A continental scale spatial investigation of lake sediment organic compositions using sedimentomics

Sedimentomics is a new method used to investigate carbon cycling in sediment organic matter. This untargeted method, based on metabolomics workflows, was used to investigate the molecular composition of sediment organic matter across northern Canada (Nunavut and Northwest Territories). Unique "lake districts" were defined using unsupervised clustering based on changes in sediment organic carbon compositions across space. Supervised machine learning analyses were used to compare the "lake districts" to commonly used regional classification systems like the treeline, ecozones, and/or georegions. Treeline was the best model to explain the compositional variance of sediment organic carbon from lakes across Canada, closely followed by the georegions model. A novel sediment metaphenomics analysis was also applied to determine how well environmental constraints explain the variation of sediment organic matter composition across a continent. We determined that sedimentomics is more informative than traditional measurements (such as total organic carbon) and can be integrated with other "omics" techniques.