$170,000 for Climate Change and Range Expansion of Invasive Plants to develop and validate predictive distribution models of high-priority invasive species under current and future climates. Research will focus on nine weeds on the Minnesota’s noxious weed list: Palmer amaranth, narrowleaf bittercress, oriental bittersweet, brown knapweed, black swallow-wort, Grecian foxglove, common teasel, Japanese hops, and Dalmatian toadflax. This work will improve detection and establish priorities for eradication and management. Principal investigator is David Moeller, professor of plant biology.
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Winter 2017 update
Invasive plant species are a significant and growing threat to agriculture, the economy, and natural spaces. How we manage these species already has and will continue to have important ecological and economic repercussions, such as the increased use of pesticides and the loss of biodiversity and native habitats. In our project, we are interested in understanding how environmental factors may influence species that are problematic and invasive in the continental United States to expand their ranges into Minnesota. We are building correlative species distribution models using machine-learning techniques for species that are potential invasion threats. The species being investigated include: Palmer Amaranth, Dalmatian Toadflax, Black Swallowwort, Narrowleaf bittercress, Common Teasel, Oriental Bittersweet, Japanese Hops, and Brown Knapweed. To build these models we are using multiple sources of climatological and other sources of environmental data and then using the models to predict the potential suitability of Minnesota habitats for invasion under current climatological conditions and under different future climatological scenarios. In preliminary models of all species, we have found that although there is some small variability among species, areas in southern Minnesota and some in central Minnesota are at greatest risk of invasion under current climate conditions and that this result is robust to the use of different climatic datasets and model building techniques. We have also found that predictions of habitat suitability under future climate projections increase for much of Minnesota and more areas of the state are at greater risk of invasion.