High-resolution mass spectrometry (HRMS) has become a vital tool for dissolved organic matter (DOM) characterization. The upward trend in HRMS analysis of DOM presents challenges in data comparison and interpretation among laboratories operating instruments with differing performance and user operating conditions. It is therefore essential that the community establishes metric ranges and compositional trends for data comparison with reference samples so that data can be robustly compared among research groups. To this end, four identically prepared DOM samples were each measured by 16 laboratories, using 17 commercially purchased instruments, using positive-ion and negative-ion mode electrospray ionization (ESI) HRMS analyses. The instruments identified~1000 common ions in both negative-and positive-ion modes over a wide range of m/z values and chemical space, as determined by van Krevelen diagrams. Calculated metrics of abundance-weighted average indices (H/C, O/C, aromaticity, and m/z) of the commonly detected ions showed that hydrogen saturation and aromaticity were consistent for each reference sample across the instruments, while average mass and oxygenation were more affected by differences in instrument type and settings. In this paper we present 32 metric values for future benchmarking. The metric values were obtained for the four different parameters from four samples in two ionization modes and can be used in future work to evaluate the performance of HRMS instruments.
Soils export large amounts of organic matter to rivers, and there are still major uncertainties concerning the composition and reactivity of this material and its fate within the fluvial network. Here we reconstructed the pattern of movement and processing of dissolved organic matter (DOM) along a soil‐stream‐river continuum under summer baseflow conditions in a boreal region of Québec (Canada), using a combination of fluorescence spectra, size exclusion chromatography and ultrahigh resolution mass spectrometry. Our results show that there is a clear sequence of selective DOM degradation along the soil‐stream‐river continuum, which results in pronounced compositional shifts downstream. The soil‐stream interface was a hot spot of DOM degradation, where biopolymers and low molecular weight (LMW) compounds were selectively removed. In contrast, processing in the stream channel was dominated by the degradation of humic‐like aromatic DOM, likely driven by photolysis, with little further degradation of either biopolymers or LMW compounds. Overall, there was a high degree of coherence between the patterns observed in DOM chemical composition, optical properties, and molecular profiles, and none of these approaches pointed to measurable production of new DOM components, suggesting that the DOM pools removed during transit were likely mineralized to CO2. Our first order estimates suggest that rates of soil‐derived DOM mineralization could potentially sustain over half of the measured CO2 emissions from this stream network, with mineralization of biopolymers and humic substances contributing roughly equally to these fluvial emissions.
Abstract. Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Boreal–Arctic Wetland and Lake Dataset (BAWLD), a land cover dataset based on an expert assessment, extrapolated using random forest modelling from available spatial datasets of climate, topography, soils, permafrost conditions, vegetation, wetlands, and surface water extents and dynamics. In BAWLD, we estimate the fractional coverage of five wetland, seven lake, and three river classes within 0.5 × 0.5∘ grid cells that cover the northern boreal and tundra biomes (17 % of the global land surface). Land cover classes were defined using criteria that ensured distinct methane emissions among classes, as indicated by a co-developed comprehensive dataset of methane flux observations. In BAWLD, wetlands occupied 3.2 × 106 km2 (14 % of domain) with a 95 % confidence interval between 2.8 and 3.8 × 106 km2. Bog, fen, and permafrost bog were the most abundant wetland classes, covering ∼ 28 % each of the total wetland area, while the highest-methane-emitting marsh and tundra wetland classes occupied 5 % and 12 %, respectively. Lakes, defined to include all lentic open-water ecosystems regardless of size, covered 1.4 × 106 km2 (6 % of domain). Low-methane-emitting large lakes (>10 km2) and glacial lakes jointly represented 78 % of the total lake area, while high-emitting peatland and yedoma lakes covered 18 % and 4 %, respectively. Small (<0.1 km2) glacial, peatland, and yedoma lakes combined covered 17 % of the total lake area but contributed disproportionally to the overall spatial uncertainty in lake area with a 95 % confidence interval between 0.15 and 0.38 × 106 km2. Rivers and streams were estimated to cover 0.12 × 106 km2 (0.5 % of domain), of which 8 % was associated with high-methane-emitting headwaters that drain organic-rich landscapes. Distinct combinations of spatially co-occurring wetland and lake classes were identified across the BAWLD domain, allowing for the mapping of “wetscapes” that have characteristic methane emission magnitudes and sensitivities to climate change at regional scales. With BAWLD, we provide a dataset which avoids double-accounting of wetland, lake, and river extents and which includes confidence intervals for each land cover class. As such, BAWLD will be suitable for many hydrological and biogeochemical modelling and upscaling efforts for the northern boreal and arctic region, in particular those aimed at improving assessments of current and future methane emissions. Data are freely available at https://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).
The boreal biome is characterized by extremely dense and complex fluvial networks that are closely coupled to land. Reconstructing the role that these fluvial networks play in regional carbon (C) budgets requires identifying landscape and environmental drivers of riverine C that operate at the whole network scale and that can be applied across landscapes. Here we explore drivers of CO2, CH4, and dissolved organic (DOC) and inorganic C (DIC) across 190 streams and rivers spanning 8 Strahler orders over an area of 500,000 km2 of heterogeneous boreal landscape in Québec, focusing on those drivers that can be readily obtained from remote sensing data. Each C species (except DIC) could be modeled as a function of a proximal network‐scale property, such as flow distance or elevation, but adding regional structure to these models greatly improved predictions. These modeled regional effects were similar for DOC, CO2, and CH4 and were strongly related to average regional soil organic content and especially to NPP, the latter integrating regional differences in climate and other environmental factors. These results suggest that there may be regional C baselines determined by a combination of landscape and climate features, which simultaneously influence the average CO2, DOC, and CH4 within fluvial networks, albeit through different underlying mechanisms and with varying degrees of influence on each C species. The latter two C species appear to be more sensitive to regional differences in soil, NPP, and climate than CO2 or DIC, and therefore more likely to shift under future scenarios of change in northern landscapes.
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