EGU21-7804, updated on 19 Mar 2021
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Complex interactions of in-stream DOM and nutrient spiralling unravelled by Bayesian regression analysis

Matthias Pucher1,2, Peter Flödl3, Daniel Graeber4, Klaus Felsenstein5, Thomas Hein1,2, and Gabriele Weigelhofer1,2
Matthias Pucher et al.
  • 1University of Natural Resources and Life Sciences, Institute of Hydrobiology and Aquatic Ecosystem Management, Department of Water - Atmosphere - Environment, Wien, Austria (
  • 2WasserClusterLunz – Biologische Station GmbH, Lunz am See, Austria
  • 3Institute of Hydraulic Engineering and River Research, University of Natural Resources and Life Sciences, Vienna, Austria
  • 4Department Aquatic Ecosystem Analysis and Management (ASAM), Helmholtz Centre for Environmental Research – UFZ, Magdeburg, Germany
  • 5Department of Statistics, Vienna University of Technology, Vienna, Austria

The carbon cycle in aquatic environments is of high interest because of its effects on water quality and greenhouse gas production as well as its alteration through anthropogenic activities with unknown outcomes. Uptake and release of dissolved organic matter (DOM) compounds is depending on the molecular structure and is strongly linked to N and P dynamics. Current research has not fully revealed the complex patterns behind.

To investigate the interactions between DOM components, we performed ten plateau addition experiments with different, realistic, complex DOM leachates (cow dung, pig dung, corn, leaves and nettles) in a small stream. The DOM quality was determined by fluorescence measurements and parallel factor (PARAFAC) decomposition and the nutrient concentrations were measured at eleven consecutive points in the stream at plateau conditions. The hydrological transport processes were incorporated by using the results of a 1-D hydrodynamic model.

The nutrient spiralling concept and its application in nutrient dynamics is a valuable basis for the analysis of our data. However, we could not find a data analysis approach, that suited the nature of our questions and data. Based on previously observed nutrient uptake models, we extended the nutrient spiralling concept by additional non-linear terms to analyse interactions between different DOM components.

We developed the “Interactions in Nutrient Spirals using BayesIan REgression (INSBIRE)” approach to analyse DOM uptake and retention mechanism. This approach can disentangle complex and interacting biotic and abiotic drivers in nutrient uptake metrics, show their variability and quantify their error distribution. We successfully used INSBIRE to show DOM-compound-specific interactions and draw conclusions from the data of our experiment. The applicability of INSBIRE has still to be tested in other studies, but we see a high potential not only in DOM dynamics but any kind of solute dynamics where interactions are crucial.

How to cite: Pucher, M., Flödl, P., Graeber, D., Felsenstein, K., Hein, T., and Weigelhofer, G.: Complex interactions of in-stream DOM and nutrient spiralling unravelled by Bayesian regression analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7804,, 2021.


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