Long-Term Release of Carbon Dioxide from Arctic Tundra Ecosystems in Alaska

Euskirchen, Eugénie; Bret‐Harte, M. Syndonia; Shaver, Gaius R.; Edgar, C.; Romanovsky, V. E.

doi:10.1007/s10021-016-0085-9

Cited by 132 publications

(161 citation statements)

References 49 publications

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“…CC BY 4.0 License. loops (Post et al, 1982;Elberling et al, 2008;Chae et al, 2015;Christiansen, 2016;Euskirchen et al, 2016). In this study, the 2016 growing season saw the wetland plot shift from being an early season source to a late season sink.…”

Section: Comparing the Influence Of Abiotic Conditions And Nitrogen Amentioning

confidence: 68%

“…Short-term studies of Arctic tundra environments are suggesting that Arctic permafrost regions currently act as sinks of atmospheric and terrestrial C (Nobrega and Grogan, 2008;Lafleur et al, 2012;McGuire et al, 2012); however, the comprehensive C study by McGuire et al (2012) also determined 10 that the tundra has been neutral in recent decades. Generally, long-term C studies are still lacking across the High Arctic tundra (Euskirchen et al, 2016). A long-term study by Euskirchen et al (2016) found that increases in air and soil temperatures at multiple depths may trigger a new trajectory of CO2 release.…”

mentioning

confidence: 99%

“…Generally, long-term C studies are still lacking across the High Arctic tundra (Euskirchen et al, 2016). A long-term study by Euskirchen et al (2016) found that increases in air and soil temperatures at multiple depths may trigger a new trajectory of CO2 release. As such, the need to understand the environmental variables that influence these processes is necessary, particularly in ecosystems like wetlands that have a disproportionate influence on the landscape C balance in the High Arctic.…”

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confidence: 99%

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Controls on spatial and temporal patterns of soil nitrogen availability in a High Arctic wetland

Hung

Atkinson

Scott

2017

Preprint

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Abstract. Increased soil nutrient availability, and associated increase in vegetation productivity, could create a negative feedback between Arctic ecosystems and the climate system, reducing the contribution of Arctic ecosystems to future climate change. To predict whether this feedback will develop, it is important to understand the environmental controls over nutrient cycling in High Arctic ecosystems, and how they vary over space and time. This study explores the environmental 10 controls over spatial patterns of soil nitrogen availability in a High Arctic wet sedge meadow and how they influence carbon exchange processes. Ion exchange resin membranes measured available inorganic nitrogen in soils throughout the growing season at a high spatial resolution, while environmental variables (e.g. active layer depth, soil temperature, soil moisture) and carbon flux measurements were taken at frequent intervals during the 2016 field season. Environmental measures correlated highly with total and late season nitrate levels (total season dry tracks nitrate R 2 = 0.533, total season wet tracks nitrate R 2 = 15 0.803, late season nitrate R 2 = 0.622), with soil temperatures at 5 cm depth having the greatest effect. Soil available nitrate and ammonium correlated highly with total and early season gross primary productivity (total season wet tracks R 2 = 0.685, early season dry tracks R 2 = 0.788, early season wet tracks R 2 = 0.785). Higher ammonium concentrations coincided with greater carbon dioxide uptake. Nitrate concentrations correlated strongly to soil moisture, but nitrate levels were much lower than ammonium concentrations, suggesting low rates of nitrification vs. mineralization. Similar patterns were observed 20 regardless of whether the wet-sedge meadow was classified as wet or dry, but the relationships were always stronger in areas classified as wet, indicating the importance of moisture and water availability on abiotic processes in High Arctic wet sedge meadows. Topography played an important role in the movement and transport of water, which influenced how nutrients were cycled and moved within the wetland. Generally, the low-lying areas had the highest inorganic nitrogen concentrations.These results suggest that finer scale processes altering nitrogen availability may influence the overall carbon balance of wet 25 sedge meadows in the High Arctic, and how these ecosystems may respond to changes in climate.

