Seabird colony locations and environmental determination of seabird distribution: a spatially explicit breeding seabird model for the Northwest Atlantic. Huettmann, F. & Diamond, A., W. Ecological Modelling, 141(1-3):261-298, 2001.
Seabird colony locations and environmental determination of seabird distribution: a spatially explicit breeding seabird model for the Northwest Atlantic [link]Website  abstract   bibtex   
We investigated whether proximity to a seabird colony is a constraining factor for seabird distribution in summer for the most abundant breeding species in the Canadian North Atlantic. We started with 20 environmental data sets for the marine environment from the Internet/WWW and governmental sources. These environmental factors were spatially stratified and overlaid in a GIS (SPANS Geographic Information System) with the PIROP (Programme integre des recherches sur les oiseaux pelagiques) database for pelagic seabirds in order to analyse how these environmental factors explain the distribution of observed seabirds (presence/absence). A Generalized Linear Model (GLM) was used to explore the significant influences of these factors on seabird distribution, and a Classification and Regression Tree (Cart) then allowed for a detailed description of seabird distribution, and for a spatial modelling approach. The specific seabird model predictions were evaluated by distance to the next seabird colony of seabirds observed, and by its georeferenced residuals using a partition tree. Our results suggest that northern and southern breeding sectors differ in the distribution-determining predictors for seabirds. Foraging distances are longer in the northern breeding sector, which may be related to a richer habitat in the study area south of 52[deg] latitude N. Our models suggest spatial separation between breeders and non-breeders.
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 title = {Seabird colony locations and environmental determination of seabird distribution: a spatially explicit breeding seabird model for the Northwest Atlantic},
 type = {article},
 year = {2001},
 keywords = {Classification and Regression Tree (Cart),Generalized Linear Model (GLM),Geographic Information System (GIS),PIROP database,Seabird colony,Seabird distribution modelling},
 pages = {261-298},
 volume = {141},
 websites = {http://www.sciencedirect.com/science/article/B6VBS-43N738T-J/2/71813ba69f33341fa4d597ba1e7b5b5d},
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 abstract = {We investigated whether proximity to a seabird colony is a constraining factor for seabird distribution in summer for the most abundant breeding species in the Canadian North Atlantic. We started with 20 environmental data sets for the marine environment from the Internet/WWW and governmental sources. These environmental factors were spatially stratified and overlaid in a GIS (SPANS Geographic Information System) with the PIROP (Programme integre des recherches sur les oiseaux pelagiques) database for pelagic seabirds in order to analyse how these environmental factors explain the distribution of observed seabirds (presence/absence). A Generalized Linear Model (GLM) was used to explore the significant influences of these factors on seabird distribution, and a Classification and Regression Tree (Cart) then allowed for a detailed description of seabird distribution, and for a spatial modelling approach. The specific seabird model predictions were evaluated by distance to the next seabird colony of seabirds observed, and by its georeferenced residuals using a partition tree. Our results suggest that northern and southern breeding sectors differ in the distribution-determining predictors for seabirds. Foraging distances are longer in the northern breeding sector, which may be related to a richer habitat in the study area south of 52[deg] latitude N. Our models suggest spatial separation between breeders and non-breeders.},
 bibtype = {article},
 author = {Huettmann, F and Diamond, A W},
 journal = {Ecological Modelling},
 number = {1-3}
}
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