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Sensory Cloud (United States)

United States

1 paper here56 citations across 1
fields
  • physics.soc-ph1
ROR 01vny5262OpenAlex

affiliations via OpenAlex

most citedPhysics-based model to predict the acoustic detection distance of terrestrial autonomous recording units over the diel cycle and across seasons: insights from an Alpine and a Neotropical forest

56 citations

researchers with a paper here
  • F. Sèbe1
  • J. Sueur1
  • S. Haupert1
collaborating institutions
  • Centre de Recherche en Neurosciences de LyonFR1 paper
  • Centre National de la Recherche ScientifiqueFR1 paper
  • InsermFR1 paper
  • Institut de Systématique, Évolution, BiodiversitéFR1 paper
  • Sorbonne UniversitéFR1 paper

1 paper

physics.soc-ph2022★ 56 cited

Physics-based model to predict the acoustic detection distance of terrestrial autonomous recording units over the diel cycle and across seasons: insights from an Alpine and a Neotropical forest

Sylvain Haupert, Frédéric Sèbe, Jérôme Sueur

1. Passive acoustic monitoring of biodiversity is growing fast, as it offers an alternative to traditional aural point count surveys, with the possibility to deploy long-term acous…

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