The second edition of EcoHacK will take place at the University of Stirling (Campus Central), 9th -11th October 2023.
With the advent of low-cost passive detectors and the recent development of new acoustic sampling methods, recording ecological sounds in the field has gained momentum amongst researchers and practitioners worldwide. Analysing sound recordings was traditionally done manually but quickly became too time-consuming a process. This has been overcome using automated methods; acoustic indices are used to summarise the sonic environment, and sound recognition algorithms based on machine learning can identify specific sounds of interest with high confidence. As these techniques are evolving rapidly, this workshop will provide an opportunity to work collaboratively on projects (similar to a hackathon format), learn, discuss, and exchange ideas on state-of-the-art methods in bio/eco acoustics.
The main objectives of EcoHacK are to:
- bring together students, early-career, postdoctoral and senior researchers as well as key stakeholders (e.g. charities and private sector bodies) interested in sound recognition, bio/eco acoustics, and soundscape ecology,
- foster links and collaboration between institutions and across disciplines, as well as encouraging dialogue between the academic and private sector,
- discuss, exchange, and share experiences and best practices in sound recording analysis,
- explore novel ways of linking acoustic data with environmental variables at different spatiotemporal scales.
Register here (https://docs.
There are two ways to participate to EcoHacK :
Propose a project idea at registration (see examples from last year here) and find your teammates during Day 1.
Join a project during Day 1.
All projects will be introduced during the “Project Pitch” session during Day 1, and on the afternoon on Day 3, all projects will present the work done during EcoHacK. Moreover, there will be opportunities to talk about any bio/ecoacoustic-related topics during lightning talks and a poster session.
Feel free to propose your own idea! All confirmed projects are listed below.
Examples of projects / themes :
Using ecoacoustic indices to characterize biodiversity in field recordings
Machine learning datasets and models for species identification using sound
Visualization of large ecoacoustics recordings databases
Statistics and machine learning in ecoacoustics
Work on specific datasets / research questions
Create a tutorial on specific methods / toolboxes / …
- Using BirdNet algorithm to classify pollinator buzzing sounds
- Investigating the impact of using different recorders (and potentially how to equalise differences)
- Extracting some inference or features from a bioacoustic dataset
- Challenge in identifying gibbon presence/behaviour from their vocalizations
- Exploring the effects of urbanization on birds and bats along an urban-rural gradient
- Developing an open source acoustic classifier for African and British bat species in R
- Improving the automatic recognition of songbirds in Doñana National Park
Dr Jeremy Froidevaux, University of Stirling, UK. Jeremy is a Leverhulme early-career research fellow at the University of Stirling, Scotland. He is a conservation biologist with broad interests in wildlife ecology and conservation. Using emergent bioacoustic methods, his research focuses on assessing the impacts of anthropogenic pressures on biodiversity, especially bats, birds, and recently bees.
Dr Nicolas Farrugia, IMT Atlantique, France. Nicolas is an assistant professor at IMT Atlantique, an elite technical university in France. His research interests include developing innovative methods to better understand Sounds and the Brain using modern machine learning and deep learning.
Dr Tom Bradfer-Lawrence, RSPB, UK. Tom is a Senior Conservation Scientist at RSPB. He is a landscape ecologist, interested in the conservation of biodiversity in human-modified landscapes. His work includes community ecology, ecoacoustics, and nature-based solutions to climate change.