Harnessing citizen science for marine conservation in Malta:: a comparative analysis of GAM and MaxEnt models in bottlenose dolphin habitat mapping

Francesca Soster; Tim Awbery; Nina Vérité–Taulet; Timothy Zammit; Kimberly Terribile

doi:10.7717/peerj.19804

Harnessing citizen science for marine conservation in Malta: a comparative analysis of GAM and MaxEnt models in bottlenose dolphin habitat mapping

Francesca Soster
, Tim Awbery
, Nina Vérité–Taulet
, Timothy Zammit
, Kimberly Terribile

SAMS UHI

Producción científica: Article › revisión exhaustiva

2 Citas (Scopus)

6 Descargas (Pure)

Resumen

Species distribution models (SDMs) are powerful tools for informing conservation, particularly for highly mobile marine species such as common bottlenose dolphins (Tursiops truncatus). In Maltese waters, the limited availability of data on this species has constrained the effectiveness of conservation efforts. Despite the designation of offshore Special Areas of Conservation (SACs), key coastal regions need more detailed spatial studies to support evidence-based management.

Idioma original	English
Número de artículo	e19804
Número de páginas	29
Publicación	PeerJ
Volumen	13
DOI	https://doi.org/10.7717/peerj.19804
Estado	Published - 5 ago 2025

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Harnessing citizen science for marine science for marine conservation in Malta
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https://peerj.com/articles/19804Licencia: CC BY

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abstract = "Species distribution models (SDMs) are powerful tools for informing conservation, particularly for highly mobile marine species such as common bottlenose dolphins (Tursiops truncatus). In Maltese waters, the limited availability of data on this species has constrained the effectiveness of conservation efforts. Despite the designation of offshore Special Areas of Conservation (SACs), key coastal regions need more detailed spatial studies to support evidence-based management.",

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AU - Zammit, Timothy

AU - Terribile, Kimberly

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KW - conservation planning

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Harnessing citizen science for marine conservation in Malta: a comparative analysis of GAM and MaxEnt models in bottlenose dolphin habitat mapping

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