With new technologies revolutionizing data collection, wildlife researchers are becoming increasingly able to collect data at much higher volumes than ever before. Now we are facing the challenges of putting this information to use, bringing the science of big data into the conservation arena. With the help of machine learning tools, this area holds immense potential for conservation practices. The applications range from online trafficking alerts to species-specific early warning systems to efficient movement and biodiversity monitoring and beyond.
However, the process of building effective machine learning tools depends upon large amounts of standardized training data, and conservationists currently lack an established system for standardization. How to best develop such a system and incentivize data sharing are questions at the forefront of this work. There are currently multiple AI-based conservation initiatives, including Wildlife Insights and WildBook, that are pioneering applications on this front.
This group is the perfect place to ask all your AI-related questions, no matter your skill level or previous familiarity! You'll find resources, meet other members with similar questions and experts who can answer them, and engage in exciting collaborative opportunities together. The AI for Conservation group provides a dedicated space to:
- Bridge disciplines: Create a space where ecologists, conservationists and environmental scientists can connect with computer scientists, artificial intelligence researchers and practitioners to address shared challenges.
- Advance knowledge: Share and discuss research, case studies and best practices at the intersection of artificial intelligence and conservation.
- Education: Provide educational resources that help ecologists understand AI methods and their use cases and inspire AI experts to learn about ecological applications.
- Facilitate collaboration: Offer resources and networking opportunities that enable AI researchers and conservation practitioners to co-develop solutions with real-world conservation impact.
Just getting started with AI in conservation? Check out our introduction tutorial, How Do I Train My First Machine Learning Model? with Daniel Situnayake, and our Virtual Meetup on Big Data. If you're coming from the more technical side of AI/ML, Sara Beery runs an AI for Conservation slack channel that might be of interest. Message her for an invite.
Header Image: Dr Claire Burke / @CBurkeSci
Explore the Basics: AI
Understanding the possibilities for incorporating new technology into your work can feel overwhelming. With so many tools available, so many resources to keep up with, and so many innovative projects happening around the world and in our community, it's easy to lose sight of how and why these new technologies matter, and how they can be practically applied to your projects.
Machine learning has huge potential in conservation tech, and its applications are growing every day! But the tradeoff of that potential is a big learning curve - or so it seems to those starting out with this powerful tool!
To help you explore the potential of AI (and prepare for some of our upcoming AI-themed events!), we've compiled simple, key resources, conversations, and videos to highlight the possibilities:
Three Resources for Beginners:
- Everything I know about Machine Learning and Camera Traps, Dan Morris | Resource library, camera traps, machine learning
- Using Computer Vision to Protect Endangered Species, Kasim Rafiq | Machine learning, data analysis, big cats
- Resource: WildID | WildID
Three Forum Threads for Beginners:
- I made an open-source tool to help you sort camera trap images | Petar Gyurov, Camera Traps
- Batch / Automated Cloud Processing | Chris Nicolas, Acoustic Monitoring
- Looking for help with camera trapping for Jaguars: Software for species ID and database building | Carmina Gutierrez, AI for Conservation
Three Tutorials for Beginners:
- How do I get started using machine learning for my camera traps? | Sara Beery, Tech Tutors
- How do I train my first machine learning model? | Daniel Situnayake, Tech Tutors
- Big Data in Conservation | Dave Thau, Dan Morris, Sarah Davidson, Virtual Meetups
Want to know more about AI, or have your specific machine learning questions answered by experts in the WILDLABS community? Make sure you join the conversation in our AI for Conservation group!
Group curators
- @annavallery
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Seabird biologist experienced in research and applied conservation. Dedicated to conducting and using innovative research to inform conservation decisions.


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- @ViktorDo
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PhD student at University of Exeter & University of Queensland. Interested in researching AI and its responsible application to Ecology, Environmental Monitoring and Nature Conservation.

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No showcases have been added to this group yet.
Bsc in IoT Networks |MSc student in Advanced Engineering for Robotics & AI. AI projects on camera traps and edge bioacoustics for bird mapping. Open Source Contributor to Microsoft Camera Trap project. Nat Geo & Nature Conservancy marine conservation externship alumnus.



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R & D Tech | Industrial Designer | Wildlife Management Technology



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- @kenadyWilson
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Sea Mammal Research Unit Univ' St Andrews
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- @Riley
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I'm a Data Scientist at Western EcoSystems Technology. I am interested in AI processing and statistical modeling of acoustic data and camera trap and drone imagery.

