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Exploring the Suitability of Ecosystem Metabolomes to Assess Imprints of Brownification and Nutrient Enrichment on Lakes
Author(s) -
Fonvielle Jeremy A.,
Giling Darren P.,
Dittmar Thorsten,
Berger Stella A.,
Nejstgaard Jens C.,
Lyche Solheim Anne,
Gessner Mark O.,
Grossart HansPeter,
Singer Gabriel
Publication year - 2021
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1029/2020jg005903
Subject(s) - ecosystem , nutrient , colored dissolved organic matter , metabolome , dissolved organic carbon , lake ecosystem , environmental science , environmental chemistry , organic matter , aquatic ecosystem , ecology , metabolomics , chemistry , biology , phytoplankton , chromatography
Loadings of colored dissolved organic matter (cDOM) and nutrients affect lake ecosystem functioning in opposite ways, rendering assessments of combined effects challenging. We used the “ecosystem metabolome” as a conceptual framework to overcome this problem by characterizing the chemically diverse pool of DOM in lakes. The underlying rationale is that the diversity of dissolved metabolites bears the legacy of allochthonous inputs, autochthonous primary production, and a wealth of organic matter transformations resulting from microbial or photodegradation. Our objective was to assess whether high‐resolution mass‐spectrometric analyses can unlock that information on DOM origin and transformation pathways as well as environmental drivers imprinting the lake ecosystem metabolome. We performed a large‐scale enclosure experiment to assess the influences of brownification and nutrient enrichment on the composition and diversity of DOM, and a complementary bottle incubation to isolate the effect of photodegradation. For validation, we assessed whether the same patterns emerge from published observational data from 109 Swedish lakes. Ultra‐high‐resolution mass spectrometry distinguished ∼3000 metabolites in solid‐phase extracts of lake water. Network analysis revealed five metabolite clusters that could be related to different source processes based on molecular weight, position in van Krevelen diagrams and assignment to molecular categories (peptides, lipids, etc.). Emergent DOM properties such as molecular diversity provided insights into the processes generating each of the five DOM clusters. Overall, our data suggest that the thousands of molecular formulas comprising ecosystem metabolomes of lakes arise from few major processes and reflect imprints of environmental drivers such as brownification and nutrient enrichment.