A continental scale spatial investigation of sediment organic matter for ecological classification

Abstract:

Lake sediments are a natural record of biodiversity because they are archives of natural organic materials derived from plants, animals, microbes, and geological processes in the catchment. We used surface sediments from 61 lakes to examine the composition of natural organic matter across northern Canada. Samples were extracted using a metabolomics-derived untargeted method and analyzed using high resolution mass spectrometry to determine their sedimentary molecular composition. Machine learning clustering analyses were then to define regional lake districts, and to overlay current spatial classification systems (i.e. ecozones) onto the distribution of sediment organic matter. Our work represents a first-of-its-kind analysis of the composition of organic carbon molecules in lake sediments across a large geographical extent using a new sedimentomics technique. This presentation highlights the power of sedimentomics to define regional and ecological boundaries, to investigate climate change, and it can be integrated with other research fields like metagenomics to build more informative models on carbon cycling.