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- @corrina.copp
- | She/her
Alberta Biodiversity Monitoring Institute (ABMI)
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- @JRousseau
- | She/Her
I am a Wildlife Ecologist at Point Blue Conservation Science. I am passionate about conservation, whether at the local community or larger scale, and enjoy analyzing data to uncover patterns in wildlife populations that can inform conservation strategies.
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- @fsanger
- | she / her/ ella
I specialize in conservation geography, using GIS, remote sensing, acoustics, and landscape ecology to study climate and land cover change impacts on biodiversity and ecosytems. I'm a professor at Clark University, and member of the XPRIZE Rainforest winning team ETH BiodivX.
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- @Mumonkan
- | he / him
Conservation X Labs & Wild Me
Software Engineer for Wildlife Conservation

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- 12 Groups
- @Dauson_M
- | Mr
Dauson Msumange is a social enterpreneur, founder and director of Tanzania Eco-Tech And Conservation Hub (TEACH).

- 0 Resources
- 1 Discussions
- 23 Groups
- @Nigel
- | He /Him
Nigel Ndlovu is a youthful leader, media entrepreneur and sustainability advocate from Bulawayo, Zimbabwe.An innovative eco conservationist..
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Ol Pejeta Conservancy
Endeavoring to implement tech solutions for conservation.



