Hello, 

I am very interested in possibly contributing a paper for this issue, but I study waterbirds in Texas. Would this be open for review papers or meta-analysis? Or deployment of new tools?

Brilliant! We'll look into archiving here. Where we have labelled data with 100's of examples of each call for each species (Peruvian Primates mostly) is that something you are looking to host? or do you prefere a more curated submission?

That is splendid news! Thanks Willem-Pier!

Hi Lorenzo,

I highly recommend the OpenSoundscapes package (developed by the Kitzes Lab at U Pittsburgh) - there are workflows to build your own CNNs there, the documentation is really thorough, and the team are very responsive to inquiries. They also have a bioacoustics 'model zoo' that lists relevant models. The Perch model from Google would be good to look into as well.

Some recent papers I've seen that might also be worth checking out -

• Advanced montane bird monitoring using self-supervised learning and transformer on passive acoustic data
• A good horizon scan paper - The potential for AI to revolutionize conservation: a horizon scan
• Challenges and solutions for ecologists adopting AI
• And perhaps not directly related, but a new framework for deploying edge models onto recorders was just released - acoupi: An Open-Source Python Framework for Deploying Bioacoustic AI Models on Edge Devices

Hope that helps a bit!

Thank you so much for sharing! 
They seem to only state the official DFFE statistics nowadays. From my connections in SouthAfrica these numbers don't always seem to reflect the actual case anymore.
On the note of preventing illegal rhino horn trade, EMSfoundation recently published a comparison of the government's rhino horn stockpile over the past years. As it is shrinking, the question arises why they are not burnt?
The numbers lower partly due to theft but possibly also due to corruption.

Hi @craigg, my background is machine learning and deep neural networks, and I'm also actively involved with developing global geospatial ecological models, which I believe could be very useful for your PhD studies.  

First of all to your direct challenges, I think there will be many different approaches, which could serve more or less of your interests.

As one idea that came up, I think it will be possible in the coming months, through a collaboration, to "fine-tune" a general purpose "foundation model" for ecology that I'm developing with University of Florida and Stanford University researchers.  More here.

You may also find the 1+ million plant trait inferences searchable by native plant habitats at Ecodash.ai to be useful.  A collaborator at Stanford actually is from South Africa, and I was just about to send him this e.g. https://ecodash.ai/geo/za/06/johannesburg

I'm happy to chat about this, just reach out!  I think there could also be a big publication in Nature (or something nice) by mid-2025, with dozens of researchers demonstrating a large number of applications of the general AI techniques I linked to above.

We are putting together a special issue in the journal Ostrich: Journal of African Ornithology and are welcoming (review) papers on the use of AI in bird research. https://www.nisc.co.za/news/202/journals/call-for-papers-special-issue-on-ai-and-ornithology

Thanks for flagging! We might be interested to submit our work on acoustic monitoring system.

My company builds a thermal video recorder that's Pi based. In principle that means it should be fairly simple to get it to go to sleep and wake up again and record and then go back to sleep again with a minor customization. It can record video from a tiny thermal imaging camera. So I think it can do what you want. Please reach out if you think this fits your needs. Thermal imaging should provide the best night vision available, it would see as well at night as day. Usually better.

This video shows you how good the night vision is:

 

Hi Paula, you're right that WhatsApp strips EXIF metadata (including GPS data), which makes it tricky to collect location information when people share photos. Perhaps you could use Google Photos/Apple Photos. Both automatically embed location data in the images if the device’s location services are enabled when the photo is taken. Then, if users upload their images to one of these platforms, you can ask them to share the photo with a link (which will include the location).

Otherwise, do you know why people are reluctant to use iNaturalist? Seek has a simpler interface and could be a solution for those hesitant about using iNaturalist ?

Hope that helps, 

Cheers, 

Lucie