Improved detection and management of leafy spurge and common tansy

photographic collage; left is common tansy; right is leafy spurge flower heads

Left: common tansy; right: leafy spurge

Image credits
Left: "Common Tansy" by Dan Mullen is licensed under CC BY-NC-ND 2.0
Right: "Leafy spurge - bloom" by Tarry Edington is licensed under CC BY 2.0



Computer-generated models make it possible for researchers to predict where invasive species are most likely to spread under future climate conditions. Machine learning techniques coupled with field survey data produce reliable maps that managers can use in early detection efforts. MITPPC scientists have already created predictive model maps of 9 invasive weed species on Minnesota’s Noxious Weed List to make early detection easier and improve the State’s eradication efforts. 

A new phase of the project aims to improve the model for more fine-scale prediction of the invasive species common tansy and leafy spurge. Researchers will take an innovative approach to species surveying across the Minnesota landscape by using techniques like remote sensing and hyperspectral satellite imaging.  

Research questions

  • What is the current and future distribution of common tansy and leafy spurge?
  • How will changes in temperature and moisture affect the growth and reproduction of common tansy and leafy spurge?
  • How do populations of common tansy and leafy spurge differ across the state and how have both species been spreading?

Practical implications

Maps that describe the future distribution of common tansy and leafy spurge will have direct value to managers and decision makers as they create plans for control and eradication throughout Minnesota. Common tansy and leafy spurge are noxious weeds in Minnesota and must be controlled to prevent the maturation and spread of propagating parts.


News and media


  • Upper Midwest Invasive Species Conference, 2022
  • Ecological Society of America - Montreal, 2022
  • UMN American Society of Photogrammetry and Remote Sensing Student Chapter, 2022

Research team

Ryan Briscoe Runquist | principal investigator

David Moeller | co-principal investigator

Thomas Lake | PhD candidate


Lab or other website 


Collaborating organizations

UMN Supercomputing Institute

Minnesota Department of Natural Resources

Minnesota Department of Agriculture