Modeling Canopy CO2Exchange in the European Russian Arctic

Kiepe, I.; Friborg, Thomas; Herbst, Mathias; Johansson, Torbjörn; Soegaard, H.

doi:10.1657/1938-4246-45.1.50

Cited by 5 publications

(2 citation statements)

References 70 publications

(81 reference statements)

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“…This varies in response to a different vegetation composition and light conditions (Givnish, 1988;Givnish et al, 2004). Photosynthetic CO 2 assimilation also depends on Ribulose 1,5 bisphosphate (Rubisco) enzymatic activity, which has been shown to be more significant in limiting photosynthetic assimilation than the average light condition in the dominant plant species in RU-Seid-SA (Kiepe et al, 2013). The average light levels during peak season could explain about 50 % of LCP (Fig.…”

Section: Resultsmentioning

confidence: 99%

Assessing the spatial variability in peak season CO2 exchange characteristics across the Arctic tundra using a light response curve parameterization

Mbufong¹,

Lund²,

Aurela³

et al. 2014

Preprint

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Abstract. This paper aims to assess the functional and spatial variability in the response of CO2 exchange to irradiance across the Arctic tundra during peak season using light response curve (LRC) parameters. This investigation allows us to better understand the future response of Arctic tundra under climatic change. Data was collected using the micrometeorological eddy covariance technique from 12 circumpolar Arctic tundra sites, in the range of 64–74° N. The LRCs were generated for 14 days with peak net ecosystem exchange (NEE) using an NEE -irradiance model. Parameters from LRCs represent site specific traits and characteristics describing: (a) NEE at light saturation (Fcsat), (b) dark respiration (Rd), (c) light use efficiency (α), (d) NEE when light is at 1000 μmol m−2 s−1 (Fc1000), (e) potential photosynthesis at light saturation (Psat) and (f) the light compensation point (LCP). Parameterization of LRCs was successful in predicting CO2 flux dynamics across the Arctic tundra. Yet we did not find any trends in LRC parameters across the whole Arctic tundra but there were indications for temperature and latitudinal differences within sub-regions like Russia and Greenland. Together, LAI and July temperature had a high explanatory power of the variance in assimilation parameters (Fcsat, Fc1000 and Psat), thus illustrating the potential for upscaling CO2 exchange for the whole Arctic tundra. Dark respiration was more variable and less correlated to environmental drivers than was assimilation parameters. Thus, indicating the inherent need to include other parameters such as nutrient availability, substrate quantity and quality in flux monitoring activities.

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Section: Resultsmentioning

confidence: 99%

Assessing the spatial variability in peak season CO2 exchange characteristics across the Arctic tundra using a light response curve parameterization

Mbufong¹,

Lund²,

Aurela³

et al. 2014

Preprint

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“…The landscape scale CH 4 fluxes were measured by the EC technique during the period from mid-May to early October 2008. The CO 2 fluxes, measured simultaneously with the CH 4 fluxes data presented in this paper, have already been reported in Marushchak et al (2013) and Kiepe et al (2013). Fluctuations in the vertical wind speed were measured at a height of 2.75 m above the ground using a three-dimensional sonic anemometer (R3, Gill Instruments Ltd, UK).…”

Section: Ec Measurementsmentioning

confidence: 94%

Methane dynamics in warming tundra of Northeast European Russia

Marushchak

Friborg

Biasi

et al. 2015

Preprint

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Abstract. Methane (CH4) fluxes were investigated in a subarctic Russian tundra site in a multi-approach study combining plot scale data, ecosystem scale eddy covariance (EC) measurements and fine resolution land cover classification scheme for regional upscaling. The flux data as measured by the two independent techniques resulted in a seasonal (May–October 2008) cumulative CH4 emission of 2.4 (EC) and 3.7 g CH4 m−2 (manual chambers) for the source area representative of the footprint of the EC instruments. Upon upscaling for the entire study region of 98.6 km2, the chamber measured flux data yielded a regional flux estimate of 6.7 g CH4 m−2 yr−1. Our upscaling efforts accounted for the large spatial variability in the distribution of the various land cover types (LCTs) predominant at our study site. In particular, wetlands with emissions ranging from 34 to 53 g CH4 m−2 yr−1 were the most dominant CH4 emitting surfaces. Emissions from thermokarst lakes were an order of magnitude lower, while the rest of the landscape (mineral tundra) was a weak sink for atmospheric methane. Vascular plant cover was a key factor in explaining the spatial variability of CH4 emissions among wetland types, as indicated by the positive correlation of emissions with the leaf area index (LAI). As elucidated through a stable isotope analysis, the plant transport was the dominant CH4 release pathway that discriminates against heavier δ13C-CH4. The methane released from wetlands was lighter than that in the surface porewater and δ13C in the emitted CH4 correlated with the vascular plant cover (LAI) implying that the plant-mediated CH4 release dominates. A mean value of δ13C obtained here for the emitted CH4, −68.2 ± 2.0 ‰, is within the range of values from other wetlands, thus reinforcing the use of inverse modeling tools to better constrain the CH4 budget. Based on the IPCC A1B emission scenario, a temperature increase of 7 °C has been predicted for the tundra region of European Russia by the end of the 21st Century. A regional warming of this magnitude will have profound effects on the permafrost distribution leading to considerable changes in the regional landscape with a potential for an increase in the areal extent of methane emitting wet surfaces. We estimate that a projected increase in air temperature of 7 °C with a mere 10 % associated increase in the combined areal coverage of willow stands, fens and lakes in the region will lead to a 51 % higher amount of CH4 being emitted into the atmosphere by the end of this century.

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Tundren und polare Wüsten

Hauck

Leuschner

Homeier

2019

Klimawandel Und Vegetation - Eine Globale Übersicht

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Modeling Canopy CO₂Exchange in the European Russian Arctic

Cited by 5 publications

References 70 publications

Assessing the spatial variability in peak season CO<sub>2</sub> exchange characteristics across the Arctic tundra using a light response curve parameterization

Assessing the spatial variability in peak season CO<sub>2</sub> exchange characteristics across the Arctic tundra using a light response curve parameterization

Methane dynamics in warming tundra of Northeast European Russia

Tundren und polare Wüsten

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Modeling Canopy CO2Exchange in the European Russian Arctic

Cited by 5 publications

References 70 publications

Assessing the spatial variability in peak season CO&lt;sub&gt;2&lt;/sub&gt; exchange characteristics across the Arctic tundra using a light response curve parameterization

Assessing the spatial variability in peak season CO&lt;sub&gt;2&lt;/sub&gt; exchange characteristics across the Arctic tundra using a light response curve parameterization

Methane dynamics in warming tundra of Northeast European Russia

Tundren und polare Wüsten

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Product

Resources

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Modeling Canopy CO₂Exchange in the European Russian Arctic

Assessing the spatial variability in peak season CO<sub>2</sub> exchange characteristics across the Arctic tundra using a light response curve parameterization

Assessing the spatial variability in peak season CO<sub>2</sub> exchange characteristics across the Arctic tundra using a light response curve parameterization