Case studies exemplify the impact that NEON can make on ecological research. Explore these stories that describe how our user community have made new, exciting discoveries about how our natural systems function.
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Arbuscular mycorrhizal (AM) fungi are found in nearly every ecosystem, quietly helping plants absorb nutrients from the soil. Dr. Bala Chaudhary wants to build a better model of how these vital ecosystem players disperse across the continent. She is using NEON’s Assignable Assets program to examine the role of aerial dispersal in AM fungal movement.
Dr. Zachary Kayler, an assistant professor in the Department of Soil and Water Systems at the University of Idaho, used NEON soil samples to test the ability of a widely-used soil health metric to detect changes from an extreme weather event - Hurricane Maria - in Puerto Rico.
Jeffery Cannon, a Forest Management Scientist at The Jones Center, is using remote sensing data from the NEON program to understand how longleaf pine forests are impacted by and recover from major weather events. He and his colleagues will use the results to develop tools to help forest managers plan restoration and conservation efforts.
Andrew Fricker, used remote sensing data from the NEON Airborne Observation Platform to train a neural net to classify tree species in a Sierra Nevada forest. He and his coauthors describe their approach in Remote Sensing: “A Convolutional Neural Network Classifier Identifies Tree Species in Mixed-Conifer Forest from Hyperspectral Imagery.”
Chris Gough, an associate professor of biology at Virginia Commonwealth University (VCU), is using data from the NEON program to explore relationships between forest structure, biodiversity, and other characteristics and their ability to sequester carbon. His collaborative work with PIs from the University of Connecticut and Purdue University was recently published in Ecology: “High Rates of Primary Production in Structurally Complex Forests."
Understanding why tick populations are increasing, and why some species are spreading into new geographic areas, is of critical importance to public health. In a recent study, researchers used NEON data to develop a model of tick population dynamics at the Ordway Swisher Biological Station field site.
A team led by NEON scientists David Hulslander and Jessica Bolis has developed a method to map tree mortality with an unprecedented level of detail using hyperspectral remote sensing data from the NEON Airborne Observational Platform and a novel imaging algorithm.
A new modeling approach could allow researchers to use remote sensing lidar data to predict small mammal biodiversity based on the structure of vegetation in an area. The study was led by Sarah Schooler, now a Ph.D. candidate at State University of New York (SUNY)–Syracuse, and Harold Zald of the Humboldt State University Department of Forestry and Wildland Resources. Lidar Prediction of Small Mammal Diversity in Wisconsin, published in Remote Sensing, explores how measurements of vegetation structure created with lidar data could be used to predict the diversity of small mammal communities.
Dr. Phoebe Zarnetske, an Assistant Professor in the Department of Integrative Biology at Michigan State University (MSU), is using data from the NEON sites to investigate patterns in biodiversity and species traits across the continent. Her goal is to better understand the drivers that influence species distributions and community assembly.
Kyla Dahlin and her team are using Airborne Remote Sensing data from five NEON sites to develop detailed 3D maps of forest structure. Their work, which was funded by the National Science Foundation (NSF), could provide new insights into the carbon storage potential of forests.
Land use changes and habitat loss have resulted in an overall loss of biodiversity across much of the country. Luis Carrasco, a post-doctoral fellow at NIMBioS, is leveraging NEON data to better understand the relationships between vegetation structure and density and bird biodiversity in forested ecosystems.
Imagine walking through the deciduous forests in Massachusetts early one spring, a gentle rain falling down on you. Taking a closer look, you now see thousands of hairy caterpillars in the trees.
Adlafia neoniana (Naviculaceae) may be tiny, but it's got a big name to live up to. It's the first new species to be discovered on a NEON field site and named after the NEON program. So what is this newly discovered organism? A single-celled aquatic alga with a cell wall made of silica, known as a diatom.
The exact composition of each local community is influenced by variables that include evolutionary history, current environmental conditions, and interspecies competition or codependence. A new study led by Will Pearse of Utah State University is using NEON data to quantify the roles of these different variables in the assembly of ecological communities.
How are ecosystems across the continent changing over time? What are the relationships between ecosystem composition and soil organic matter? And how are soil composition and carbon storage potential likely to change in the future? The answers lie under our feet.
It's one thing to read about ecological concepts in a textbook. It's another to see them revealed by real-world data. Students at Ball State University recently explored key ecological concepts using data from the NEON program.
A new study led by François Ritter, a Ph.D. candidate at the University of Illinois–Chicago Department of Earth and Environmental Sciences, provides important insights into the frequency of dew formation across the U.S.
A new study funded through the National Science Foundation (NSF) Rapid Response to Funding (RAPID) Grant program attempts to answer critical questions about the correlations between biomass burned from wildfires and the emitted quantities of trace gases and aerosols.
To build better models of watershed processes and calibrate remote sensing data with observations on the ground, a diverse team of researchers spent two weeks this summer gathering soil and vegetation data from hundreds of individual sites within the East River watershed near Crested Butte, CO.
A study led by Lawrence Berkley National Laboratory (LBNL) has used the NEON assignable assets program to gather airborne remote sensing data near Crested Butte, Colorado. They will use the data to study plant community distributions and canopy biochemistry to shed light on watershed systems.
The NEON project is producing a vast treasure trove of open access airborne remote sensing data. Can computer algorithms help ecologists make sense of it all? A team of ecologists and data scientists at the University of Florida thought so. To accelerate the process, they initiated a data science challenge.
