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  1. Impact
  2. NEON at AGU 2022

NEON and Battelle at AGU

NEON and Battelle are excited to join in the AGU 2022 Fall Meeting - one of the world's largest scientific conferences - December 12-16 in Chicago, IL. We will have staff attending in person and virtually, and will join with attendees from across the globe to share and take part in the conference.

Open data = science for all

The National Ecological Observatory Network (NEON) is a continental-scale ecological observation facility fully funded by NSF and operated by Battelle. NEON collects and provides open data and samples from field sites across the United States to characterize and quantify how our nation's ecosystems are changing. The comprehensive data, spatial extent, and remote sensing technology provided by the NEON program contribute to a better understanding and more accurate forecasting of how human activities impact ecology and how we can more effectively address critical ecological questions and issues.

NEON data and resources are freely available to enable users to tackle scientific questions at scales not accessible to previous generations of ecologists. The Observatory includes 81 field sites (47 terrestrial and 34 aquatic) located in different ecosystems across the United States (including Alaska, Hawaii, and Puerto Rico). Data collection methods are standardized across sites and include automated instrument measurements, observational field sampling, and airborne remote sensing surveys. Field sites are strategically selected to represent different regions of vegetation, landforms, climate, and ecosystem performance. The NEON data catalog includes over 180 data products. The Observatory also archives biological, genomic, and geological samples, available upon request and curated by the NEON Biorepository at Arizona State University.

NEON is part of a bold effort to:

  • Understand and forecast continental-scale environmental change
  • Inform natural resource decisions
  • Engage the next generation of scientists

Join us! What questions will you answer?

Explore the AGU Meeting Website

Fall Meeting

Get started with NEON!

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Event schedule

All times are Central Standard Time (CST) (UTC-6).

Check back for updates!

 

Oral Sessions & Talks

B12C-02 - Geochemical and Fungal Controls Over Decomposition of Lignin, Litter, and Soil Organic Carbon at the Continental Scale  -  Talk
Monday, 12 December; 09:15 - 9:25
NEON author: Samantha Weintraub-Leff

H13G-06 - High-Frequency Sensors Reveal Variable Concentration-Discharge Relationships Across Temporal Scales in a Snowmelt-dominated Rocky Mountain Catchment  -  Talk
Monday, 12 December; 11:50 - 12:00
NEON author: Robert Hensley

B15C - Advances in Upscaling Networked Observations to Regions and the Globe Using Machine Learning and Modeling III Oral  -  Session
Monday, 12 December; 14:45 - 16:15
NEON convener: Stefan Metzger

B15D - Soils in the Anthropocene: New Insights Across Space and Time I Oral  -  Session
Monday, 12 December; 14:45 - 16:15
NEON convener: Samantha Weintraub-Leff

GC26D-05 - Disparities in Observed vs Modeled Soil Nitrogen Mineralization Using a Continentally Distributed Dataset  -  Talk
Tuesday, 13 December; 17:31 - 17:42
NEON author:  Samantha Weintraub-Leff

B43A - Advances in Measuring Plant and Ecosystem Function: Toward Effective Climate Solutions II Oral  -  Session
Thursday, 15 December; 11:00 - 12:30
NEON convener: Stefan Metzger

B56C - Surface-Atmosphere Interactions: From Single Flux Measurements to Integrated Syntheses III Oral  -  Session
Friday, 16 December; 8:00 - 11:30
NEON co-convener: David Durden

B55B-04- Tracking the Response and Recovery of Vegetation Structure Following Fire in the Cerrado Biome using Spaceborne Lidar  -  Talk
Friday, 16 December; 15:15 - 15:25
NEON author: Venkata Shashank Konduri

Posters

B11B - Advances in Upscaling Networked Observations to Regions and the Globe Using Machine Learning and Modeling  -  Online Poster Discussion
Monday, 12 December; 08:00 - 9:00
NEON convener: Stefan Metzger