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El Instituto Humboldt está buscando un(a) Desarrollador(a) de Inteligencia Artificial que quiera aplicar su experiencia en Python y procesamiento de lenguaje natural para proteger la biodiversidad.
25 July 2025
The Marine Innovation Lab for Leading-edge Oceanography develops hardware and software to expand the ocean observing network and for the sustainable management of natural resources. For Fall 2026, we are actively...
24 July 2025
Dear colleagues, I'd like to share with you the output of the project KIEBIDS, which focused on using AI to extract biodiversity-relevant information from museum labels. Perhaps it can be applied also to other written...
17 July 2025
The Department of AI and Society (AIS) at the University at Buffalo (UB) invites candidates to apply for multiple positions as Assistant Professor, Associate Professor, or Full Professor. The new AIS department was...
8 July 2025
This is a chance to participate in a short survey about the preferences that conservation practitioners have for evidence. There's a chance to win one of three £20 Mastercard gift cards.
24 June 2025
In this case, you’ll explore how the BoutScout project is improving avian behavioural research through deep learning—without relying on images or video. By combining dataloggers, open-source hardware, and a powerful...
24 June 2025
Using Ultra-High-Resolution Drone Imagery and Deep Learning to quantify the impact of avian influenza on northern gannet colony of Bass Rock, Scotland. Would love to hear if you know of any other similar exaples from...
12 June 2025
La Universidad de Ingeniería y Tecnología (UTEC) está buscando cubrir nuevas vacantes en su Instituto Amazónico de Investigación para la Sostenibilidad (ASRI).
12 June 2025
Shared from WWF: "ManglarIA is a mangrove conservation project, supported by Google.org in 2023, that is deploying advanced technology, including artificial intelligence (AI), to collect and analyze data on the health...
12 June 2025
Careers
Rewilding Europe is seeking a Business Intelligence Analyst to support measuring rewilding impact through data automation, dashboards, and cross-domain analysis.
3 June 2025
The intern will support CI in exploring and implementing AI solutions that address conservation challenges. We are looking for someone familiar with modern AI technologies (genAI, AI agents, LLMs, foundation models, etc...
2 June 2025
HawkEars is a deep learning model designed specifically to recognize the calls of 328 Canadian bird species and 13 amphibians.
13 May 2025
September 2025
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Description | Activity | Replies | Groups | Updated |
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Interesting. Thanks for the explanation. Nice to hear your passion showing through. |
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AI for Conservation, Camera Traps, Data Management & Mobilisation, Open Source Solutions, Software Development | 4 months ago | |
📸 Do you use camera traps in your work? Take part in our survey!Hi everyone! I’m currently a final-year engineering... |
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Camera Traps, AI for Conservation, Data Management & Mobilisation, Open Source Solutions, Software Development | 4 months ago | |
WILDLABS colleagues—My team at TNC is looking for support as we try to understand opportunities of AI applications for freshwater (eco)... |
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AI for Conservation | 4 months 1 week ago | |
Hi Adam! Sounds like you have your work cut out for you. I have not used radar systems or AI systems for this sort of detection, but there are methods using change detection... |
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AI for Conservation, Drones, Wildlife Crime | 4 months 1 week ago | |
Hey Amber, that makes a lot of sense! And this effort by Insect Detect is amazing, thanks for sharing! |
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AI for Conservation, Autonomous Camera Traps for Insects | 4 months 1 week ago | |
One of our goals with explorer.land is to bridge satellite data and on-the-ground perspectives — helping teams combine field updates,... |
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AI for Conservation, Geospatial, Open Source Solutions, Sensors | 4 months 2 weeks ago | |
Hi, just wanted to let whoever is interested that v.1.3 of DeepFaune is out! Deepfaune is a software that runs on any standard... |
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Camera Traps, AI for Conservation, Open Source Solutions | 4 months 2 weeks ago | |
New stable release : v1.5.1We are pleased to announce the latest release with several important enhancement, fixes and documentation improvements to ensure compatibility with the... |
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Acoustics, AI for Conservation, Open Source Solutions, Software Development | 4 months 2 weeks ago | |
Hi all, I'm Vainqueur BULAMBO. I'm looking for a fully funded PhD opportunity in ecological data science or conservation... |
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Acoustics, AI for Conservation, Autonomous Camera Traps for Insects | 4 months 3 weeks ago | |
A nice work from @dmorris! See his LK post. "Lots of information in the conservation literature is represented in maps (e.g., the... |
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AI for Conservation, Geospatial | 4 months 4 weeks ago | |
Hi all, I'm the founder of a company in Texas that provides thermal drone surveying for private game ranches. Right now, we're doing everything completely manually in terms of... |
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AI for Conservation | 4 months 4 weeks ago | |
Really looking forward to following this project. I'm very curious how you'll be able to tease out different species, particularly among species that feature a variety of worker... |
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Acoustics, AI for Conservation | 5 months 1 week ago |
No-code custom AI for camera trap images!
25 April 2025 8:33pm
28 April 2025 3:57pm
We do, but the way the models handle the images differs depending on whether they're coming from videos or static images. A quick example: videos provide movement information, which can a way of distinguishing between species. We use an implementation of SlowFast for one of our video models that attempts to extract temporal information at different frequencies. If the model has some concept of "these images are time sequenced" it can extract that movement information, whereas if it's a straight image model, that concept doesn't have a place to live. But a straight image model can use more of its capacity for learning e.g. fur patterns, so it can perform better on single images. We did some experimentation along these lines and did find that models trained specifically for images outperformed video models run on single images.
Hope that helps clear up the confusion. Happy to go on and on (and on)...
28 April 2025 5:58pm
Interesting. Thanks for the explanation. Nice to hear your passion showing through.
Overview of Image Analysis and Visualization from Camera traps
28 April 2025 8:09am
RFP: AI + freshwater biodiversity
23 April 2025 5:47pm
Drone & ai use for uncovering illegal logging camps
21 April 2025 4:49am
21 April 2025 12:49pm
Hi Adam!
Sounds like you have your work cut out for you. I have not used radar systems or AI systems for this sort of detection, but there are methods using change detection models to visualise changes in forests where logging may be occuring between different dates using drone photogrammetry and GIS software. I have found these methods very effective when monitoring deforestation, especially because not only can you quickly visualise where deforestation has happened, but you can also quantify the damage at the same time. Let me know if you would like to learn more.
Kind regards
Sean Hill
WILDLABS AWARDS 2024 - Enhancing Pollinator Conservation through Deep NeuralNetwork Development
7 April 2024 5:55pm
18 April 2025 10:33pm
Hi Kim,
That's really interesting! I didn't realize thermal worked with bees! Thanks so much for sharing that detail.
Liz
19 April 2025 12:40pm
Great work! Do you think the night time models also worked better due to lack of interference from shadows being counted? or maybe issues around a non-standard background.
If it helps, I believe the creators of InsectDetect which is open source, did a lot of work training their model to differentiate insect shadows vs. insects. Also after testing their smart trap on flowers, went with a standardised, non-lethal attractive background.
InsectDetect: Build your own insect-detecting camera trap!

