Luíz Fernando Esser

GitHub - luizesser/caretSDM: caretSDM applies a geoprocessing framework to the caret machine learning package, facilitating the access of Species Distribution Modeling community to state-of-the-art me... caretSDM applies a geoprocessing framework to the caret machine learning package, facilitating the access of Species Distribution Modeling community to state-of-the-art methods. - luizesser/caretSDM

Me and my fellows have realized some years ago the potential of caret. Since then we could put together the caretSDM package which crosses caret and stars packages to build species distribution models. github.com/luizesser/ca...

We mourn the passing of our Editor-in-Chief Steve Long.

His vision to establish one of the first journals dedicated to Global Change over 30 years ago was truly ahead of its time. Through GCB, researchers have demonstrated that biology and ecosystems are not simply victims of global change..

The Keeling Curve The Keeling Curve is a daily record of global atmospheric carbon dioxide concentration maintained by Scripps Institution of Oceanography at UC San Diego.

426.98 parts per million (ppm) CO2 in air 22-Jul-2025
keelingcurve.ucsd.edu

caretSDM: Build Species Distribution Modeling using 'caret' Use machine learning algorithms and advanced geographic information system tools to build Species Distribution Modeling in a extensible and modern fashion.

New on CRAN: caretSDM (1.1.0). View at https://CRAN.R-project.org/package=caretSDM

✅ Practical applications for conservation, restoration, and predicting climate impacts on ecosystems.

#Ecology #Biodiversity #ClimateChange #OpenScience

✅ We explore how functional traits (not just species identity) can better capture community dynamics, especially under climate change.
✅ Highlighted the role of metacommunity theory and the need for hybrid approaches combining correlative and mechanistic models.

🔍 Key Takeaways:

✅ Community Distribution Models (CDMs) extend traditional species-level models to predict biodiversity patterns by integrating dispersal constraints, environmental filters, and biotic drivers.

Species Distribution Models to Help Integrate Community Ecology Species distribution models can be used to infer communities' distributions, but what are the impacts of methodological choices in the context of Community Ecology theory? Here we map how state-of-th...

🌍 New Publication Alert! 🌿
Excited to share our latest review article: "Species Distribution Models to Help Integrate Community Ecology" published in Austral Ecology!

📄 Open Access: Read the full article here: onlinelibrary.wiley.com/doi/10.1111/...

GitHub - luizesser/caretSDM: caretSDM applies a geoprocessing framework to the caret machine learning package, facilitating the access of Species Distribution Modeling community to state-of-the-art me... caretSDM applies a geoprocessing framework to the caret machine learning package, facilitating the access of Species Distribution Modeling community to state-of-the-art methods. - luizesser/caretSDM

📖 Learn more & contribute:

GitHub: github.com/luizesser/ca...

A huge thanks to everyone who supported this project! 🙏 I’d love your feedback—give it a try and let me know what you think!

#RStats #Ecology #SDM #DataScience #Biodiversity #CRAN

🔹 Key Features:
✔ Unified framework for SDM using caret
✔ Supports multiple algorithms (100+ algorithms)
✔ Automated model tuning & validation

📦 Install it now:

R> install.packages("caretSDM")

🔹 What does it do?
caretSDM integrates advanced geoprocessing tools with the caret ecosystem to streamline SDM workflows, making it easier to train, evaluate, and compare models for ecological and biodiversity research.

Build Species Distribution Modeling using caret Use machine learning algorithms and advanced geographic information system tools to build Species Distribution Modeling in a extensible and modern fashion.

We are currently preparing a paper for submission, but some articles to help users are already available on the package website: luizesser.github.io/caretSDM/

🎉 Exciting News! My R Package caretSDM is Now on CRAN! 🎉
I’m thrilled to announce that caretSDM, my new #RStats package for Species Distribution Modeling (SDM), is now available on CRAN! 🚀

#RStats #Ecology #SDM #DataScience #Biodiversity #CRAN

Can a global predictive #modelling approach be applied to a #regionalscale to address local #conservationefforts?
Check this out doi.org/10.1111/ddi....

Luíz Fernando Esser | Achievement See this researcher's achievement on ResearchGate.

100 citations according RG. A true milestone to any aspiring scientist.

www.researchgate.net/profile/Luiz... via @researchgate

A poster for the event titled "Nature Narratives: Eden, Spoils or Garden" featuring Prof Sandra Díaz. The poster includes the Oxford Martin School and University of Oxford logos at the top. The text provides event details: Date & Time - 5th March 2025, 17:00–18:15 (GMT), Location - Oxford Martin School & Online. The right side displays a photograph of dandelion seed heads in a sunny field. The URL for more information is included: https://www.oxfordmartin.ox.ac.uk/events.

Is nature a paradise, a resource, or a garden? Join us as Professor Sandra Díaz, 2025 Tyler Prize laureate, delves into why it’s time to rethink our relationship with the nature.

📆 5 March | From 5pm

Register now: https://www.oxfordmartin.ox.ac.uk/events/nature-narratives

Disequilibrium in plant distributions: Challenges and approaches for species distribution models Plant distributions are often in disequilibrium with climate, not occupying all suitable habitat and present in conditions that no longer support long-term population persistence. This proves a chall...

Disequilibrium in plant distributions: Challenges and approaches for species distribution models - check our new review in @journalofecology.bsky.social doi.org/10.1111/1365... 🍃🌦️♨️🌿 #SDM #plants #speciesdistributions #ranges

chooseGCM: A Toolkit to Select General Circulation Models in R Can we recreate state-of-the-art climate change projections with limited computational resources? Our research demonstrates that it is possible through a novel machine learning-based approach. By dev...

🔗 Link to the article: onlinelibrary.wiley.com/doi/10.1111/...

YouTube video by Luíz Esser How to choose General Circulation Models using R

✅ A detailed tutorial on how to use the package.
If you're working with climate change projections and want a more efficient and reliable way to select GCMs, chooseGCM is for you! 🔥

🔗 Tutorial Video: www.youtube.com/watch?v=jmGL...

YouTube video by Luíz Esser chooseGCM - Reasoning and Theory

📽️ To make it easy to understand and apply, we’ve prepared two videos:
✅ A short 3-minute overview explaining the method.
🔗 Short Video: www.youtube.com/watch?v=tADR...

🔬 Our recent publication presents a methodological framework that significantly reduces computational time by over 79% while maintaining a high correlation (>0.9) with full-scale simulations. This is a game-changer for species distribution modeling (SDM) and ecological niche modeling (ENM)!

🚀 New Tool for Climate Projections! 🌍📊
We are excited to introduce chooseGCM, our new R package designed to help researchers efficiently select General Circulation Models (GCMs) for climate projections! 🌱🌡️

Here’s what happens to regression 📈 when sample sizes are low…

even with a strong underlying correlation, sampling error will erode everything! 🧪 ‼️

#rstats simulation viz via the switchboard package for R

Bluesky’s science takeover: 70% of Nature poll respondents use platform Roughly 6,000 readers answered our poll, with many declaring that Bluesky was nicer, kinder and less antagonistic to science than X.

Roughly 6,000 readers answered our poll, with many declaring that Bluesky was nicer, kinder and less antagonistic to science than X

https://go.nature.com/42tH8Ai

TECHNICAL ADVANCE
chooseGCM: A Toolkit to Select General Circulation Models in R

📄 https://buff.ly/3Pn3c7R