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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).more » « less
Abstract. The objective of this study was to upscale airborne flux measurements ofsensible heat and latent heat and to develop high-resolution flux maps. Inorder to support the evaluation of coupled atmospheric–land-surface models weinvestigated spatial patterns of energy fluxes in relation to land-surfaceproperties. We used airborne eddy-covariance measurements acquired by the Polar 5research aircraft in June–July 2012 to analyze surface fluxes.Footprint-weighted surface properties were then related to 21 529 sensibleheat flux observations and 25 608 latent heat flux observations using bothremote sensing and modeled data. A boosted regression tree technique wasused to estimate environmental response functions between spatially andtemporally resolved flux observations and corresponding biophysical andmeteorological drivers. In order to improve the spatial coverage and spatialrepresentativeness of energy fluxes we used relationships extracted acrossheterogeneous Arctic landscapes to infer high-resolution surface energy fluxmaps, thus directly upscaling the observational data. These maps of projectedsensible heat and latent heat fluxes were used to assess energy partitioningin northern ecosystems and to determine the dominant energy exchangeprocesses in permafrost areas. This allowed us to estimate energy fluxes forspecific types of land cover, taking into account meteorological conditions.Airborne and modeled fluxes were then compared with measurements from aneddy-covariance tower near Atqasuk. Our results are an important contribution for the advanced, scale-dependentquantification of surface energy fluxes and they provide new insights into theprocesses affecting these fluxes for the main vegetation types inhigh-latitude permafrost areas.more » « less
Climate change is affecting the Arctic at an unprecedented rate, potentially releasing substantial amounts of greenhouse gases (CO2 (carbon dioxide) and CH4 (Methane)) from tundra ecosystems. Measuring greenhouse gas emissions in the Arctic, particularly outside of the summer period, is very challenging due to extreme weather conditions. This research project provided the first annual balance of both CH4 and CO2 fluxes in a total of five sites spanning a 300Km transect across the North Slope of Alaska (three sites in Barrow, one site in Aquasuk, and one site in Ivotuk). The results from the continuous year-round CH4 fluxes across these sites showed how cumulative emissions for the cold season accounted on average for 50% of the annual budget (Zona et al., 2016), a notably higher contribution than previously modelled, and also higher than observed in boreal Alaska. The analysis of the cold period CH4 fluxes suggested that the presence of an unfrozen soil layer in the fall and early winter was a major control on cold season CH4 emissions (Zona et al., 2016). We also cross-compared all instruments measuring ecosystem scale CO2 and CH4 fluxes operating at our sites, which allowed us to make recommendation of the best performing instruments under these extreme weather conditions. The best performing instruments were closed path analyzers and intermittently heated sonic anemometers which had the highest final data cover. A continuously heated anemometer increased data coverage relative to non-heated anemometers, but resulted in an overestimation of the fluxes (Goodrich et al., 2016). We developed an intermittent heating strategy that was only activated when the data quality was low, and appeared to be the preferable method to prevent icing while avoiding biases to the measurements. Closed and open-path analyzers showed good agreement, but data coverage was much greater when using closed-path analyzers, especially during winter (Goodrich et al., 2016). Given the importance of vegetation on greenhouse gas emissions, we also investigated the role of different vegetation types under a broad range of environmental conditions on the CH4 emissions. We found that vegetation type can be a very useful tool to describe the spatial variability in CH4 emissions over the landscape (McEwing et al., 2015), and that just two vegetation types were able to explain about 50% of the variability in CH4 fluxes across ecosystems even hundreds of kilometers apart (Davidson et al., 2016a). To upscale these plot scale fluxes we completed high resolution vegetation maps in each of our tower sites (Davidson et al., 2016b), which are the finest resolution maps currently available from these sites, and also contributed to larger scale mapping effort (Walker et al., 2016). The soil microbial analysis from soil cores collected across our sites showed an association between overall microbial diversity and latitude, with a higher diversity found in the northerly site and lower diversity in the southerly site, contrary to current knowledge (Wagner et al., accepted). We also measured CH4 and CO2 concentrations