Andrea Zampetti
@andrewzampetti.bsky.social
2.2K followers 610 following 17 posts
PhD student @ Sapienza University 🇮🇹 🐒🐺🦌Conservation biology 📊 Ecological modeling 📸 Camera-traps 🤖 Leveraging AI to transform wildlife conservation 🐾 📖 https://www.researchgate.net/profile/Andrea-Zampetti-4
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andrewzampetti.bsky.social
Can AI improve #cameratrap studies?

Our study in @methodsinecoevol.bsky.social shows how #machinelearning can enhance wildlife surveys by automating species detection & classification and enabling unbiased density estimates 📷🦌.

Check it out! ⬇️
besjournals.onlinelibrary.wiley.com/doi/10.1111/...
Reposted by Andrea Zampetti
bes-quantitative.bsky.social
Thrilled to announce our webinar series:

🌱📈 Quantifying Ecology 📈🌱

We are collaborating with our SIG friends to bring you quantitative methods in different ecological contexts.

Kicking off with Dr @jamesaorr.bsky.social and @bes-aquaticgroup.bsky.social on 5th August. More details to come!
Reposted by Andrea Zampetti
science.org
A game-changing new opponent has stepped onto the badminton court. But don’t worry; it’s still a beginner.

Researchers have developed a robot that can successfully volley a shuttlecock, tracking down the object and moving across the court to send it back to its human adversary: scim.ag/4kz3nKW
Reposted by Andrea Zampetti
ppalencia.bsky.social
Another promising paper on the transition from AI models for image classification to user friendly apps.
Let's see how it works!
#cameratrapping

peercommunityjournal.org/item/10.2407...
Reposted by Andrea Zampetti
methodsinecoevol.bsky.social
📖Published📖

Matthew Kling presents phylospatial, a new R package that fully supports probability, abundance, and binary community data across a range of spatial phylogenetic diversity (PD) analyses 🌎 🧪 Check the article out here 👇

buff.ly/onf4BV6
Reposted by Andrea Zampetti
lsantinieco.bsky.social
The first paper of the "Urbis project" focusing on the urban ecosystem of Rome is out in Urban Forestry & Urban Greening!
Here we characterize the urban landscape and propose a multiscale framework to better support urban biodiversity research and planning
doi.org/10.1016/j.la...
Reposted by Andrea Zampetti
phenogirl.bsky.social
A new preprint on the best configuration settings of BirdNET for improving bird detections, lead by Cristian Pérez-Granados & David Funosas. A derived paper of the WABAD dataset, with more than 4,000 minutes of annotated audios. Enjoy reading!! #bioacoustics
www.researchsquare.com/article/rs-6...
Optimisation of passive acoustic bird surveys: a global assessment of BirdNET settings
BirdNET is a popular machine learning tool for automated recognition of bird sounds. Here we evaluate how BirdNET settings affect the model performance both at vocalization and species levels, using 4...
www.researchsquare.com
Reposted by Andrea Zampetti
elifakata.bsky.social
Our paper is now out in Nature Human Behaviour! 🎉 We use games from behavioural economics to explore how LLMs behave in repeated social interactions, revealing both self-interested strengths and coordination blind spots, and propose strategies to improve AI-human collaboration.
Reposted by Andrea Zampetti
oaggimenez.bsky.social
Here are a few slides to present our paper in a short talk for the annual days of our national group in statistical ecology ecostat2025.sciencesconf.org

doi.org/10.6084/m9.f...
Reposted by Andrea Zampetti
scbitaly.bsky.social
The Student Award for Best Oral Presentation goes to @andrewzampetti.bsky.social for his talk on TropiCam-AI: an automated classifier of Neotropical arboreal mammals and birds from camera-traps. Well done, Andrea!
Special mention to Claire Louise Penton for securing 2nd place—congrats! #ECR2025
Reposted by Andrea Zampetti
virginiagewin.bsky.social
Currently, roughly 90–95% of AI usage in biodiversity
and conservation research is simply identifying
a species of interest in gobs of data, says
@sarameghanbeery.bsky.social of the Massachusetts Institute of Technology, co-founder of MegaDetector.

But that promises to change swiftly.
Reposted by Andrea Zampetti
globalmammal.bsky.social
Excited to share that Martina Fernando, PhD student at our Global Mammal Assessment Lab, just presented her work "Developing a global probability map of illegal hunting on terrestrial mammals"with Michela Pacifici and Marco Davoli 🐘🌍 #ConservationScience #IllegalHunting #ECR2025
Reposted by Andrea Zampetti
jgeschke.bsky.social
Adoption of AI in conservation will lead to beneficial outcomes for conservation effectiveness and improve our understanding of the natural world. However, it will not wholly replace established conservation techniques, education, and on-the-ground research.

📑 doi.org/10.1016/j.tr...
Reposted by Andrea Zampetti
danlarremore.bsky.social
😳 WithdrarXiv 🙏

- Dataset of 14K+ withdrawn arXiv papers
- associated retraction comments
- entire history through 09/24
- taxonomy of retraction reasons, from critical errors to policy violations
- WithdrarXiv-SciFy, enriched version w/ scripts for parsed full-text PDFs

arxiv.org/abs/2412.03775
WithdrarXiv: A Large-Scale Dataset for Retraction Study
Retractions play a vital role in maintaining scientific integrity, yet systematic studies of retractions in computer science and other STEM fields remain scarce. We present WithdrarXiv, the first larg...
arxiv.org
Reposted by Andrea Zampetti
global-ecology.bsky.social
Great worflow and R package for any one working of ecological trait database !!

by Elizabeth Wenk et al. in Ecological Informatics Nov. 2024

www.sciencedirect.com/science/arti...

🧪🌐🌍
Reposted by Andrea Zampetti
kirstyfranklin.bsky.social
New paper! If you use time-lapse cameras, this one's for you!

Proud of this collaboration with UEA Computing Sciences' Marcus Jenkins & Michal Mackiewicz to improve object detection for time-lapse imagery using temporal features. 📷🖥️⏲️

Open Access in Sensors: mdpi.com/3088004
andrewzampetti.bsky.social
That's awesome! Can I be added please?
Reposted by Andrea Zampetti
sarameghanbeery.bsky.social
I started to put together a starter pack for research in AI+Ecology, check it out and let me know if you would like to be added!

go.bsky.app/8zugFF6
andrewzampetti.bsky.social
🫂 Thanks to the co-authors @davidemirante.bsky.social, @ppalencia.bsky.social and
@lsantinieco.bsky.social for their critical contribution, and a special aknowledgement to the people at Tenuta Sant'Egidio for their precious field support 🐗🦉! #AI4Conservation
andrewzampetti.bsky.social
‼️🔴 Our results suggest that popular algorithms for animal detection such as MegaDetector can be safely integrated with CT-DS and REM, and that final density estimates are reliable. Moreover, CT-DS showed to be robust even when taxonomic classifier accuracy was as low as 50%.