You can now add (for $20) an AI agent to your RStudio session…
Any support for non-profits @posit.co? This could help to speed up analyses in wildlife conservation.
Broadly agree, Zack, & really important to hold Starmer to account for his own words! But not sure I agree with the last sentence, at least on current evidence. It doesn’t seem to be the case that Starmer’s doing anything T wants, more that he’s playing the long game.
Although we have known this for many years—e.g. @neobirdconserve financed early work by Vitek Jirinek—this should have been the top news headline last week. These declines in 'pristine' tropical forests are well-documented, poorly understood and continue apace. www.science.org/content/arti...
I didn’t notice anywhere that it said it was AI, but also didn’t notice the name of an author either, which is a bit of a red flag
The oldest known wild Sunda clouded leopard is a 6.51-year-old female! Similar to the oldest known mainland leopard cat too.
Pretty neat what long-term camera trap studies can tell us.
onlinelibrary.wiley.com/doi/10.1111/...
Hi Laura, this write-up is AI generated I think? Just flagging this for others.
Yep I agree, SCR certainly not easy, but the statistical foundations are solid, and it’s easier than the ‘unmarked’ route (REM/REST etc.)! There’s no reason why it shouldn’t be being applied across lynx populations in Europe in a standardised way.
Interesting study, too, thanks for sharing!
Some argue protected areas in fire-prone landscapes can undermine forest carbon (fuel build-up → higher fire risk). This paper shows Spanish protected areas consistently outperform comparable unprotected lands, strongest in National Parks.
iopscience.iop.org/article/10.1...
Lynx (including Eurasian) are actually one of the “easier” ones, since you can identify individuals (unlike for, say, deer). Done with good survey design (and that doesn’t mean throwing a few cameras up and hoping for the best 🤓) and analysis, you can get an accurate & precise population estimate.
I don’t know what this is, but I am here for the team names
Essential reading for conservation scientists & ecologists (in fact anyone doing science across borders!) 🌍🧪https://onlinelibrary.wiley.com/doi/10.1111/ele.70227?af=R
Remote-control science is an internet-enabled form of "parachute" science
FWIW, I see a lot of this in AI and macroecology research
"Podemos vivir sin lobos (...) como estuvimos a punto de vivir sin linces, como posiblemente podamos vivir en pocos años sin urogallos, salmones y anguilas (...). Pero somos muchas las personas que no queremos vivir sin ellos"
Léete estoy de @ernestodmartin.bsky.social
elpais.com/clima-y-medi...
📣 NEW! I’ve just released the BIGGEST and perhaps most creative project I’ve ever worked on!
“Searching for Birds” searchingforbirds.visualcinnamon.com 🐤
A project, an article, an exploration that dives into the data that connects humans with birds, by looking at how we search for birds.
Oh that’s good 👏
February: “Even the land is tired. Most of the birds that can afford it have gone to Florida” 🤓
Would be interesting to compare the results on more recent models - but this problem won’t go away. LLMs are always going to be extrapolating from what has already, and often, been thought, which is why they aren’t windows to the future but anchors to the past.
And, bonus fact, it actually spells pretty good (unlike, say, cat pee!). A musky, sweet and sour smell.
In the dry climate of the Gobi (where our long-term study is), the smell doesn’t last as long as in the wet Himalayas, so it’s extra special when you find a strong scent mark - it must be fresh!
Ok, I will keep an eye out for future courses (in-person if possible)! And may I salute you for providing your physical book as an open online version, too 🫡 Everyone is able to learn more about these models, without needing to jump over a paywall oliviergimenez.github.io/banana-book/
Hi Olivier, looks very useful; will there be any training courses/workshops on the topics in the book?
This has been my experience too. When I run out of brainpower, I sometimes turn to LLMs. But then comes the endless back-and-forth with the thing to actually make the code work; I guess that’s the vibe coding part 🥺 I can’t imagine what this is doing to the skills of those newly learning coding…
The 10th Annual #Tech4Wildlife Challenge is starting soon!📸
Help us celebrate a decade of conservation technology by sharing how you use #Tech4Wildlife throughout next week.
Learn how to participate 👉 wildlabs.net/article/join...
#conservation #conservationtech #naturetech
Cool! Carnivores help mycorrhizal fungi to disperse.
Paper is here for those interested (although paywalled so I can’t actually read it): onlinelibrary.wiley.com/doi/10.1111/...
Coffee! ☕️ 🫘
For the UK: Kiss the Hippo has great credentials (direct sourcing, carbon neutral, organic) kissthehippo.com/pages/kiss-t...
For the Netherlands: Wakuli does some great work direct with suppliers www.wakuli.com/pages/mission
Ah I see. Yep monitoring is only useful when properly embedded in the conservation work and when communities (as in the link above ☝️), managers, everyone involved, is invested in it, and it has a very clear purpose in project design. Monitoring (and especially AI 😏) is not useful in and of itself.
Excuse me?
Love to see this: a women’s camera trapping group in the high mountains of Himachal Pradesh, western Himalaya. All power to them.
Exemplary data collection in the field shown as well, including proper testing of camera setup using “walk test” 😇
#cameratrap 🌏🧪
youtu.be/98Tigg7WXCg?...
Beautiful and incredible scenes from the centre of the Netherlands, a country with 1.5 times the density of people in the UK. A pack of 11 wolves roaming through the snow!
Alongside “AI colonialism”, the other big worry with this is that modelling results are never confronted with reality, they exist in some kind of desk-based bubble. All models are wrong, only some are useful. It’s by going out & touching the grass that we can sort the useful from the nonsensical.
~0.2 snow leopards over that area 😉
A landscape view of the rugged and barren Tost Mountains in the South Gobi, Mongolia. Taken using a drone at around sunset, the mountains have an orange-green hue, and the scene would not look out of place on Mars!
A drone’s-eye view of the South Gobi, Mongolia, at sunset. Home to our long-term study of snow leopards & the social-ecological system of ungulates, carnivores & livestock herders.
You might wonder if anything was living down there. But there are 20 snow leopards & 2000 ibex. Life finds a way! 🌏
