Machine and deep learning approaches to understand and predict habitat suitability for seabird breeding

Machine and deep learning approaches to understand and predict habitat suitability for seabird breeding

Abstract The way animals select their breeding habitat may have great impacts on individual fitness. This complex process depends on the integration of information on various environmental factors, over a wide range of spatiotemporal scales. For seabirds, breeding habitat selection integrates both l...

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Bibliographic Details
Main Authors: Antonio Garcia‐Quintas, Amédée Roy, Christophe Barbraud, Hervé Demarcq, Dennis Denis, Sophie Lanco Bertrand
Format: Article
Language:English
Published: Wiley 2023-09-01
Series:Ecology and Evolution
Subjects:
animal habitat modeling
convolutional neural networks
gulls and terns breeding
remote sensing
seabirds' colonies
selection pattern
Online Access:https://doi.org/10.1002/ece3.10549

Internet

https://doi.org/10.1002/ece3.10549

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