Ecoacoustics For Conservation Workshop 2020

11-12 February 2020, QUT, Brisbane, Australia

Organisers: Susan Fuller and Paul Roe, QUT

Large areas of Australia are experiencing sustained anthropogenic pressure, environmental degradation and biodiversity loss. Increased threats from habitat loss and fragmentation, pollution, human-wildlife conflict, invasive species, climate change, etc, are leading to increased species endangerment and loss of ecosystem structure and function. As a result, monitoring of ecosystem health and biodiversity across temporal and spatial scales is a critical priority. Innovations in ecoacoustic technology and big data analysis approaches have the potential to address this challenge and deliver conservation outcomes.

Ecoacoustics can be applied in all types of terrestrial and aquatic (freshwater and marine) ecosystems and to questions relevant to individual species, populations, or species assemblages across landscapes.  The aim of this workshop is to explore current and future research opportunities in ecoacoustics with a focus on ecological applications in conservation. The primary focus is on terrestrial monitoring of audible fauna.

The goal of the first day’s workshop is to investigate how we might bring together interested parties to address the open challenges and opportunities of ecoacoustic monitoring for conservation.  The second day is a tutorial on using the open source sound analysis tools developed at QUT, including acoustic indices.

Attendance cost is $65 including GST. If you would like to attend please pay here.

Note: The workshop is open to all with a focus on real world applications; however, talks are by invitation only.

Location: The workshop will be held in D Block, QUT Gardens Point Campus, Brisbane

Venue map

The program (subject to change) is displayed below:

Day1: Tuesday 11th Feb

Opportunities and Challenges of Acoustic Monitoring

Room D101

8:00-9:00 Registration and Coffee
9:00-9:10 Welcome – Prof Kerrie Wilson (IFE Director)
9:10-9:30 Introduction – Paul and Susan
9:30-10:30 Talks – Targeted Monitoring of Threatened Species
10:30-11:00 Coffee Break
11:00-12:00 Talks – Targeted Monitoring, Species Assemblages & Ecosystem Health
12:00-1:00 Lunch (provided)
1:00-3:00 Facilitated workshop to identify common challenges and opportunities:

break into groups & come together

3:00-3:30 Coffee break
3:30-4:30 Hub or centre proposal to address challenges
4:30-5:00 Wrap up & next steps
6:30~ Dinner – location at Southbank TBA

 

Day 2: Wednesday 12th Feb

Sound Analysis using QUT Ecoacoustic Tools

Rooms D101 & D301

This workshop will present a practical approach to using the QUT ecoacoustics tools to analyse environmental recordings. The workshop is targeted at users who are interested in understanding the different approaches to analysing sound data, and how to use the QUT ecoacoustics tools. Ideally participants should have some familiarity with R and using a computer from the command line. The workshop will start at the beginning and it will cover the basics of sound, sound recording, sound file manipulation and sound analysis. A hands on approach will be taken, with participants analysing sound from the Australian Acoustic Observatory. All the tools and data used will be open source including the QUT analysis tools. Participants need to bring their own laptop.

8:00-9:00 Registration and Coffee
9:00-10:30 Session 1Sound Basics
The nature of sound

sound recording and recorders

sound representation (files, formats and manipulation)

Playing sound and basic effects and analysis (filtering, plotting etc.)

10:30-11:00 Coffee Break
11:00-12:30 Session 2Analytical Approaches
  Fauna sounds (calls, songs and soundscapes)

machine learning overview

supervised and unsupervised approaches

indices

deep learning

clustering approaches

12:30-1:30 Lunch (provided)
1:30-3:00 Session 3Indices and QUT Analysis Programs
Different indices and scales

false colour spectrograms

machine learning and indices (Weka)

3:00-3:30 Coffee break
3:30-5:00 Session 4 – Build your own recogniser using indices

 

Proudly supported by QUT

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