Research project title: Accurate detection and integrated treatment of oak wilt (Bretziella fagacearum) in Minnesota
Species: Oak wilt (Bretziella fagacearum)
Project status: Completed in 2021
More than 266,000 oak trees were infected by oak wilt fungus between 2007 and 2016 in Minnesota, making it the second greatest invasive pathogen threat to the state behind Dutch elm disease. The fungus is found in more than a quarter of all Minnesota counties.
Early and accurate detection of oak wilt is key to stopping its spread. This project explores the diagnostic potential of hyperspectral imaging, a remote sensing technology capable of surveying a scene or landscape and extracting detailed information about its features. Hyperspectral imaging is conducted with the use of planes or unmanned aerial vehicles (UAVs), also known as drones, that can fly high over the forest canopy. This type of imaging may be sensitive enough to identify oak wilt before visible signs of infection, and help managers differentiate between trees exhibiting oak wilt and those suffering from drought or other diseases.
The team will also address current best practices in oak wilt management. Most programs today promote root cutting between diseased and healthy oaks to prevent disease spread. The preferred tool for this step in Minnesota is the vibratory plow line. This project will test anecdotal claims that two passes with a plow line achieves longer control than a single cut.
- How can hyperspectral imagery technology be used to detect oak wilt at the leaf, tree crown and forest stand levels?
- How can we improve root cutting protocol to stop the below-ground spread of oak wilt fungus?
This project represents a long-term effort to identify, understand and contain the oak wilt disease to protect Minnesota’s legacy forests. Technology-assisted approaches like this one have potential to bring faster, more accurate diagnostic capabilities to forest health professionals in the future.
Research project title: Accurate detection of oak wilt disease from tree to landscape scales for enhanced forest management
Species: Oak wilt (Bretziella fagacearum)
Project status: In progress
This project builds on the work completed in the first phase, and represents a critical component of a long-term effort to identify, understand, and contain the oak wilt disease to protect Minnesota and US forests. Important advances have been made in understanding oak wilt, developing treatments, and documenting spread. However, critical gaps remain both in accurate detection of the disease, differentiating it from other diseases on different oak hosts, and in improving best management practices.
Over the last four years, the research team has successfully used hyperspectral data as well as airborne imaging spectroscopy to detect oak wilt symptoms and differentiate them from other stress factors. They will develop approaches for canopy level oak wilt detection and large-scale mapping of oak wilt intensity. They will also evaluate the efficacy of contrasting oak wilt management strategies.
- What models and tools are best to detect and differentiate oak wilt from other damage at multiple scales?
- What is the efficacy of an improved oak wilt treatment method in a long-term field experiment, comparing current and proposed approaches? What are the costs of the two approaches?
The goal of this project is to provide novel tools that are readily available to detect and treat oak wilt that can be applied by natural resource managers across a range of spatial scales at the county, state, and regional levels. Researchers will work with implementation partners to provide tools and training that best serves their needs. The work will have impact beyond Minnesota given its relevance throughout the range of oak wilt.
Phase 1 of this project developed methods and approaches for better detection of oak wilt using spectroscopic technology. The study showed that it is possible to use spectroscopic tools to accurately diagnose a disease from other possible stresses, such as oak blight, present in common co-occurring oak species. Researchers also documented best practices to prevent the spread of oak wilt using the two pass vibratory plow protocol.
Phase 2 is ongoing.
- Canopy spectral reflectance detects oak wilt at the landscape scale using phylogenetic discrimination (Remote Sensing of Environment, 2022)
- Spectral differentiation of oak wilt from foliar fungal disease and drought is correlated with physiological changes (Tree Physiology, 2020)
News and media
- UMN researchers say invasive fungus that threatens oak trees is spreading (The Minnesota Daily, 2020)
- Cross-disciplinary research teams seek to answer grand challenges in biology (National Science Foundation, 2020)
- Saving America's Tree: Oak Wilt Early Detection in Minnesota (Minnesota Invasive Terrestrial Plants and Pests Center, 2019)
- The spectral diversity of plants (Nature Ecology & Evolution Community, 2018)
- 5 Ways Researchers Are Using Drones to Stop Invasive Species (Minnesota Invasive Terrestrial Plants and Pests Center, 2019)
- Meet the Researcher: Gerard Sapés
- NASA Carbon Cycle & Ecosystems Joint Science Workshop, 2023
- University of Minnesota Office of Vice President for Research Research Workshop, 2023
- SDG Webinar
- International Workshop on Sap Flow
- Upper Midwest Invasive Species Conference, 2022