in the soil, which showed to be orders of magnitude higher than in the atmosphere (Arndt et al., 2016). Our results contributed to model development (Xu et al., 2016; Kobayashi et al., 2016; Liljedahl et al., 2016; Luus et al., 2017), and to a wide variety of other projects as shown by the hundreds of download of our data from Ameriflux. Overall, this grant resulted in the publication of 25 peer reviewed journal articles, including in high impact factor journals such as PNAS (Proceedings of the National Academy of Sciences of the United States of America), and Nature Climate Change, in addition to five more in review and in preparation, and supported the research of seven PhD students, two master students, and ten undergraduate students.more » « less
In the western USA, shifts from snow to rain precipitation regimes and increases in western juniper cover in shrub‐dominated landscapes can alter surface water input via changes in snowmelt and throughfall. To better understand how shifts in both precipitation and semi‐arid vegetation cover alter above‐ground hydrological processes, we assessed how rain interception differs between snow and rain surface water input; how western juniper alters snowpack dynamics; and how these above‐ground processes differ across western juniper, mountain big sagebrush and low sagebrush plant communities. We collected continuous surface water input with four large lysimeters, interspace and below‐canopy snow depth data and conducted periodic snow surveys for two consecutive water years (2013 and 2014). The ratio of interspace to below‐canopy surface water input was greater for snow relative to rain events, averaging 79.4% and 54.8%, respectively. The greater surface water input ratio for snow is in part due to increased deposition of redistributed snow under the canopy. We simulated above‐ground energy and water fluxes in western juniper, low sagebrush and mountain big sagebrush for two 8‐year periods under current and projected mid‐21st century warmer temperatures with the Simultaneous Heat and Water (SHAW) model. Juniper compared with low and mountain sagebrush reduced surface water input by an average of 138 mm or 24% of the total site water budget. Conversely, warming temperatures reduced surface water input by only an average of 14 mm across the three vegetation types. The future (warmer) simulations resulted in earlier snow disappearance and surface water input by 51 and 45 days, respectively, across juniper, low sagebrush and mountain sagebrush. Information from this study can help land managers in the sagebrush steppe understand how both shifts in climate and semi‐arid vegetation will alter fundamental hydrological processes. Copyright © 2016 John Wiley & Sons, Ltd.
How do plant communities on zonal loamy vs. sandy soils vary across the full maritime Arctic bioclimate gradient? How are plant communities of these areas related to existing vegetation units of the European Vegetation Classification? What are the main environmental factors controlling transitions of vegetation along the bioclimate gradient?
1700‐km Eurasia Arctic Transect (EAT), Yamal Peninsula and Franz Josef Land (FJL), Russia.
The Braun‐Blanquet approach was used to sample mesic loamy and sandy plots on 14 total study sites at six locations, one in each of the five Arctic bioclimate subzones and the forest–tundra transition. Trends in soil factors, cover of plant growth forms (PGFs) and species diversity were examined along the summer warmth index (SWI) gradient and on loamy and sandy soils. Classification and ordination were used to group the plots and to test relationships between vegetation and environmental factors.
Clear, mostly non‐linear, trends occurred for soil factors, vegetation structure and species diversity along the climate gradient. Cluster analysis revealed seven groups with clear relationships to subzone and soil texture. Clusters at the ends of the bioclimate gradient (forest–tundra and polar desert) had many highly diagnostic taxa, whereas clusters from the Yamal Peninsula had only a few. Axis 1 of a DCA was strongly correlated with latitude and summer warmth; Axis 2 was strongly correlated with soil moisture, percentage sand and landscape age.
Summer temperature and soil texture have clear effects on tundra canopy structure and species composition, with consequences for ecosystem properties. Each layer of the plant canopy has a distinct region of peak abundance along the bioclimate gradient. The major vegetation types are weakly aligned with described classes of the European Vegetation Checklist, indicating a continuous floristic gradient rather than distinct subzone regions. The study provides ground‐based vegetation data for satellite‐based interpretations of the western maritime Eurasian Arctic, and the first vegetation data from Hayes Island, Franz Josef Land, which is strongly separated geographically and floristically from the rest of the gradient and most susceptible to on‐going climate change.