20 April 2025 5:14pm
Hey Amber, that makes a lot of sense! And this effort by Insect Detect is amazing, thanks for sharing!
Global Science Data Management and AI Graduate Intern
18 April 2025 2:52pm
Ground Truth: How Are You Verifying What Maps Show?

16 April 2025 3:35pm
DeepFaune v.1.3 is out!
14 April 2025 3:50pm
scikit-maad community
8 August 2024 10:16am
19 February 2025 10:26am
Hello!
I could be wrong, but from looking at the source code of the ACI calculation on the scikit-maad it appears that it autosets j = length of signal. If you want to break it down to e.g. 5 windows you can break the spectrogram into 5 chunks along time and then sum the ACI in each window. This gives a more similar result to the results you got using the other methods. What did you set as nbwindows for seewave?
s, fs = maad.sound.load('test_data_ACI/LINE_2003-10-30_20_00_34.wav')
Sxx, tn, fn, ext = maad.sound.spectrogram (s, fs, mode='amplitude')
full_time = Sxx.shape[1] # number of time samples in spectrogram
j_count = 5 # number of chunks we want to break it into
window_size = np.floor(full_time/j_count) # total time divided by number of chunks = number of time samples per chunk
ACI_tot = 0
for i in range(j_count):
_, _ , ACI = maad.features.acoustic_complexity_index(Sxx[:,int(i*window_size):int(i*window_size+window_size)])
ACI_tot = ACI_tot + int(ACI)
This gives ACI_tot = 1516
6 March 2025 11:07am
Hi all,
I have recently been utilising the ROI module of scikit-maad to locate non-biophonic sounds across low-sample rate Arctic hydrophone datasets and have a query about how ROI centroids are calculated...
Looking at the source code for the function "centroid_features" in .\maad\features\shape.py, I can see that the function calls "center_of_mass" from .\scipy\ndimage\_measurements.py. This to me suggests that the centroid should be placed where energy is focussed, i.e. the middle of the acoustic signature captured by the masking stage of ROI computations.
I'm a bit confused as to why the centroids I have appear to be more or less placed in the centre of the computed ROIs, regardless of the energy distribution within the ROI. The sounds I'm capturing have energy focussed towards lower frequencies of the ROI bands, so I would have expected the centroid to shift downwards as well.
Has anyone modified how ROI centroids are defined in their work? I'd be quite interested to set up centroids to signify where the peak energy level lies in the ROI, but I'm not quite sure how to do this cleanly.
Any advice would be greatly appreciated, thanks!
Kind regards,
Jonathan
11 April 2025 10:08pm
We are pleased to announce the latest release with several important enhancement, fixes and documentation improvements to ensure compatibility with the latest versions of SciPy and scikit-image as well as with Xeno-Canto.
In this new version, 2 new alpha indices are implemented, aROI and nROI, the latter being a good proxy of the average species richness per 1 min soundscape.
Application of computer vision for off-highway vehicle route detection: A case study in Mojave desert tortoise habitat
8 April 2025 2:30pm
22 April 2025 11:05pm
22 April 2025 11:05pm
24 April 2025 9:24am
Looking for PhD position
6 April 2025 6:12am
Ecology Georeferencing - A dataset
4 April 2025 2:59pm
Has anyone combined flying drone surveys with AI for counting wild herds?
14 April 2024 3:40pm
31 May 2024 5:47pm
Hi Johnathan,
There is a Canadian company more or less doing that. They have their own endurance drone and optical/thermal cameras. Very much keyed into surveys and they may have success given the number of helicopter accidents we have had in Western Canada. Not sure if the AI part is there yet.
I know they've done surveys with at least one department here but not much beyond that. I talked to one of the developers their just as a point of interest. The current leadership today looks different than I remember though.
Superwake
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6 June 2024 2:48pm
The camera can be aimed at the greenhouse background, which is like a huge green screen. Inside the greenhouse there's only a few flying insects, and they would all have to fly between the optics and the wall or roof eventually. Or if the bot is flying, have it look upwards.
It's pretty much a programing question. Unfortunately I am not the type of person who is good at both building and troubleshooting hardware, and writing code. I took some programming back in college but I am not sure if I want to get myself up to speed. It's starting to sound like I need a few years of college before I can even get started. Which I already did, too bad none of it counts for anything anymore. Or I guess I can compete in the marketplace with people with real money behind them, which is the only thing that means anything. If you are brilliant and not funded, you might as well be a scarecrow.
3 April 2025 12:53am
Hi all, I'm the founder of a company in Texas that provides thermal drone surveying for private game ranches. Right now, we're doing everything completely manually in terms of counting during both the initial flight as well as the review. Automating our process with an AI program would be great, but there are multiple limitations I'd imagine:
1.) Thermal imaging has pretty poor resolution even when you're only 100 feet or so above the ground. We'll often need to bring the drone down even closer to identify a buck vs doe. I'd imagine an AI model would be even more limited by this poor resolution
2.) Using a visible zoom camera in tandem with the thermal can help with this issue, but then you are very limited. Thermal works great at night, but requires cool, cloudy days if you're wanting to fly in the daylight to use the optical camera. In Texas, these are few and far between.
3.) Even if you were to figure out everything else, there are often animals that rewuire a pilot to move the drone off its path in order to identify (for example if they're bedded down behind a tree we will often need to swing around to the other side.
If anyone is interested, we do record all of our surveys, so I have 1000+ hours of thermal footage of animals from whitetail deer to nilgai to zebra. I'd be happy to share this with someone who's interested in potentially building a model if they think they can solve the limitations.
Free Webinar by Nature FIRST: Bridging Ecology and ESG – Smarter Decisions with Knowledge Graphs
2 April 2025 10:59am
Nature Tech for Biodiversity Sector Map launched!
1 April 2025 1:41pm
4 April 2025 1:57pm
Desafio IA Natureza & Clima / AI Challenge: Nature & Climate
1 April 2025 12:54pm
Multiple grants
28 March 2025 1:42pm
WILDLABS AWARDS 2024 - BumbleBuzz: automatic recognition of bumblebee species and behaviour from their buzzing sounds
12 April 2024 8:37am
12 April 2024 8:41pm
Super great to see that there will be more work on insect ecoacoustics! So prevalent in practically every soundscape, but so often over-looked. Can't wait to follow this project as it develops!
17 April 2024 10:23am
Thanks Carly! I will keep anyone interested in this project posted on this platform. Cheers
26 March 2025 8:08pm
Really looking forward to following this project. I'm very curious how you'll be able to tease out different species, particularly among species that feature a variety of worker sizes.
Ai agents for conservation
26 March 2025 8:08pm
Nature Tech Unconference - Anyone attending?
8 March 2025 12:11pm
15 March 2025 8:28am
Definitely!
21 March 2025 12:07pm
The Futures Wild team will be there :)
26 March 2025 7:54pm
Yep see you on friday
Generative AI for simulating landscapes before and after restoration activities
26 March 2025 1:59pm
26 March 2025 7:50pm
Yep we are working on it
1/ segment
2/remote unwanted ecosytem
3/get local potential habitat
4/generate
5/add to picture
Cloud-Native Geospatial Conference
26 March 2025 3:40pm
2025 AI upskilling workshop for former US/state environmental scientists