B12F - Advances in Upscaling Networked Observations to Regions and the Globe Using Machine Learning and Modeling II Poster  -  Session
Monday, 12 December; 9:00 - 12:30
NEON convener: Stefan Metzger

B12F-1134 - Network-scale Data Integration to Improve Earth-System Modeling  -  Abstract
Monday, 12 December; 9:00 - 12:30
NEON coauthors: Dave Durden, Dawn Lenz, Samantha Weintraub-Leff, Ed Ayres, Michael SanClements

B22I - Soils in the Anthropocene: New Insights Across Space and Time II Poster  -  Session
Tuesday, 13 December; 09:00 - 12:30
NEON convener: Samantha Weintraub-Leff

IN32C-0397 - Open Source Tools for Working with NEON Remote Sensing Data  -  Abstract
Wednesday, 14 December; 09:00 - 12:00
NEON authors: John Adler, Bridget Hass, Christine M Laney

SY33A-08 - Integrating Community Knowledge and Large Scale, Phenological Data: Building a Partnership to Determine Alaska’s Berry Future  -  Talk
Wednesday, 14 December; 12:10 - 12:20
NEON author: Lori Petrauski

B44A - Advances in Measuring Plant and Ecosystem Function: Toward Effective Climate Solutions III   -  Online Poster Discussion
Thursday, 15 December 13:45 - 14:45
NEON convener: Stefan Metzger

B45F - Advances in Measuring Plant and Ecosystem Function: Toward Effective Climate Solutions IV Poster  -  Session
Thursday, 15 December; 14:45 - 18:15
NEON convener: Stefan Metzger

B45F-1774 - Expanding Community Science by Leveraging NEON Research Support  -  Abstract
Thursday, 15 December; 14:45 - 18:15
NEON authors: Rommel C Zulueta, Michael SanClements

B52H - Surface-Atmosphere Interactions: From Single Flux Measurements to Integrated Syntheses I Poster  -  Session
Friday, 16 December; 09:00 - 12:30
NEON co-convener: Dave Durden

B52H-0922 - NEON Surface-Atmosphere Resources: Paths from Network Science to Societal Benefits  -  Abstract
Friday, 16 December; 09:00 - 12:30
NEON authors: Stefan Metzger, Dave Durden, Chris Florian, Hongyan Luo, Caleb Slemmons, Michael SanClements, Cove Sturtevant

Featured video

More science videos

These videos give a better understanding of the NEON program, explain data collection techniques, and explore scientific concepts related to ecological data. Many of them are short, engaging animated videos that teach key data concepts and tell ecological stories using data and are perfect for adding to presentations and classroom discussions.

neonscience youtube

Explore NEON resources

NEON provides a variety of resources to support researchers, educators, and students in using NEON data including:

Data Tutorials

Looking to improve your data skills using specific tools like R or Python? Want to learn more about working with a specific NEON data product?

NEON develops online tutorials to help you improve your research. These self-paced tutorials are designed for you to used as standalone help on a single topic or as a series to learn new techniques.

Teaching Modules

For educators, NEON provides Teaching Modules that include lesson outlines, curated datasets, and data skills activities to teach essential ecological concepts with accompanying data skills.  Teaching modules are cross-listed on QUBES Hub and through other collaborating projects. 

We welcome inquires from instructors interested in using NEON data in their own classrooms. 

Workshops

Workshops can range from a few hours to a week and teach specific skills and provide more insight into NEON data.

NEON workshops are posted on our Upcoming Events page. You can browse our upcoming workshops here, and also find links to past workshops and recorded events. Contact us with any questions about our workshops and trainings. 

Information for Researchers

This page includes a variety of information to help researchers plan their research and submit proposals to funding agencees, including the National Science Foundation. Topics include AOP flight schedules and interannual observational sampling schedules, site access guidelines, how to request a letter of support and how to request an assignable assets.

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The National Ecological Observatory Network is a major facility fully funded by the National Science Foundation.

Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the National Science Foundation.