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Geostatistical models for identifying juvenile fish hotspots in marine conservation

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Detalhes bibliográficos
Resumo:Species distribution models play a pivotal role in the management and conservation of commercially significant marine species. This work focuses on investigating geostatistical models that connect species occurrence and biomass observations with environmental covariates at a limited number of locations. The main objectives are to identify hotspots of juvenile richness, and map recruitment areas and seasons. Our analysis centers on the landing per unit of effort of small sardine (Sardina pilchardus, length 11–15 cms) along the northern Portuguese coast during a period with fewer administrative fishing restrictions (2007–2011). Using a Bayesian-INLA framework, we address the complexity associated with hierarchical geostatistical models capable of handling temporally collected data. The results of this study enhance our understanding of juvenile sardine distributions and allow us to identify hotspots, contributing to the sustainability of marine ecosystems and the preservation of commercially significant species.
Autores principais:Menezes, Raquel
Outros Autores:Gonçalves, Francisco; Silva, Daniela; Dias, Inês; Silva, Alexandra A.
Assunto:Geostatistics Species distribution models Bayesian framework Recruitment areas Geostatistics ⋅ Species distribution models ⋅ Recruitment areas ⋅ Bayesian framework Ciências Naturais::Matemáticas
Ano:2025
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
Descrição
Resumo:Species distribution models play a pivotal role in the management and conservation of commercially significant marine species. This work focuses on investigating geostatistical models that connect species occurrence and biomass observations with environmental covariates at a limited number of locations. The main objectives are to identify hotspots of juvenile richness, and map recruitment areas and seasons. Our analysis centers on the landing per unit of effort of small sardine (Sardina pilchardus, length 11–15 cms) along the northern Portuguese coast during a period with fewer administrative fishing restrictions (2007–2011). Using a Bayesian-INLA framework, we address the complexity associated with hierarchical geostatistical models capable of handling temporally collected data. The results of this study enhance our understanding of juvenile sardine distributions and allow us to identify hotspots, contributing to the sustainability of marine ecosystems and the preservation of commercially significant species.

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