@elaterite Woah. I'm amazed the roots are strong enough to hold those trees up. Impressive!

@animalculum Cool study. Thanks for sharing.

@ricci Interesting. That works too, although I had to look up Brooklyn, NZ I see it's a suburb of Wellington city. (I need to spend more time exploring Wellington.)

@ricci Cool tool!

I took the numbers for the mastodon.nz server I'm on and did some calculations inspired by your tool. If mastodon.social is the equivalent of Shanghai, the world's biggest city, then mastodon.nz would be ~63k, between the New Plymouth and Napier. Those are both excellent NZ cities, although both much smaller than Auckland. That's not necessarily a bad thing. It does underscore how much more colossal mastodon.social is though.

@Rachelburch Impressive. We've got Taxus baccata growing here in NZ but I've never seen one remotely this big.

Then again, it was only 176 years ago that English colonists, and their garden plants, settled in Christchurch city, where I live. Our yew trees clearly have a lot more growing to do.

@Rachelburch Woah. That's a colossal yew tree. Any idea how old it is?

@sohkamyung @98Percent Yes, weka and kea, both, are like NZ’s equivalents of raccoons. All are smart and mischievous.

@miki Thanks. Yes, it’s all the hoovering up of training data sets without permission by the big LLM products that I object to (plus the massive power consumption needed to build and refine the models). The tech behind the models is pretty neat.

@spacefinner The Department of Conservation AR4s use four AA batteries and can easily run longer than a week, although we program them to record at lower frequency at night to save power (since the nocturnal birds in NZ don’t sing at such high frequencies). I use the three AA battery case for the AudioMoths, which runs for about two weeks (although only with lower power microSD cards).

@tillmanreuter We use NZ Department of Conservation manufactured AR4s, which come in excellent weather proofed cases, plus we’ve got a set of AudioMoths plugged into better microphones (the same that the AR4s use).

As much as I loathe LLM "AI" built from hoards of stolen data, machine learning "AI" has become terrifically useful.

This past week I had 10 audio recorders set out in the forest and nearby grassland, all recording non-stop from Monday afternoon to Friday morning. That was on our recent university field ecology field trip.

Today I downloaded all the files to a hard drive (156 GB of data) and then I set my little M1 Macbook Air to work, using the offline desktop BirdNet app to identify all of the birds in the recordings.

It took most of the day, and now I have a 42,284 row spreadsheet of birds detected.

It really feels like magic.

Here's a quick sorted lists of all the bird detections with species IDs with a confidence score >0.9.

Together with the students in the course, we'll later compare how birds have changed since we started doing this in 2020, and how the birds in the grassland differ from the forest.

#birds #BirdNet #ecology #nz #MachineLearning