2001</risdate><volume>38</volume><issue>1</issue><spage>170</spage><epage>179</epage><pages>170-179</pages><issn>0021-8901</issn><eissn>1365-2664</eissn><coden>JAPEAI</coden><abstract>1 Since the early 1980s, greater flamingos Phoenicopterus ruber roseus have been reported to cause damage to the rice fields of the Camargue, south‐eastern France. 2 We tested whether some rice fields had landscape features that were more attractive to flamingos than others, using data from the period 1993–97 and from 1978 different paddies. Discriminant function analysis (DFA), logistic regression (LR) and artificial neural networks (ANN) were used to identify the environmental variables best explaining flamingo incursions. 3 The most accurate models (LR) gave 75% prediction success and used as predictors the surface area of rice fields, the presence of contiguous damaged fields, the presence of wooded margins and the distance to natural marshes. 4 Our study suggests that it is possible to identify accurately fields at risk from damage in order to concentrate scaring methods. We also suggest that planting hedges should be promoted, and wood cutting discouraged, in high‐risk areas. 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subjects Agroecology
Applied ecology
Artificial neural networks
Biological and medical sciences
bird pest
Crops
cultivated fields
cutting
discriminant analysis
Ecological modeling
environmental factors
environmental variables
France
Freshwater
Fundamental and applied biological sciences. Psychology
Human ecology
landscapes
Life Sciences
marshes
Modeling
neural networks
Oryza sativa
paddies
Phoenicopterus roseus
Phoenicopterus ruber
Phoenicopterus ruber roseus
Phytopathology. Animal pests. Plant and forest protection
planting
prediction
predictive model
regression analysis
Rice
risk
surface area
Sustainable agriculture
Vertebrates
Waterfowl
wood
title Identifying rice fields at risk from damage by the greater flamingo
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