25 March 2025 7:10pm
AI Weather Quest
25 March 2025 5:07pm
United Nations Open Source Principles
13 March 2025 4:13pm
25 March 2025 11:54am
All sound, would be nice if there were only 5, though!
InsectSet459: an open dataset of insect sounds for bioacoustic machine learning
24 March 2025 5:46pm
Postdoctoral fellow in AI for Ultrasonic Bioacoustic Monitoring
24 March 2025 3:31pm
Compute for Climate Fellowship 2025: Empowering Climate Tech Startups with Cloud Computing and AI
22 March 2025 4:13pm
Indigenous Groups Are Safeguarding Culture with Their Own ChatGPT | Atmos
21 March 2025 12:59pm
Subject: “Baa-bridge” – AI Sheep Stress Reduction, Seeking Genius Input!
20 February 2025 9:55pm
21 March 2025 12:18pm
I'm sure others here can comment better than I on models for classifying animal sounds, but from an ML pint of view, a key concern is getting enough data. 10 recordings does not sound like a lot (although how long are they?) and 1000 epochs does sound like a lot. It is very possible that your model is just learning to memorize the inputs, and that it will generalise poorly.
28 April 2025 7:03am
When you process videos, do you not first break them down into a sequence of images and then process the images ? I'm confused as to the distinction between the processing videos versus images here.