By this definition an eBird checklist is a digital twin #eBird

I feel like a larger-scale replication study of this important topic ("a good life for all within planetary boundaries") would be really empowering for my students. So I would be keen to hear from anyone who knows about useful resources or has done something similar in their classes! #DSLC

e.g., having students work as a class to collect soil samples or bioacoustic monitoring outputs, and then working on a multi-week field + #datascience lab report activity in groups (w/ #Python or #R) where there is a cleaned class dataset but each group has distinct hypotheses.

Even these simpler, faster, and smaller-scale exercises (e.g. can fit in one 75-minute class session) were really powerful for students who have these rich, multidisciplinary interests in the environment and living more humanely together. My larger-scale activities tho have often focused on #ecology

Specifically, have the students split into teams, and examine the underlying data in the citation trail that drives this powerful conclusion. I've done some similar (smaller scale) projects with sources such as goodlife.leeds.ac.uk/download-data/ or #ourworldindata.

Hehehe #budgie

Is this from The Great Derangement?

I like this vision. But how do we reconcile the tension between individual agency and collective good?

Lots of great fruit in the pawpaw’s Annonaceae family, including the (IMO) incomparable Taiwan atemoya! The pawpaw is unique as one of the only temperate members of this large, pan tropical family of delicious fruits (custard apples, soursop, and atemoya).

Fascinating! We saw a related pattern with an earlier “eXodus” for climate/environmental peeps, but at the time, there wasn’t yet widespread BSky adoption (due to the invite only mechanism you describe). IMO your profile matching approach is really cool; thanks for sharing!
doi.org/10.1016/j.tr...

Our essay was part of the 20th anniversary special issue for the Conservation Social Science Working Group. To see all of the great articles in this issue, please check out these links:
1️⃣ doi.org/10.1111/cobi... (OA link to our essay)
2️⃣ bit.ly/3RFqmYk
3️⃣ shorturl.at/USCbM (link to special issue)

Huge thanks to my incredible co-authors Susan Cook-Patton, @jterbaugh.bsky.social, Luci Lu, Yuta Masuda, @lexunit.bsky.social, @berobinson.bsky.social and funding from @pomonacollege.bsky.social, @bezosearthfund.org, & @nature.org. It's an exciting time to synthesize evidence for conservation! 🌎📊🔍

CRITICAL QUESTIONS REMAIN: How do we ensure ethical use of AI in conservation? How do we address English language bias? How do we validate AI-assisted findings? If you're interested in these questions, please get in touch with our team--we've got a new working group focused on this topic. 🧵: 4/6

Here's how ML + NLP can help:
1️⃣ Speed & scale up literature searches
2️⃣ Automate screening for relevance
3️⃣ Extract key information from studies
4️⃣ Process unstructured text data at scale
5️⃣ Identify patterns across thousands of papers
These tools can cut workload by 35-99%! ⚡️ 🧵: 3/6

Why does this matter? Conservation and climate science face HUGE challenges synthesizing evidence across different fields. The volume of research is growing exponentially, while disciplinary differences make it tough to integrate knowledge. Traditional manual review can't keep up! 🧵: 2/6