Facial Recognition Analyses Reveal Social Networks of Co‐Occurrence at Harbor Seal Haul‐Out Sites.
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| Title: | Facial Recognition Analyses Reveal Social Networks of Co‐Occurrence at Harbor Seal Haul‐Out Sites. |
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| Authors: | Hall, Wyatt1 (AUTHOR), Hanson, Abigail1 (AUTHOR), Dunn, Sydney1 (AUTHOR), Benton, Ava1 (AUTHOR), Filipowicz, C.1 (AUTHOR), Khazaee, Ahmad2 (AUTHOR), Dinçer, Tolga2 (AUTHOR), Ingram, Krista K.1 (AUTHOR) kingram@colgate.edu |
| Source: | Ecology & Evolution (20457758). Jun2026, Vol. 16 Issue 6, p1-14. 14p. |
| Subject Terms: | *Animal behavior, *Population dynamics, *Marine ecology, Harbor seal, Social networks, Human facial recognition software, Place attachment (Psychology) |
| Geographic Terms: | Maine |
| Abstract: | Understanding the behavior and population dynamics of harbor seals (Phoca vitulina), an ecologically significant and widespread coastal pinniped, is vital to effectively manage vulnerable coastal marine ecosystems. A novel, non‐invasive facial recognition technology was used to identify harbor seals at haul‐out sites across two consecutive molting seasons in Middle Bay, Maine. Using a gallery of 672 individual seals found in the bay over a 6‐year period, we recorded the presence of seals at target sites over 30 days across 2 years and constructed social network analyses based on repeated co‐occurrences at these sites within the seasons and across years. Our results revealed strong site fidelity among a subset of seals across years and persistent co‐occurrences between individual seals within seasons and across years, suggesting non‐random haul‐out behaviors within the region. A core group of seals central to the networks were regularly observed at the sites across the span of the molting season, indicating strong site co‐fidelity of seals during this season. Module membership of co‐occurring seals varied across years, but the overall structure of the network (graph density, average degree, average clustering and average path length) remained consistent across years. These findings underscore the robust site fidelity of harbor seals to specific haul‐out locations in Middle Bay and demonstrate that harbor seals are not transient visitors to this region. This study also demonstrates the utility of facial recognition as an effective, non‐invasive method for long‐term monitoring of wild seal movements, distribution, habitat use, and social interactions. Using this approach can provide novel insights into how individuals and populations of wild seals respond to environmental or anthropogenic changes and can inform conservation efforts to mitigate threats to coastal ecosystems. [ABSTRACT FROM AUTHOR] |
| Copyright of Ecology & Evolution (20457758) is the property of Wiley-Blackwell 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 |
| FullText | Text: Availability: 0 |
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| Header | DbId: 8gh DbLabel: GreenFILE An: 194870768 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Facial Recognition Analyses Reveal Social Networks of Co‐Occurrence at Harbor Seal Haul‐Out Sites. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hall%2C+Wyatt%22">Hall, Wyatt</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hanson%2C+Abigail%22">Hanson, Abigail</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dunn%2C+Sydney%22">Dunn, Sydney</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Benton%2C+Ava%22">Benton, Ava</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Filipowicz%2C+C%2E%22">Filipowicz, C.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Khazaee%2C+Ahmad%22">Khazaee, Ahmad</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dinçer%2C+Tolga%22">Dinçer, Tolga</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ingram%2C+Krista+K%2E%22">Ingram, Krista K.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> kingram@colgate.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Ecology+%26+Evolution+%2820457758%29%22">Ecology & Evolution (20457758)</searchLink>. Jun2026, Vol. 16 Issue 6, p1-14. 14p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Animal+behavior%22">Animal behavior</searchLink><br />*<searchLink fieldCode="DE" term="%22Population+dynamics%22">Population dynamics</searchLink><br />*<searchLink fieldCode="DE" term="%22Marine+ecology%22">Marine ecology</searchLink><br /><searchLink fieldCode="DE" term="%22Harbor+seal%22">Harbor seal</searchLink><br /><searchLink fieldCode="DE" term="%22Social+networks%22">Social networks</searchLink><br /><searchLink fieldCode="DE" term="%22Human+facial+recognition+software%22">Human facial recognition software</searchLink><br /><searchLink fieldCode="DE" term="%22Place+attachment+%28Psychology%29%22">Place attachment (Psychology)</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Maine%22">Maine</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Understanding the behavior and population dynamics of harbor seals (Phoca vitulina), an ecologically significant and widespread coastal pinniped, is vital to effectively manage vulnerable coastal marine ecosystems. A novel, non‐invasive facial recognition technology was used to identify harbor seals at haul‐out sites across two consecutive molting seasons in Middle Bay, Maine. Using a gallery of 672 individual seals found in the bay over a 6‐year period, we recorded the presence of seals at target sites over 30 days across 2 years and constructed social network analyses based on repeated co‐occurrences at these sites within the seasons and across years. Our results revealed strong site fidelity among a subset of seals across years and persistent co‐occurrences between individual seals within seasons and across years, suggesting non‐random haul‐out behaviors within the region. A core group of seals central to the networks were regularly observed at the sites across the span of the molting season, indicating strong site co‐fidelity of seals during this season. Module membership of co‐occurring seals varied across years, but the overall structure of the network (graph density, average degree, average clustering and average path length) remained consistent across years. These findings underscore the robust site fidelity of harbor seals to specific haul‐out locations in Middle Bay and demonstrate that harbor seals are not transient visitors to this region. This study also demonstrates the utility of facial recognition as an effective, non‐invasive method for long‐term monitoring of wild seal movements, distribution, habitat use, and social interactions. Using this approach can provide novel insights into how individuals and populations of wild seals respond to environmental or anthropogenic changes and can inform conservation efforts to mitigate threats to coastal ecosystems. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Ecology & Evolution (20457758) is the property of Wiley-Blackwell 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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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/ece3.73856 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 1 Subjects: – SubjectFull: Animal behavior Type: general – SubjectFull: Population dynamics Type: general – SubjectFull: Marine ecology Type: general – SubjectFull: Harbor seal Type: general – SubjectFull: Social networks Type: general – SubjectFull: Human facial recognition software Type: general – SubjectFull: Place attachment (Psychology) Type: general – SubjectFull: Maine Type: general Titles: – TitleFull: Facial Recognition Analyses Reveal Social Networks of Co‐Occurrence at Harbor Seal Haul‐Out Sites. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hall, Wyatt – PersonEntity: Name: NameFull: Hanson, Abigail – PersonEntity: Name: NameFull: Dunn, Sydney – PersonEntity: Name: NameFull: Benton, Ava – PersonEntity: Name: NameFull: Filipowicz, C. – PersonEntity: Name: NameFull: Khazaee, Ahmad – PersonEntity: Name: NameFull: Dinçer, Tolga – PersonEntity: Name: NameFull: Ingram, Krista K. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20457758 Numbering: – Type: volume Value: 16 – Type: issue Value: 6 Titles: – TitleFull: Ecology & Evolution (20457758) Type: main |
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