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Environmental Stats October seminar – Erin Schliep (University of Missouri)

  • 30 Oct 2020
  • 10:00 AM - 11:00 AM (UTC+11:00)
  • https://au.bbcollab.com/guest/fcf219c74ac743e89565a9e6e8d349a9

This Friday (30th October, 10am EDT) we will have the Environmental Statistics section October seminar and virtual visit, by Erin Schliep (U Missouri): 

Bayesian hierarchical modeling and data fusion for multivariate speciated nitrogen in lakes.

Erin Schliep (University of Missouri)

Friday 30 Oct @10am  AEDT -click here to join

About the presentation:

Concentrations of nitrogen provide a critical metric for understanding ecosystem function and water quality in lakes. However, varying approaches for quantifying nitrogen concentrations may bias the comparison of water quality across lakes and regions. Different measurements of total nitrogen exist based on its composition (e.g., organic versus inorganic, dissolved versus particulate), which we refer to as nitrogen species. Fortunately, measurements of multiple nitrogen species are often collected, and can therefore be leveraged together to inform our understanding of the controls on total nitrogen in lakes. We develop a multivariate hierarchical statistical model that fuses speciated nitrogen measurements obtained across multiple methods of reporting in order to improve our estimates of total nitrogen. The model accounts for lower detection limits and measurement error that vary across lake, species, and observation. By modeling speciated nitrogen, we obtain more resolved inference regarding sources of nitrogen and their relationship with complex environmental drivers. We illustrate the inferential benefits of our model using speciated nitrogen data from the LAke GeOSpatial and temporal database (LAGOS). 

About the speaker:

Erin Schliep is an Assistant Professor of Statistics at the University of Missouri. She completed her PhD at Colorado State University and was a postdoctoral fellow at Duke University prior to joining the faculty at Missouri. Her research focus is statistical methodology for multivariate, dependent data including spatial and spatio-temporal modeling.
 

You are encouraged to meet the speaker after the event. If interested please add your name and meeting location to this sheet. 

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