Summer methane ebullition from a headwater catchment in Northeastern Siberia

Streams and rivers are active processors of terrestrial carbon and significant sources of carbon dioxide (CO2) and methane (CH4) to the atmosphere. Recent studies suggest that ebullition may represent a sizable yet overlooked component of the total CH4 flux from these systems; however, there are no published CH4 ebullition estimates for streams or rivers in subarctic or arctic biomes, regions that store vast quantities of vulnerable, old organic carbon in permafrost soils. We quantified CH4 ebullition from headwater streams in a small arctic watershed in Northeastern Siberia. Ebullitive emissions were 0.64 mmol m-2 d-1, which is lower than the global average but approximately 2 times greater than the pan-arctic diffusive CH4 flux estimate reported in a recent synthesis of global freshwater CH4 emissions. The high CO2:CH4 of sediment bubbles (0.52) suggests that methane emissions may currently be constrained by resource competition between methanogens and microbes using more efficient metabolic strategies. Furthermore, the magnitude and frequency of ebullition events were greater as temperatures increased, suggesting that ebullition from streams could become a more prominent component of the regional CH4 flux in a warmer future

A land-to-ocean perspective on the magnitude, source and implication of DIC flux from major Arctic rivers to the Arctic Ocean

Author Posting. © American Geophysical Union, 2012. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 26 (2012): GB4018, doi:10.1029/2011GB004192.A series of seasonally distributed measurements from the six largest Arctic rivers (the Ob', Yenisey, Lena, Kolyma, Yukon and Mackenzie) was used to examine the magnitude and significance of Arctic riverine DIC flux to larger scale C dynamics within the Arctic system. DIC concentration showed considerable, and synchronous, seasonal variation across these six large Arctic rivers, which have an estimated combined annual DIC flux of 30 Tg C yr−1. By examining the relationship between DIC flux and landscape variables known to regulate riverine DIC, we extrapolate to a DIC flux of 57 ± 9.9 Tg C yr−1for the full pan-arctic basin, and show that DIC export increases with runoff, the extent of carbonate rocks and glacial coverage, but decreases with permafrost extent. This pan-arctic riverine DIC estimate represents 13–15% of the total global DIC flux. The annual flux of selected ions (HCO3−, Na+, Ca2+, Mg2+, Sr2+, and Cl−) from the six largest Arctic rivers confirms that chemical weathering is dominated by inputs from carbonate rocks in the North American watersheds, but points to a more important role for silicate rocks in Siberian watersheds. In the coastal ocean, river water-induced decreases in aragonite saturation (i.e., an ocean acidification effect) appears to be much more pronounced in Siberia than in the North American Arctic, and stronger in the winter and spring than in the late summer. Accounting for seasonal variation in the flux of DIC and other major ions gives a much clearer understanding of the importance of riverine DIC within the broader pan-arctic C cycle.Funding for this work was provided through NSF-OPP-0229302 and NSF-OPP-0732985. Additional support to SET was provided by an NSERC Postdoctoral Fellowship.2013-06-1

Canadian Arctic Archipelago Rivers Project Geochemical Data 2014-2016

This data set describes geochemical samples collected from 25 rivers and 11 lakes throughout the Canadian Arctic Archipelago (CAA). CAA rivers were sampled as part of the Canadian Arctic Archipelago Rivers Program (CAA-RP) and the Canadian Arctic GEOTRACES program with access via land, water, and air during the summer seasons of August 1-September 9, 2014, and August 11-19, 2015. Time series observations were also collected from the Coppermine River in Kugluktuk, Nunavut (NU) (year-round; August 5, 2014 to August 23, 2016), and from Freshwater Creek in Cambridge Bay, NU (open water only; June 19, 2014 to September 16, 2016). Lake samples were collected opportunistically during float plane air-surveys in 2014 and 2015 as part of the CAA-RP study in the southern CAA. Precipitation was collected during two significant rain events in Kugluktuk, NU (August 25, 2015) and Cambridge Bay, NU (August 20, 2016). River water samples were collected according to methods developed by the Arctic Great Rivers Observatory (Arctic-GRO; http://www.arcticgreatrivers.org/); lake sampling followed the same general methods, with collection carried out in deeper waters away from the shore; rain samples were collected using an HCl cleaned plastic box and processed immediately the morning following the rain event in order to limit the influences of evaporation. Sampling and analytical methods are described in detail in Brown et al., 2020. This data set includes the raw data supplied in Supplementary Tables S2 (Geochemical Data for the CAA-Rivers Project, collected from 2014 - 2016) and S3 (Geochemical Time Series Data for the Coppermine River and Freshwater Creek collected from 2014 - 2016) that accompany Brown et al., 2020. In addition to geochemical observations, the following calculated parameters can be found in Supplementary Table S2 of Brown et al., 2020: drainage basin area; predominant bedrock lithology; percent coverage of lakes; and surficial geology characteristics. These parameters were determined for each river drainage basin as described in the text and associated references found in Brown et al., 2020

A global map of mangrove forest soil carbon at 30m spatial resolution

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kgm*3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86?729 Mg C ha*1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30?122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies