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AI for Conservation / Feed

Artificial intelligence is increasingly being used in the field to analyse information collected by wildlife conservationists, from camera trap and satellite images to audio recordings. AI can learn how to identify which photos out of thousands contain rare species; or pinpoint an animal call out of hours of field recordings - hugely reducing the manual labour required to collect vital conservation data.

discussion

Move BON Development: Follow up discussion

Lacey Hughey

19 June 2024 12:02pm

Hey Biologging Community! We just launched a new initiative to mobilize animal tracking data in support of national and global scale conservation goals (learn more here!). If you...

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Akiba

12 July 2024 5:38am

Hi Talia! 

I feel like the topic is so broad that it might help to put some constraints around things, see what works, and then broaden those out. I have a lot of ideas regarding the data monitoring and collection side based on the other sensor and observation networks we've set up in the past. 

There may also be some potential scope to incorporate things like data collection and integrated monitoring to the Build Your Own Datalogger series where the system is updated to feed data into the observation network. 

It'd probably take a bit of discussion and coordination. Let me know if interested. I'm fine to jump on a call or discuss via email too.

CathyNj

22 July 2024 9:24pm

@cmwainaina please take a look

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Link

Rapid Camera Trap labeling with ChatGPT

Sara Olsson

17 July 2024 3:02pm

Hi all, I've published a blog post on rapidly labeling camera trap data using ChatGPT for species identification and a simple object detection model to get the bounding boxes. While presented in Edge Impulse, this approach can be replicated outside the platform using Python...

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event

ForestSAT

Elsa Carla De Grandi

5 July 2024 7:04pm

Seeing the forest and the trees: Promoting the application of spatial technologies for forest observation and analysis

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Elsa Carla De Grandi

3 September 2024 6:02pm

Happy to announce that the event will be recorded! Although unfortunately access to recordings will not be free.By registering you will gain access to all session and workshop...
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discussion

Question About Interpolation

Raul Castillo

18 June 2024 10:52pm

Hello! I am a Computer Science Student experimenting with the multi-step models on TensorFlow's "Time series forecasting" tutorial.I am applying to the models the positional data...

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Larry O'Brien

28 June 2024 6:35pm

The use of synthetic training data such as interpolated sequence values is common, but fraught with the issue of your synthetic signal generating features that are not true to real life. 

Instead, you might think about about appending the values of two long-period sin waves per input element to the sequence going in to your first linear / fully-connected layer. The simplest thing that could possibly work would be to interpret minute of the day and day of the month as the values of your sin wave! (Or perhaps minute/hour if all training sequences are quite short.) Since you’re doing sequence prediction, you would add the appropriate values for each image(?) in the sequence being evaluated.   

With that additional signal going in to the model in the early layers, the NN should have a good chance of learning that the differences in the modulating signal corresponds to distance in time. 

This technigue was popularized by early Large Language Models to encode the distance between words. There’s been refinement (search “Rotary Encoding” for instance) but the basic idea of sin waves generalizes well.

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discussion

Conservation Technology for Human-Wildlife Conflict in Non-Protected Areas: Advice on Generating Evidence

Amit Kaushik

22 January 2024 11:36pm

Hello,I am interested in human-dominated landscapes around protected areas. In my case study, the local community does not get compensation because they are unable to provide...

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Chavoux Luyt

4 February 2024 8:16am

Hi Amit,

The most important thing is that the livestock owners contact you as soon as possible after finding the carcass. We commonly do two things if they contact us on the same day or just after the livestock was killed:

  1. Use CyberTracker (or similar software) on an Android smart phone to record all tracks, bite marks, feeding pattern and any other relevant signs of the reason for the loss with pictures and GPS coordinates. [BTW, Compensation is a big issue -- What do you do if the livestock was stolen? What do you do if a domestic animal killed the livestock? What if it died from disease or natural causes and was scavenged upon by carnivores afterwards?]
  2. In the case of most cats, they would hide the prey (or just mark it by covering it with grass or branches and urinating in the area). In this case you can put up a camera trap on the carcass to capture the animal when it returns to its kill (Reconyx is good if you can afford it - we use mostly Cuddeback with white flash). This will normally only work if the carcass is fresh (so other predators would not be able to smell it and not know where it is yet), so the camera only has to be up for 3-5 days max.

This is not really high-tech, but can be very useful to not only establish which predator was responsible (or if a predator was responsible), but also to record all the evidence for that.

Aaron Kennedy

13 June 2024 8:58pm

Hey Amit, 

This is a great question; from our work, we've seen people do a couple of things. We've even seen people using Ring doorbell footage in urban areas as evidence. 

The best thing we've seen is matching the community needs with existing infrastructure: 

  • Are there existing cameras you can leverage, like the doorbell cameras? 
  • Can public participation monitoring service this, i.e. public submitted photos and videos? 

It also totally depends on the wildlife species you're working with, the interaction, damages, etc. If you've found any good solutions, let me know. I'd love to share that information with our clients here who have constant bear problems. 

 

Kim Hendrikse

14 June 2024 9:09am

In that case, you might want to keep an eye on the project from @Lars_Holst_Hansen 



 

Read "I have been working hard on this camera based polar bear alarm with Kim… | Lars Holst Hansen | 17 comments" on

I have been working hard on this camera based polar bear alarm with Kim… | Lars Holst Hansen | 17 comments

I have been working hard on this camera based polar bear alarm with Kim Hendrikse and other collaborators including Zoologisk Have in Copenhagen - where the system is now beeing tested. I hope to field test it at Zackenberg Research Station next year. | 17 comments on LinkedIn

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discussion

AI Identification Models on Thermal Data

Siddhi Singh

6 June 2024 8:30pm

Hello, my name is Siddhi. I recently joined WildLabs and getting to know different groups. I hope that this is the right place to post! I am interested in AI to identify...

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Siddhi Singh

7 June 2024 4:06am

Wow! This dataset seems great and definitely worth trying out. Do you perhaps have a dataset for deer, elk, and those animals of the sort? 
I live in the mountainous region so deer are very common and easily hit. 

Thank you again

Dan Morris

7 June 2024 5:43pm

Sorry, the only other dataset of thermal camera trap images that I'm aware of is mostly elephants, although it does have some goats:

https://github.com/arribada/human-wildlife-conflict?tab=readme-ov-file#elephant-dataset

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discussion

VIHAR-2024 deadline extension, June 30th (Interspeech satellite event) 

Marius Miron

5 June 2024 10:30am

Dear Wildlabs community,The submission deadline for VIHAR-2024 has been extended to June 30th, 2024. VIHAR-2024 (https://vihar-2024.vihar.org) is the fourth international...

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Alex Rood

5 June 2024 3:05pm

Thanks for sharing this @nkundiushuti ! I think this post would be better suited as an event, that way it will show up on the WILDLABS event calendar page. Let me know if you have any questions on how to make an event post! You just click the +Post button in the top right corner, then click "event."

Marius Miron

7 June 2024 8:29am

hi Alex!! I already posted the event, I just wanted to posted an update: the deadline was extended. 

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article

New WILDLABS Funding & Finance group

Frank van der Most

5 June 2024 3:24pm

WildLabs will soon launch a 'Funding and Finance' group. What would be your wish list for such a group? Would you be interested in co-managing or otherwise helping out?

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Alex Rood

5 June 2024 4:14pm

This is great, Frank! @StephODonnell, maybe we can try to bring someone from #Superorganism (@tomquigley ?) or another venture company (#XPRIZE) into the fold!
Paul Edonga

6 June 2024 1:38am

I find the group to be dope, fundraising in the realm of conservation has been tough especially for emerging conservation leaders. There are no centralized grants tracking common...
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event

Bioacoustics and AI 101

Vanesa Reyes

29 May 2024 2:21pm

Recent developments in AI have not only led to dramatic increase in accuracy of detecting/classifying sounds, but have simultaneously made these tools accessible for people with little to no prior knowledge of AI. This...

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event

5th World Ecoacoustics Congress

Vanesa Reyes

28 May 2024 8:07pm

In 2024, the 5th WEC, which will be held from 8th to 12th July in Madrid, will aim to bring together cutting-edge researchers and the international scientific community around this emerging field. During five days, we...

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DeepDive: estimating global biodiversity patterns through time using deep learning

Alex Rood

20 May 2024 4:51pm

These authors "develop an approach based on stochastic simulations of biodiversity and a deep learning model to infer richness at global or regional scales through time while incorporating spatial, temporal and taxonomic sampling variation."

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Read "DeepDive: estimating global biodiversity patterns through time using deep learning | Nature Communications" on Nature

DeepDive: estimating global biodiversity patterns through time using deep learning | Nature Communications

Understanding how biodiversity has changed through time is a central goal of evolutionary biology. However, estimates of past biodiversity are challenged by the inherent incompleteness of the fossil record, even when state-of-the-art statistical methods are applied to adjust estimates while correcting for sampling biases. Here we develop an approach based on stochastic simulations of biodiversity and a deep learning model to infer richness at global or regional scales through time while incorporating spatial, temporal and taxonomic sampling variation. Our method outperforms alternative approaches across simulated datasets, especially at large spatial scales, providing robust palaeodiversity estimates under a wide range of preservation scenarios. We apply our method on two empirical datasets of different taxonomic and temporal scope: the Permian-Triassic record of marine animals and the Cenozoic evolution of proboscideans. Our estimates provide a revised quantitative assessment of two mass extinctions in the marine record and reveal rapid diversification of proboscideans following their expansion out of Africa and a >70% diversity drop in the Pleistocene. Estimates of palaeodiversity are biased by the incompleteness of the fossil record. Here, the authors develop DeepDive, a deep learning approach that infers richness while accounting for record heterogeneity, and test it with two empirical datasets.

Nature