July 2025
NEON'S NARRATIVE
Last month, I collaborated with Dr. Paula Mabee and other folks at NEON, along with Dr. Justin Kitzes at the University of Pittsburgh, to bring the “Cyberinfrastructure and AI for Ecological Research at NEON and Beyond” workshop to life. This workshop connected 41 researchers and 10 student note-takers at the University of Pittsburgh to explore transformative opportunities at the intersection of AI, sensors, and ecology.
Designed as an “un-conference,” the workshop emphasized participant-led breakout sessions over traditional talks. AI and edge computing are enabling new innovations and approaches to advancing our scientific understanding of ecosystems. Participants engaged in vigorous discussions on edge AI, adaptive sampling, and ecological applications of large language models. Over 70 original ideas were generated and later distilled into focused sessions, ranging from animal-borne sensors and eDNA collection to AI-ready data infrastructures and precision agriculture.
A key highlight was the vision for AI agents and foundation models tailored for ecologists, leveraging resources such as the Sage Grande Testbed and NEON to test and explore the new modalities. The shift from simple biosphere sampling to adaptive, autonomous, agent-based investigation was identified as a major future direction for AI-enabled infrastructure integrated with scientific instrumentation.
The workshop demonstrated the critical role of interdisciplinary collaboration in advancing ecological science and laid the groundwork for impactful, AI-driven environmental research. Several groups of scientists self-organized into writing teams to draft position papers. Sage Grande and NEON are working together to explore AI-enabled data analysis and discover how new instruments could be tested within the NEON framework.
I was excited to work with NEON to bring leading minds in AI and ecology together!
Best,
Pete Beckman
Professor at Northwestern University
Designed as an “un-conference,” the workshop emphasized participant-led breakout sessions over traditional talks. AI and edge computing are enabling new innovations and approaches to advancing our scientific understanding of ecosystems. Participants engaged in vigorous discussions on edge AI, adaptive sampling, and ecological applications of large language models. Over 70 original ideas were generated and later distilled into focused sessions, ranging from animal-borne sensors and eDNA collection to AI-ready data infrastructures and precision agriculture.
A key highlight was the vision for AI agents and foundation models tailored for ecologists, leveraging resources such as the Sage Grande Testbed and NEON to test and explore the new modalities. The shift from simple biosphere sampling to adaptive, autonomous, agent-based investigation was identified as a major future direction for AI-enabled infrastructure integrated with scientific instrumentation.
The workshop demonstrated the critical role of interdisciplinary collaboration in advancing ecological science and laid the groundwork for impactful, AI-driven environmental research. Several groups of scientists self-organized into writing teams to draft position papers. Sage Grande and NEON are working together to explore AI-enabled data analysis and discover how new instruments could be tested within the NEON framework.
I was excited to work with NEON to bring leading minds in AI and ecology together!
Best,
Pete Beckman
Professor at Northwestern University
As Chief Scientist and Observatory Director of NEON, Dr. Paula Mabee is leading her organization in exploring how AI can reshape ecological research.
This summer, she co-led a U.S. National Science Foundation (NSF) funded interdisciplinary workshop called “Cyberinfrastructure and AI for Ecological Research at NEON and Beyond.” It focused on identifying research priorities across AI-enabled cyber and physical infrastructure, and ecological research.
This summer, she co-led a U.S. National Science Foundation (NSF) funded interdisciplinary workshop called “Cyberinfrastructure and AI for Ecological Research at NEON and Beyond.” It focused on identifying research priorities across AI-enabled cyber and physical infrastructure, and ecological research.
A continental scale analysis reveals widespread root modality
- Widespread bimodal root patterns were found when researchers leveraged deep-soil NEON data across North America, which suggests that AI-enhanced ecological modeling could revolutionize the detection and prediction of underground carbon and nutrient dynamics.
- Researchers using NEON data from 70,000 U.S. plant plots found that non-native plant success is driven not only by fast resource-use traits but also by novel ecological characteristics. These insights could be sharpened through AI-powered trait abundance modeling.
Explore how NEON data, samples, and infrastructure is being used in new research
October 10: REGISTER
Living Data 2025: Unified Information Driving Transformation
Living Data 2025 taking place October 21-24 in Bogotá, Colombia, is a joint conference featuring NEON in a session co-organized with Long Term Ecological Research Network (LTER), Environmental Data Initiative (EDI) and Global Biodiversity Information Facility (GBIF), highlighting partnerships to advance biodiversity data synthesis, especially amid the growing use of AI and machine learning.
October 15-17: ATTEND
NEON Convergence Summit 2025: Advancing Continental-Scale Biology
NEON’s first Convergence Summit in Boulder, Colorado, will explore innovative ways to use NEON data, samples and infrastructure to advance continental-scale biology. Mark your calendars!
Living Data 2025: Unified Information Driving Transformation
Living Data 2025 taking place October 21-24 in Bogotá, Colombia, is a joint conference featuring NEON in a session co-organized with Long Term Ecological Research Network (LTER), Environmental Data Initiative (EDI) and Global Biodiversity Information Facility (GBIF), highlighting partnerships to advance biodiversity data synthesis, especially amid the growing use of AI and machine learning.
October 15-17: ATTEND
NEON Convergence Summit 2025: Advancing Continental-Scale Biology
NEON’s first Convergence Summit in Boulder, Colorado, will explore innovative ways to use NEON data, samples and infrastructure to advance continental-scale biology. Mark your calendars!
To view additional events, visit NEON’s event calendar.
EOS, July 14, 2025
How Plants Respond to Scattered Sunlight
NEON was used to analyze how plants respond to scattered sunlight, enabling researchers to uncover insights on continental scale about carbon uptake and ecosystem dynamics.
How Plants Respond to Scattered Sunlight
NEON was used to analyze how plants respond to scattered sunlight, enabling researchers to uncover insights on continental scale about carbon uptake and ecosystem dynamics.
• NEON Calibration Technician , Boulder, CO
• NEON Field Ecologist , Limnology, Vancouver, WA
Data Skills Tutorial
Access NEON Data for Metagenomics
Exploring NEON AOP Remote Sensing and GBIF occurrence data in Google Earth Engine Python (geemap) to assess the impacts of a wildfire
Access NEON Data for Metagenomics
- Using NEON tools to access metadata for metagenomic samples.
Exploring NEON AOP Remote Sensing and GBIF occurrence data in Google Earth Engine Python (geemap) to assess the impacts of a wildfire
- Use NEON airborne hyperspectral data to map a fire and then use the GEE (Google Earth Engine) Python API to explore the burn scar. Incorporate pygbif(Python Global Biodiversity Information Facility) library to pull records from the NEON Biorepository to see if and/or how the fire impacted Carabid beetle communities.
Track weekly Observatory status updates.
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Subscribe to Flight Reports from NEON’s Airborne Observation Platform (AOP).
Learn more about NEON data collection methods.
Visit the Learning Hub for new data skills tutorials and code packages to help work with NEON data.
Subscribe to Flight Reports from NEON’s Airborne Observation Platform (AOP).
Learn more about NEON data collection methods.
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