Andrea Zampetti

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!

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

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...

📖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

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...

Capuchin monkeys kidnap baby howler monkeys, shocking scientists The disturbing fad could be the result of boredom.

Capuchin monkeys kidnap baby howler monkeys, shocking scientists www.popsci.com/environment/...

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...

Spotted! Remote camera traps used in a novel design reveal a perilous situation for the Critically Endangered Northwest African cheetah (Acinonyx jubatus hecki) in a conflict‐affected protected area in Benin This first long-term study of the Critically Endangered Northwest African cheetah in Benin highlights a very low density. The Pendjari National Park is likely to be a core area for cheetah in the WAP...

This new approach minimises on-the-ground fieldwork in an area where conflict is widespread, and provides vital data needed to support conservation interventions for this rare and iconic subspecies. Find out more:
besjournals.onlinelibrary.wiley.com/doi/10.1002/...

BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The up...

🚨New data paper/open data alert!🚨 BioTIME v2.0 is out now! We've expanded the database with improved spatial and taxonomic coverage, with a new R package! As always, free, public, and open acess :)

Paper:
onlinelibrary.wiley.com/doi/10.1111/...

Database:
biotime.st-andrews.ac.uk

More shots fired in the #causalInference #ecology literature! 🌍

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.

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...

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

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.

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

2025 Species Distributions Modelling Course Several people wrote Miguel Araújo and Babak Naimi expressing interest in a new edition of the SDM course. In response to those requests a full 10th edition of the course is now scheduled for November...

The SDM (Species Distribution Modelling) course is back, now in its 10th edition. With Babak Naimi.
www.maraujolab.eu/2025/02/13/2...

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...

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...

😳 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

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...

🧪🌐🌍

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

That's awesome! Can I be added please?

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

🫂 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

‼️🔴 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%.

Two-ways partial dependence plot for a) CT-DS and b) REM showing how two key machine learning parameters exhibit compensating effects that result in unbiased density estimates.

📈 Our simulations revealed that certain key algorithm's parameters are good predictors for biases in density: so, early exploratory analyses can reveal if an automated approach can be used, and how much over/underestimation of the parameter is expected.

Comparison of density estimates for the three target species when image classification is carried out manually or by machine learning algorithms.

📊 We showed that CT-DS and REM both provide reliable estimates when an algorithm (#MegaDetector,
@sarameghanbeery.bsky.social @doctorofrock.bsky.social) is used to filter blank images, and CT-DS can even be used with an automated taxonomic classifier (#WildlifeInsights) with minimal bias.

🦡🦊🦌 We estimated density both on the field and in a simulation setting with two popular camera-trap models: Camera-Trap Distance Sampling (CT-DS) and Random Encounter Model (REM). Image classification was carried out both manually, and using two machine learning algorithms.

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/...

🫂 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