Abstract. Methane (CH4) emissions from the boreal and arcticregion are globally significant and highly sensitive to climate change.There is currently a wide range in estimates of high-latitude annualCH4 fluxes, where estimates based on land cover inventories andempirical CH4 flux data or process models (bottom-up approaches)generally are greater than atmospheric inversions (top-down approaches). Alimitation of bottom-up approaches has been the lack of harmonizationbetween inventories of site-level CH4 flux data and the land coverclasses present in high-latitude spatial datasets. Here we present acomprehensive dataset of small-scale, surface CH4 flux data from 540terrestrial sites (wetland and non-wetland) and 1247 aquatic sites (lakesand ponds), compiled from 189 studies. The Boreal–Arctic Wetland and LakeMethane Dataset (BAWLD-CH4) was constructed in parallel with acompatible land cover dataset, sharing the same land cover classes to enablerefined bottom-up assessments. BAWLD-CH4 includes information onsite-level CH4 fluxes but also on study design (measurement method,timing, and frequency) and site characteristics (vegetation, climate,hydrology, soil, and sediment types, permafrost conditions, lake size anddepth, and our determination of land cover class). The different land coverclasses had distinct CH4 fluxes, resulting from definitions that wereeither based on or co-varied with key environmental controls. Fluxes ofCH4 from terrestrial ecosystems were primarily influenced by watertable position, soil temperature, and vegetation composition, while CH4fluxes from aquatic ecosystems were primarily influenced by watertemperature, lake size, and lake genesis. Models could explain more of thebetween-site variability in CH4 fluxes for terrestrial than aquaticecosystems, likely due to both less precise assessments of lake CH4fluxes and fewer consistently reported lake site characteristics. Analysisof BAWLD-CH4 identified both land cover classes and regions within theboreal and arctic domain, where future studies should be focused, alongsidemethodological approaches. Overall, BAWLD-CH4 provides a comprehensivedataset of CH4 emissions from high-latitude ecosystems that are usefulfor identifying research opportunities, for comparison against new fielddata, and model parameterization or validation. BAWLD-CH4 can bedownloaded from https://doi.org/10.18739/A2DN3ZX1R (Kuhn et al., 2021).
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The Boreal–Arctic Wetland and Lake Dataset (BAWLD)
Abstract. Methane emissions from boreal and arctic wetlands, lakes, and rivers areexpected to increase in response to warming and associated permafrost thaw.However, the lack of appropriate land cover datasets for scalingfield-measured methane emissions to circumpolar scales has contributed to alarge uncertainty for our understanding of present-day and future methaneemissions. Here we present the Boreal–Arctic Wetland and Lake Dataset(BAWLD), a land cover dataset based on an expert assessment, extrapolatedusing random forest modelling from available spatial datasets of climate,topography, soils, permafrost conditions, vegetation, wetlands, and surfacewater extents and dynamics. In BAWLD, we estimate the fractional coverage offive 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 usingcriteria that ensured distinct methane emissions among classes, as indicatedby a co-developed comprehensive dataset of methane flux observations. InBAWLD, 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 wetlandclasses, covering ∼ 28 % each of the total wetland area,while the highest-methane-emitting marsh and tundra wetland classes occupied5 % and 12 %, respectively. Lakes, defined to include all lentic open-waterecosystems 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 lakearea, while high-emitting peatland and yedoma lakes covered 18 % and 4 %,respectively. Small (<0.1 km2) glacial, peatland, and yedomalakes combined covered 17 % of the total lake area but contributeddisproportionally to the overall spatial uncertainty in lake area with a95 % 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 withhigh-methane-emitting headwaters that drain organic-rich landscapes.Distinct combinations of spatially co-occurring wetland and lake classeswere identified across the BAWLD domain, allowing for the mapping of“wetscapes” that have characteristic methane emission magnitudes andsensitivities to climate change at regional scales. With BAWLD, we provide adataset which avoids double-accounting of wetland, lake, and river extentsand which includes confidence intervals for each land cover class. As such,BAWLD will be suitable for many hydrological and biogeochemical modellingand upscaling efforts for the northern boreal and arctic region, inparticular those aimed at improving assessments of current and futuremethane emissions. Data are freely available athttps://doi.org/10.18739/A2C824F9X (Olefeldt et al., 2021).
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- NSF-PAR ID:
- 10311706
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Date Published:
- Journal Name:
- Earth System Science Data
- Volume:
- 13
- Issue:
- 11
- ISSN:
- 1866-3516
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Wetlands in Arctic drained lake basins (DLBs) have a high potential for carbon storage in vegetation and peat as well as for elevated greenhouse gas emissions. However, the evolution of vegetation and organic matter is rarely studied in DLBs, making these abundant wetlands especially uncertain elements of the permafrost carbon budget. We surveyed multiple DLB generations in northern Alaska with the goal to assess vegetation, microtopography, and organic matter in surface sediment and pond water in DLBs and to provide the first high-resolution land cover classification for a DLB system focussing on moisture-related vegetation classes for the Teshekpuk Lake region. We associated sediment properties and methane concentrations along a post-drainage succession gradient with remote sensing-derived land cover classes. Our study distinguished five eco-hydrological classes using statistical clustering of vegetation data, which corresponded to the land cover classes. We identified surface wetness and time since drainage as predictors of vegetation composition. Microtopographic complexity increased after drainage. Organic carbon and nitrogen contents in sediment, and dissolved organic carbon (DOC) and dissolved nitrogen (DN) in ponds were high throughout, indicating high organic matter availability and decomposition. We confirmed wetness as a predictor of sediment methane concentrations. Our findings suggest moderate to high methane concentrations independent of drainage age, with particularly high concentrations beneath submerged patches (up to 200
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/essd-13-5127-2021
