ECR feature: Ryan Briscoe Runquist on predicting invasion risk

Ryan Briscoe Runquist is a postdoc at the University of Minnesota in the USA. She is an evolutionary ecologist interested in invasive species and their potential impacts in a changing world. Here, Ryan shares her recent work on predicting invasive species range expansion using Joint Species Distribution Model.

R. Briscoe Runquist in front of a population of Leafy Spurge (Euphorbia virgata, formerly E. esula), an ecologically and economically damaging invasive species of the Upper Midwestern United States, which is particularly problematic for pastures and rangelands.

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Institute. University of Minnesota – Twin Cities

Academic life stage. Senior Postdoctoral Research Associate

Major research themes. I am generally interested in the ecology, evolution, and biogeography of plants and how those processes interact with global change – especially in invasive species.

Plant communities along the Zumbrota River in Minnesota, USA.

Current study system. I am currently researching invasive plant species of the Upper Midwestern United States and Central Canada. Most of the plants that I work with are herbaceous short-lived perennials that are causing lots of ecological and economic harm, such as crop losses and damage to ecosystem services like clean water. Although they can cause a lot of damage, invasive species are scientifically rich natural experiments to investigate the interaction of ecological and evolutionary forces in real time. Working in invasion biology is highly integrative at the intersection of basic and applied research and incorporates techniques from genomics to modelling to large field experiments.

Recent JBI paper. Briscoe Runquist, R. D., T. A. Lake, & D. A. Moeller (2021). Improving predictions of range expansion for invasive species using joint species distribution models and surrogate co-occurring species. Journal of Biogeography, 48(7):1693–1705

Plant communities along the Kettle River in Banning State Park, Minnesota, USA.

Motivation behind this paper. It would be incredibly useful to land managers and governments if scientists could effectively predict which regions are most at risk of invasion. Unfortunately, building these types of predictive models is quite challenging, if not impossible, with our current frameworks. This is because the underlying assumptions of the models, such as the assumption that a plant is not actively expanding its range, are in contrast with the reality that invasive species are a moving target. To overcome this issue, we wanted to use existing knowledge about what plant community members are most likely to co-occur with an invasive species as it enters a new region to help make better predictions about what areas are a greater risk.

Key methodologies. In our new method, we combined a rich dataset of over 10,000 plant communities collected by the Minnesota Department of Natural Resources since 1971 from across the state with a new class of models, called Joint Species Distribution Models (JSDMs). The JSDMs allowed us to identify native species in the state that had particularly similar or dissimilar habitat affinities to our invasive species of interest. We were then able to include in our model information on the sites where these native species occurred to help identify areas in Minnesota that might be subject to invasion. Including these surrogate species as natural indicators of habitat (i.e., phytometers) improved the predictive performance of our models.

Japanese hops (Humulus japonicus) growing in a dense monoculture along the edge of a river (Image Credit: “Japanese Hop” by matthewbeziat is licensed under CC BY-NC 2.0).

Unexpected challenges. We experienced a few different challenges while working on this research project. Our original approach to modelling the potential invasive distribution of these species focused on traditional species distribution model frameworks. However, there were so few records for these species in our study area that we needed to investigate other avenues, which is how we started working with JSDMs. Using JSDMs was challenging in a few different ways; there are several different potential approaches, and they are all relatively new. We investigated a few different JSDM frameworks but eventually settled on gJams because the documentation is helpful, and the results produced by this framework are readily incorporated into our workflow.

Major results. We found that models that incorporated surrogate native species could better predict invasive species occurrences compared to traditional models. Our surrogate models performed especially well along the leading edge of the invasion front. When land managers are trying to gauge invasion risk, models that can predict the expanding range edge occurrences are particularly useful. This is especially true if we are interested in predicting new areas outside of the current range of the invasive species that may be at risk for a future invasion.

Oriental Bittersweet (Celastrus orbiculatus) vines overwhelming a tree. The species causes damage through smothering trees and causing limb breakage due to the vines’ weight [Image Credit: “Oriental Bittersweet (Celastrus orbiculatus)” by Plant Image Library is licensed under CC BY-SA 2.0].

Next steps for this research. In my continued research, I am investigating other model frameworks that can incorporate more information about invasive species biology. The aim of these models is to use a combination of experiments and occurrence data to better estimate a species niche to improve predictions about species distributions and invasion potential. One area that I am particularly excited about is the use of imagery from Earth Observation satellite missions to detect more invasive species populations and help correct our incomplete occurrence record.

If you could study any organism on Earth, what would it be? I love plants, but I would love to do more research with trees. It would be amazing to study the high-altitude conifers in the ancient bristlecone pine forest.

Narrowleaf bittercress (Cardamine impatiens) growing between rocks [Image credit: “Cardamine impatiens (narrowleaf bittercress)” by tgpotterfield is licensed under CC BY-NC-SA 2.0].

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