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Releases: ear-team/HAUPERT_MEE_2022

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

20 Oct 10:40
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This repository contains data and functions in 'R' that were used to process the data and create figures of the publication :
Haupert et. al, 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 in Methods in Ecology and Evolution

The authors are: Sylvain Haupert, Frédéric Sèbe & Jérôme Sueur

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

10 Oct 12:15
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This repository contains all the functions in 'R' that were used to process the data and create figures of the publication Haupert et. al. 2022, Methods in Ecology and Evolution