Project

Metatranscriptomics; Denitrification; Lake Models; Organic nitrogen compounds; Nitrogen; Lakes; 15N Stable Isotope; Organic matter mineralization; Microbial ecology; Anammox

Lead
Die Regulation des Stickstoffs in SeenDer natürliche Stickstoffkreislauf wird heute durch den Menschen mehr als verdoppelt, mit gravierenden Folgen für die Atmosphäre, Böden, Oberflächen- und Grundwasser. Besonders betroffen sind die Küstengewässer, bei welchen das Algenwachstum, anders als in Seen, oft durch den Stickstoff begrenzt wird. Auf dem Weg zu den Meeren funktionieren die Seen wie reinigende Organe, die einen Teil der Stickstofffracht durch Denitrifikation entfernen (gelöstes Nitrat wird in Luftstickstoff umgesetzt). Obwohl die Nettoeffekte recht gut quantifizierbar sind, weiss man über die Prozesse und die mikrobiellen Akteure die dahinterstehen noch wenig Bescheid.
Lay summary
In diesem Projekt werden wir untersuchen, wie die unterschiedlichen Bedingungen in Seen die Umsetzungen von Stickstoffverbindungen beeinflussen. Eine grundsätzliche Rolle spielt dabei die Unterscheidung von nährstoffreichen und nährstoffarmen Seen, die verschiedenen Tiefenzonen in Seen und die Jahreszeitlichen Veränderungen. In einem multidisziplinären Ansatz werden wir geochemische Bedingungen und mikrobiologische Abbauwege der Stickstoffumsetzungen im Detail untersuchen. Die Ergebnisse werden in einem physikalisch-biogeochemischen Seenmodell implementiert, welches die Verallgemeinerung der aus unseren Untersuchungen gewonnenen Daten erlaubt. Die Kenntnis der Wirkung spezifischer Einflussfaktoren auf Prozessraten und mikrobielle Populationen wird eine grosse Hilfe für die Interpretation und Anpassung der (weltweit) kontinuierlich erhobenen Daten aus Seeuntersuchungen sein. Die Ergebnisse erlauben sowohl eine Abschätzung der Kapazität der Seen bei der Elimination von Stickstoff als auch der Bildung von ozonrelevantem Lachgas (N2O).

Direct link to Lay Summary

Last update: 27.09.2016

NCBI BioProject PRJNA644886:

Author	Baumann, Kathrin
Publication date	08.07.2020
Persistent Identifier (PID)	PRJNA644886
Repository	NCBI - SRA
Abstract

16SrRNA sequence data Lake Tanganyika (Callbeck et al 2021)

NCBI BioProject PRJNA675607

Author	Baumann, Kathrin
Persistent Identifier (PID)	PRJNA675607
Repository	NCBI - SRA
Abstract

4 Surface water Metagenomes Lake Tanganyika (Ehrenfels et al 2021)

Active participation

Communication	Title	Media	Place	Year

Title	Year

Number	Title	Start	Funding scheme

We intend to implement a generalizable mechanistic model for nitrogen (N) transformation, and specifically N removal, in lakes. The N cycle is characterized by an enormous diversity of chemical forms and pathways prevailing under varying conditions. However, in practice, only few of these may be relevant to describe net changes and transformation rates in lakes. The challenge is to obtain an understanding of processes that are dominant in nutrient rich and nutrient poor lakes. This in turn requires a prioritization of key indicators based on a critical evaluation of the essential system parameters that need to be observed to adequately predict net effects. The knowledge of these parameters would help to increase the reliability of generalizations and would allow to use existing monitoring data for the interpretation of N removal capacities of different systems. Here we propose a multidisciplinary approach that will fill major gaps in our understanding of the major geochemical and microbial N transformation pathways and rates, their distribution pattern in lakes in time and space, and how the ‘macroscopic’ view (whole lake mass balance approach) and ‘microscopic view (under-standing of individual processes and rates) are linked. This proposal seeks funding for two PhD students that will work together on two lakes with different trophic states and surveys of a larger number of Swiss lakes. Geochemical tasks comprise (i) the experimental characterization of specific N-transformation processes and quantification of rates on sediment cores collected from different lake depths and seasons in these two lakes, (ii) determination of N removal rates from mass balances of the hypolimnia of the two lakes, and comparison with direct analyses of the specific process rates, (iii) estimation of areal N-removal rates for ~10 additional lakes with a mass balance approach based on 20-50 years of monitoring data. Results will be com-pared with the detailed mass balances and bias with estimations from monitoring data sets discussed.Microbiological tasks include (i) characterization of the microbial communities and functional genes involved in N-transformation processes at the selected locations and seasons in the two experimental lakes using quantitative molecular approaches and shotgun-metatranscriptomics, and characterization of the con-trolling environmental factors (ii) assessment of microbial communities in ~10 additional lakes in relation to the quality of organic matter and estimated hypolimnetic N-removal rates, and (iii) provision of experimental evidence for the importance of organic matter quantity and quality in controlling both process rates and the microbial community composition in lake sediments. This multidisciplinary approach will create a unique dataset that will facilitate interpretation and contextualization of disciplinary results. Geochemical and modeling perspectives will benefit from information on the microbial communities, their changes and physiological reactions in response to the environment. Microbiological results can either confirm that simple assumptions on process controls are sufficient, or may indicate how simple models should be amended to take biological response into account. The interpretation of microbial ecology in turn stands and falls with the quality of information on the physico-chemical environment and the actual process rates, and will therefore also profit from the disciplinary interaction. Together, both disciplinary views provide the basis to build a lake-scale mechanistic model of N removal grounded not simply in empirically observed correlations but in actual understanding of the underlying processes and their controls. The implementation of a one-dimensional coupled physical-biogeochemical lake model for the two lakes will aim at (i) assessing the capability of different parameterizations for the individual contributions of the lake-internal N cycle to reproduce the observation in the lakes, (ii) quantifying different process rates and fluxes involved in the N cycle, and (iii) assessing uncertainties based on the observations and modeling approach.