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Abstract In the Arctic waterbodies are abundant and rapid thaw of permafrost is destabilizing the carbon cycle and changing hydrology. It is particularly important to quantify and accurately scale aquatic carbon emissions in arctic ecosystems. Recently available high-resolution remote sensing datasets capture the physical characteristics of arctic landscapes at unprecedented spatial resolution. We demonstrate how machine learning models can capitalize on these spatial datasets to greatly improve accuracy when scaling waterbody CO₂and CH₄fluxes across the YK Delta of south-west AK. We found that waterbody size and contour were strong predictors for aquatic CO₂emissions, attributing greater than two-thirds of the influence to the scaling model. Small ponds (<0.001 km²) were hotspots of emissions, contributing fluxes several times their relative area, but were less than 5% of the total carbon budget. Small to medium lakes (0.001–0.1 km²) contributed the majority of carbon emissions from waterbodies. Waterbody CH₄emissions were predicted by a combination of wetland landcover and related drivers, as well as watershed hydrology, and waterbody surface reflectance related to chromophoric dissolved organic matter. When compared to our machine learning approach, traditional scaling methods that did not account for relevant landscape characteristics overestimated waterbody CO₂and CH₄emissions by 26%–79% and 8%–53% respectively. This study demonstrates the importance of an integrated terrestrial-aquatic approach to improving estimates and uncertainty when scaling C emissions in the arctic. 

{"Abstract":["This project is integrating scientific research in the Arctic with education and outreach, with a strong central focus on engaging undergraduate students and visiting faculty from groups that have had little involvement in Arctic science to date. The central element of the project is a month-long research expedition to the Yukon River Delta in Alaska. The expedition provides a deep intellectual and cultural immersion in the context of an authentic research experience that is paramount for "hooking" students and keeping them moving along the pipeline to careers as Arctic scientists. The overarching scientific issue that drives the research is the vulnerability and fate of ancient carbon stored in Arctic permafrost (permanently frozen ground). Widespread permafrost thaw is expected to occur this century, but large uncertainties remain in estimating the timing, magnitude, and form of carbon that will be released when thawed. Project participants are working in collaborative research groups to make fundamental scientific discoveries related to the vulnerability of permafrost carbon in the Yukon River Delta and the potential implications of permafrost thaw in this region for the global climate system.\n This data set contains pressure, Photosynthetically Active Radiation (PAR), air temperature, wind direction, wind speed, wind gust speed, rain, relative humidity, soil moisture at 15 centimeter (cm) depth, and two measurements of soil temperature at 15 cm depth from the 2018 and 2019 expeditions."]} 

Data from this study originate from the NSF (National Science Foundation) Polaris Project. The Polaris Project integrates scientific research in the Arctic-boreal region with education and outreach, with a primary focus on engaging and inspiring the next generation of scientists. The overarching scientific issue that drives the Polaris Project is the vulnerability and fate of ancient carbon stored in perennially frozen ground, permafrost. Although extensive permafrost thaw is expected to occur across the northern permafrost region this century, large uncertainties remain in the timing, magnitude, and form of carbon that will be released. Participants of the Polaris Project conducted field research in the Yukon-Kuskokwim Delta (YKD), collaborating to make fundamental scientific discoveries related to the transformation and fate of thawed permafrost carbon, and implications for global climate. This data set includes aquatic chemistry data from expeditions to the YKD during 2015–2019. Parameters measured include water temperature, pH, dissolved oxygen, conductivity, dissolved organic and inorganic carbon, nitrogen species, phosphorous, greenhouse gases, stables isotopes of carbon and water, optical properties of water, and fluxes of methane and carbon dioxide made in the field. These data were compiled and underwent quality assurance / quality control specifically for the scientific objectives of the manuscript published by Zolkos et al. (2022). Consequently, this dataset contains a modified version of Polaris Project YKD aquatic chemistry data previously published for 2015–2016 (http://doi.org/10.18739/A22804Z8M) and 2017 (http://doi.org/10.18739/A23775V7T). Data from 2018–2019 were not previously published. Therefore, users interested in the original datasets for 2015–2017 are encouraged to access them via the provided links, while users interested in the data and metadata specific to the associated manuscript by Zolkos et al. are encouraged to use this companion dataset. 

The Polaris Project, a National Science Foundation–funded program at the Woodwell Climate Research Center, aims to comprehensively address minority participation in climate and Arctic science research. Critical participant outcomes included development of interdisciplinary research projects, involvement in self-efficacy and advocacy experiences, and increased awareness and discussion of Arctic research careers. 

Abstract. Permafrost soils store between 1330 and 1580 Pg carbon (C), which is 3 times the amount of C in global vegetation, almost twice the amount of C in the atmosphere, and half of the global soil organic C pool. Despite the massive amount of C in permafrost, estimates of soil C storage in the high-latitude permafrost region are highly uncertain, primarily due to undersampling at all spatial scales; circumpolar soil C estimates lack sufficient continental spatial diversity, regional intensity, and replication at the field-site level. Siberian forests are particularly undersampled, yet the larch forests that dominate this region may store more than twice as much soil C as all other boreal forest types in the continuous permafrost zone combined. Here we present above- and belowground C stocks from 20 sites representing a gradient of stand age and structure in a larch watershed of the Kolyma River, near Chersky, Sakha Republic, Russia. We found that the majority of C stored in the top 1 m of the watershed was stored belowground (92 %), with 19 % in the top 10 cm of soil and 40 % in the top 30 cm. Carbon was more variable in surface soils (10 cm; coefficient of variation (CV)  =  0.35 between stands) than in the top 30 cm (CV  =  0.14) or soil profile to 1 m (CV  =  0.20). Combined active-layer and deep frozen deposits (surface – 15 m) contained 205 kg C m−2 (yedoma, non-ice wedge) and 331 kg C m−2 (alas), which, even when accounting for landscape-level ice content, is an order of magnitude more C than that stored in the top meter of soil and 2 orders of magnitude more C than in aboveground biomass. Aboveground biomass was composed of primarily larch (53 %) but also included understory vegetation (30 %), woody debris (11 %) and snag (6 %) biomass. While aboveground biomass contained relatively little (8 %) of the C stocks in the watershed, aboveground processes were linked to thaw depth and belowground C storage. Thaw depth was negatively related to stand age, and soil C density (top 10 cm) was positively related to soil moisture and negatively related to moss and lichen cover. These results suggest that, as the climate warms, changes in stand age and structure may be as important as direct climate effects on belowground environmental conditions and permafrost C vulnerability.