AIS webinars: Seeking starry stonewort

Monitoring for invasive species means navigating a paradox. The best time to find new invasives is "as early as possible," when control or eradication is more feasible. However, this is also when the species will be hardest to find. We may not even know where or how best to look for it yet or that we need to be looking for it. Using data on where a species is and isn't, and what occupied sites look like, we can build statistical models that predict where we are likely to find the species in the future. In other words, we can take presence and absence data on an emerging invasive like starry stonewort (Nitellopsis obtusa) and derive predictions for where starry stonewort might be living right now that we don't yet know about.

In this webinar, we'll describe how we overcame challenges to build a within-lake occupancy model for starry stonewort. We’ll talk about where starry stonewort is likeliest to be found, assuming a lake is already occupied by it. We'll describe the data set we built, discuss our model's structure in general, and summarize what the model has told us and what should happen next.

Presenters

Alex Bajcz is a plant ecologist and environmental scientist. His research has explored how and why plants reproduce as they do, how global change processes may disrupt that reproduction, and why invasives may experience enhanced reproductive success over their native peers. Alex advises MAISRC staff, project leaders, and students on quantitative ecology: statistics, data science and management, graphs and communication of data, and programming and computation.

John Fieberg is a professor of quantitative ecology in the Department of Fisheries, Wildlife, and Conservation Biology at the University of Minnesota where he teaches undergraduate- and graduate-level courses in statistics. Before joining the faculty at the University of Minnesota, he worked for ten years as a research statistician at the Minnesota Department of Natural Resources and two and half years as a biometrician with the Northwest Indian Fisheries Commission. Much of his research focuses on how to choose, apply and interpret appropriate statistical methods when confronted with messy ecological data.

Dan Larkin is a MAISRC research fellow and associate professor and Extension specialist in the Department of Fisheries, Wildlife and Conservation Biology at the University of Minnesota. He and his research team work on applied challenges in invasive species management and ecological restoration in lakes, wetlands, and terrestrial habitats. He trains volunteers and professionals to support invasive species response and ecological restoration efforts.