2023
DOI: 10.1002/ece3.10549
|View full text |Cite
|
Sign up to set email alerts
|

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

Antonio Garcia‐Quintas,
Amédée Roy,
Christophe Barbraud
et al.

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 land and sea features over several spatial scales. Seabirds explore these features prior to breeding, assessing habitats' quality. However, the information‐gathering and decision‐making process by seabirds when choosing a bre… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
references
References 63 publications
0
0
0
Order By: Relevance