Accurate detection and integrated treatment of oak wilt in Minnesota
Jeannine Cavender-Bares, Ecology, Evolution & Behavior
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.
US Forest Service, Cedar Creek Ecosystem Science Reserve, University of Nebraska - Lincoln, University of Wisconsin - Madison
Jeannine Cavender-Bares, principal investigator
Beth Fallon, post-doctoral associate
Rebecca Montgomery, co-principal investigator
Jenny Juzwik, co-principal investigator
Gerard Sapes, post-doctoral associate
News & Publications
- "The spectral diversity of plants" Nature Ecology & Evolution Community
- Plant spectral diversity integrates functional and phylogenetic components of biodiversity and predicts ecosystem function (Nature Ecology & Evolution, 2018)
- Detecting prairie biodiversity with airborne remote sensing (Remote Sensing of Environment, 2019)