Statistics Across Campuses: Erin Schliep -- Bayesian hierarchical modeling and data fusion for multivariate speciated nitrogen in lakes

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

Date: 30 October 2020, Friday 

Time: 10am 

Speaker: Dr Erin Schliep (University of Missouri) 

Abstract: 

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).  

Link: https://au.bbcollab.com/guest/fcf219c74ac743e89565a9e6e8d349a9