Climate change and range expansion of invasive plants

Background

Computer-generated models make it possible for researchers to predict where terrestrial 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. For this project, data was collected from public records and combined with available environmental data in order to create the SDMs.

The following species are on the state's "eradicate" list (except narrowleaf bittercress) and were studied in this project:

• Palmer amaranth: a highly aggressive weed that threatens agricultural production
• Narrowleaf bittercress: herbaceous annual invading forested areas along rivers in eastern Minnesota; considered an “early detection” species with limited distribution in the state and designated as a “prohibited, control” weed
• Oriental bittersweet: a heavy, deciduous vine with red and yellow fruit; can girdle or collapse trees
• Brown knapweed: a perennial plant with pink flower that has potential to outcompete native species; not yet common in Minnesota
• Black swallow-wort: herbaceous perennial vine in the milkweed family, with seed pods and starlike flowers; infestations can grow to cover several acres of land
• Common teasel: prolific seed producer able to form dense monocultures; considered an “early detection” species with limited distribution in the state
• Japanese hops: herbaceous vines that grow so rapidly they can smother other plants; only two confirmed instances in Minnesota to date, along the Root and Mississippi Rivers
• Dalmatian toadflax: yellow, snapdragon-like flowers; this plant is a major problem in the western US but so far, few Minnesota infestations have been found
• Wild parsnip: An aggressive perennial plant that germinates from seed, spends the first year or more as a rosette, eventually bolts into a mature plant in the second year or later, flowers, sets seed, and dies
• Common tansy: A perennial plant with multiple stems that grow from a clump, giving the plant a shrub-like appearance

Research questions

• What is the current distribution of the above 9 invasive species?
• What is the predicted distribution of the above 9 invasive species for the current climate?
• What is the predicted distribution of the above 9 invasive species under climate change conditions?

Outcomes

This research team created predictive model maps of 10 terrestrial invasive weed species on Minnesota’s Noxious Weed List to make early detection easier and improve eradication efforts. The models provide value to managers and decision makers as they create plans for control and eradication throughout Minnesota.

They also provided training to US Forest Service professionals about the underlying mechanics of species distribution models and how and when they can be used to effectively forecast and manage the spread of invasive species under current and future climate conditions.

Publications

• Predicting range expansion of invasive species: Pitfalls and best practices for obtaining biologically realistic projections (Diversity and Distributions, 2020)
• Species distribution model projections for incipient invasive species of Minnesota (manuscript for MN Management Decision Makers, 2019)
• Species Distribution Models and Joint Species Distribution Models of Nine Invasive Species in North America (Data Repository for U of M, 2019)
• Species distribution models throughout the invasion history of Palmer amaranth predict regions at risk of future invasion and reveal challenges with modeling rapidly shifting geographic ranges (Scientific Reports, 2019)

Outreach and presentations

• Palmer Amaranth Summit, January 2019
• UMISC-NAISMA Conference, October 2018
• NWAC Management and Policy Subcommittee Meeting, April 2018
• Climate Change Training for US Forest Service Managers, February 2018
• “Detecting invasive species in MN”, CBS Market Science Outreach Table at Nokomis Farmer’s Market, August 2016 

News and media

• Enhanced computational approaches boost invasive plant predictive power (MITPPC, 2024)
• UMN researchers predict spread of invasive plant species into Minnesota (Minnesota Daily, March 2019)
• Evaluating Species Distribution Models (Minnesota Supercomputing Institute, 2019)