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Section: Comparing the Influence Of Abiotic Conditions And Nitrogen Amentioning

confidence: 68%

mentioning

confidence: 99%

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confidence: 99%

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Controls on spatial and temporal patterns of soil nitrogen availability in a High Arctic wetland

Hung

Atkinson

Scott

2017

Preprint

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“…The measurements and data processing are described in more detail for Imnavait in [25] and for Bonanza Creek in [26]. For all the sites, the 30-minute values were aggregated into 24-hour values (averages for T; totals for P, and ET) using MATLAB.…”

Section: Methodsmentioning

confidence: 99%

Regional Climate Model Simulation of Surface Moisture Flux Variations in Northern Terrestrial Regions

Fischer¹,

Walsh²,

Euskirchen³

et al. 2018

ACS

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The wetness of high-latitude land surfaces is strongly dependent on the difference between precipitation (P) and evapotranspiration (ET). If climate models are to capture the trajectory of surface wetness in high latitudes, they must be able to simulate the seasonality and variations of the surface moisture fluxes, as well as the sensitivities to the variations to the drivers. In this study, a combination of regional climate model output and eddy covariance measurements from flux tower locations in Alaska is used to evaluate model simulations of the surface moisture fluxes and their variations. In particular, we use the model output and the field measurements to test the hypothesis that temperature (T) is the key driver of variations of ET in tundra regions underlain by permafrost, while precipitation plays a greater role in boreal forest areas. Although the model's hydrologic cycle is stronger (larger P, larger ET) relative to the in situ measurements at all the sites, the prominent seasonal cycles of P, T, and ET are captured by the model. The tower measurements from all sites show a short period (one or two months) of negative P-ET during summer, indicative of surface drying, although the model does not show this period of drying at the inland tundra site. At all the tundra sites, both the flux tower data and the model simulations show that daily and warm-season totals of ET are largely temperature-driven. Daily ET shows a weak negative correlation with precipitation in the measurements and in the model results for all the sites. Precipitation is the main driver of year-to-year variations of the seasonally integrated net moisture flux at all the sites, implying that precipitation will be at least as important as temperature in the future trajectory of surface wetness.

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“…et al, 1973;Laidler and Treitz, 2003). However, soil attributes can be equally important in ecosystem carbon exchange (Euskirchen et al, 2017), and it is crucial to find out how soil attributes co-vary with those plant attributes that can be detected using remote sensing. Moreover, while LAI is a suitable measure of photosynthetically-active biomass for vascular plants, few studies have produced LAI estimates for mosses (Bond-Lamberty and Gower, 2007) and the abundance of mosses has been estimated as areal coverage or thickness of the active green layer (Douma et al, 2007;5 Riutta et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data

Mikola¹,

Virtanen²,

Linkosalmi³

et al. 2018

Preprint

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Abstract. Arctic tundra ecosystems will have a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity 20 of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) -bare soil, lichen tundra, shrub tundra, flood meadow, graminoid tundra, bog, dry fen, wet den and water -to classify the variation in our site. To characterize the LCTs, we sampled 92 study plots for plant (biomass and leaf area index, LAI) and soil 25 (organic matter OM%, bulk density, moisture, pH, litter layer depth, litter mass loss, temperature and active layer depth) attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images (QuickBird and WorldView-2, portraying vegetation at 180, 220 and 750 growing degree days, DD with 0 °C threshold) and a digital elevation model (derived from a WV-2 stereo-30 pair image). We found that soils in our site ranged from mineral soils in bare soil and lichen tundra (on average 3.9 % OM) to soils of high OM% in graminoid tundra, bog, dry fen and wet fen (38 %), with shrub tundra and flood meadow Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but the amount of variation explained was significantly lower (6-15 %). NDVI captured variation in peak season vascular LAI better than variation in moss biomass, but the difference depended on the phase of the growing season in the image:180-DD, 220-DD and 750-DD NDVI captured 23, 17 and 7 % of moss mass variation and 25, 34 and 50% of vascular 5 LAI variation, respectively. For this reason, soil attributes associated with moss mass were better captured by early season NDVI and those associated with LAI by late season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and they could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including 10 OM% and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance or topography.This suggests that using simple reflectance indices and DEM for spatial extrapolation of those vegetation and soil attributes that are relevant for regional ecosystem and global climate models warran...

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Long-Term Release of Carbon Dioxide from Arctic Tundra Ecosystems in Alaska

Cited by 132 publications

References 49 publications

Controls on spatial and temporal patterns of soil nitrogen availability in a High Arctic wetland

Controls on spatial and temporal patterns of soil nitrogen availability in a High Arctic wetland

Regional Climate Model Simulation of Surface Moisture Flux Variations in Northern Terrestrial Regions

Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data

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