Testing for concordance between predicted species richness, past prioritization, and marine protected area designations in the western Indian Ocean.
Africa
biodiversity proxy
environmental drivers
especies representantes
factores ambientales
marine spatial planning
modelo espacial
planeación espacial marina
riqueza de taxones
spatial modeling
taxa richness
África
Journal
Conservation biology : the journal of the Society for Conservation Biology
ISSN: 1523-1739
Titre abrégé: Conserv Biol
Pays: United States
ID NLM: 9882301
Informations de publication
Date de publication:
28 Mar 2024
28 Mar 2024
Historique:
revised:
29
09
2023
received:
05
06
2023
accepted:
15
01
2024
medline:
28
3
2024
pubmed:
28
3
2024
entrez:
28
3
2024
Statut:
aheadofprint
Résumé
Scientific advances in environmental data coverage and machine learning algorithms have improved the ability to make large-scale predictions where data are missing. These advances allowed us to develop a spatially resolved proxy for predicting numbers of tropical nearshore marine taxa. A diverse marine environmental spatial database was used to model numbers of taxa from ∼1000 field sites, and the predictions were applied to all 7039 6.25-km Evaluación de la concordancia entre la riqueza de especies pronosticada, priorizaciones pasadas y la designación de áreas marinas protegidas en el oeste del Océano Índico Resumen Los avances científicos en la cobertura de datos ambientales y los algoritmos de aprendizaje automatizado han mejorado la capacidad de predecir a gran escala cuando hacen falta datos. Estos avances nos permiten desarrollar un representante con resolución espacial para predecir la cantidad de taxones marinos en las costas tropicales. Usamos una base de datos espaciales de diversos ambientes marinos para modelar la cantidad de taxones a partir de ∼1000 sitios de campo y aplicamos las predicciones a las 7039 celdas arrecifales de 6.25‐km
Autres résumés
Type: Publisher
(spa)
Evaluación de la concordancia entre la riqueza de especies pronosticada, priorizaciones pasadas y la designación de áreas marinas protegidas en el oeste del Océano Índico Resumen Los avances científicos en la cobertura de datos ambientales y los algoritmos de aprendizaje automatizado han mejorado la capacidad de predecir a gran escala cuando hacen falta datos. Estos avances nos permiten desarrollar un representante con resolución espacial para predecir la cantidad de taxones marinos en las costas tropicales. Usamos una base de datos espaciales de diversos ambientes marinos para modelar la cantidad de taxones a partir de ∼1000 sitios de campo y aplicamos las predicciones a las 7039 celdas arrecifales de 6.25‐km
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
e14256Subventions
Organisme : Supporting the Policy Enabling Environment for Development (USAID SPEED)
Organisme : U.S. Department of the Interior's International Technical Assistance Program
Organisme : U.S. Agency for International Development
Informations de copyright
© 2024 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.
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