Digging deeper: Development and application of an untargeted exometabolomics approach to identify biogeochemical hotspots of dissolved organic matter vulnerability in Arctic soils

Arctic soils contain vast reserves of carbon (C) that, with rising temperatures, may become a significant source of greenhouse gases (GHGs) (i.e. CO₂, CH₄, N₂O) due to increased microbial decomposition of soil organic matter (SOM). However, there are significant spatial variations in GHG production that lead to hotspots of C release across the landscape, creating significant uncertainty in climate models. Reliably predicting the magnitude of C loss via microbial production of GHGs, and the proportion lost as either CO₂ or CH₄, depends on many factors, including soil temperature and moisture, microbial community structure and function, as well as the composition and availability of the most labile SOM pool—low molecular weight dissolved organic matter (LMW DOM). While the effects of temperature and moisture on GHG production in Arctic soils have been studied extensively, there is a dearth of information on the effects of LMW DOM chemistry and its potential to be a predictive chemical signal of biological hotspots of C release, in large part due to unique analytical challenges. LMW DOM is an incredibly complex and dynamic mixture of small molecules from both biotic and abiotic origin that turnover on the order of days or even hours and are obscured by countless other interfering signals in the soil, each a complicating factor in isolation, detection, and quantitation. Recent advancements in liquid chromatography mass spectrometry (LC/MS) have provided a means for sensitive, robust, and high-throughput measurements of LMW DOM composition and availability but have not yet been applied in Arctic soils. In this dissertation, an untargeted LC/MS approach for characterizing LMW DOM availability was developed and evaluated, benchmarking its analytical performance in Arctic soils for the first time. The optimized approach was then applied to soils from two Arctic ecosystems to measure variations in LMW DOM across the landscape, due to soil depth, aboveground vegetation, topography, or level of degradation due to thaw. In addition to establishing the LC/MS measurements and data interpretation, this dissertation also had several key interdisciplinary components including remote-location field sample collection, establishing an accessible data analysis pipeline, and examining this work from a public policy perspective.