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Estimating methane emissions using vegetation mapping in the taiga–tundra boundary of a north-eastern Siberian lowland Cover

Estimating methane emissions using vegetation mapping in the taiga–tundra boundary of a north-eastern Siberian lowland

Open Access
|Jan 2019

Figures & Tables

Fig. 1.

(a) Regional and (b) Local position of the study site. The Indigirka lowland is located in the north area of the watershed (Google Maps). WorldView-2 satellite image covered an area of 10 × 10 km (true colour). The main branch of the Indigirka River lies in the upper part of the image. The locations of the Kodac site (K), B site (B), local surveyed plot for training (circle) and test pixels (rectangular) are plotted on the map. Each survey point contains 3–4 quadrats for vegetation surveys. Vegetation was mapped within a target area (red line) without hills and cloudy areas.

Fig. 2.

(a) True colour image and (b) vegetation map showing nine vegetation classes on the site scale (400 × 400 m) at site K (Kodac). The lake class does not appear at this scale, and therefore the map was covered by eight classes only, as shown in (b).

Table 3.

Methane emissions at the local scale were calculated using the observed CH4 flux, and the area of each vegetation class obtained from the vegetation map. In situ CH4 flux (230 observation in total) was observed from 3 July to 9 August 2009–2016. The sedge-dominated wetland contributes 70% of total emissions.

ClassArea (km2)Coverage%Observed mean CH4 flux (mg m−2 d−1) a SENDaysEstimated local CH4 emission (106 g CH4 month−1)CH4 contribution%Willow26270.30.31750.30.2Cotton-sedge22231141190367870River14152.6 b 0.31821.11.0Emergent9.29.596291442725Shrub8.08.30.80.7830.20.2Bare-land6.87.0−3.42.272−0.7−0.6Lake4.64.8253.4323.62.8Tree4.04.1−0.10.249230.00.0Sphagnum1.81.9388.924172.21.9Total9637 c 9.823094111

[i] aMethane flux observed by the calculation of the average of chamber-measured values. Data shown are averages ± standard error (SE), with the repeated number of total flux measurements (N) and the observation days (Days).

[ii] bRiver methane flux was estimated from river dissolved CH4 concentrations and transfer velocity (Supplementary Material: Text S1, Fig. S7).

[iii] cAverage local CH4 flux per square metre per day (mg CH4 m−2 d−1).

Fig. 3.

Vegetation, relative elevation (a) and soil moisture (b) along a 50-m transect. Soil moisture was measured as the averaged volumetric water content at the surface (0–8 cm) by time domain reflectance on 12 July 2012, 15 July 2014 and 12 July 2015. Sphagnum spp. and cotton-sedge areas are hatched to illustrate potential CH4 sources.

Table 1.

Classes assigned by visual observation and final classes based on satellite image mapping. Plant species composition classes corresponding to microtopographies were categorised into six classes. Because of the similarity of species compositions, structures and spectral features of satellite images among the shrub-dry, shrub-wet and dry-tussock classes, and between the willow and alder classes, these classes were combined into the shrub class and the willow class, respectively. Bare-land, river and lake classes were added, whereupon the landscape was finally grouped into nine classes.

Microtopographic classesVegetation classes based on plant species compositionVegetation classes for satellite-data based mappingPlant communityMoss layerShrub and herb layerClassesClusters a Mound (High)TreeTreeI, II, IIIGreen-moss b Larix cajanderi, Betula nana, Ledum palustre, Vaccinium vitis-idaea, Vaccinium uliginosumTreeShrubShrub-dry c VI, VIIGreen-moss b Betula nana, Ledum palstre, Rubus chamaemorusShrubShrub-moist c Green-moss/Sphagnum-dry d Salix pulchra, Vaccinium uliginosumDry-tussock c Sphagnum-dry e Carex aquatilis, Salix pulchraWet area (Low)SphagnumSphagnumXIISphagnum-wet f Carex aquatilis, Eriophorum vaginatum, Salix pulchra,SphagnumCotton-sedgeCotton-sedgeXISphagnum-wet f , Moss-wet g Eriophorum angustifolium, Comarum palstreCotton-sedgeWillowIXGreen-moss b , Moss-wet g Salix boganidensisWillowAlderVIIIGreen-moss b Alnus fruticosaEmergentXMoss-wet g Equisetum spp. Arctophila fulva, Carex chordorrhizaEmergentBare-landNoNoBare-landLake/RiverNoNoLake/River

a Clusters of plant species composition in local scale (Table S2).

b Green-moss (Tomentypnum nitens, Hylocomium splendens, Aulacomnium turgidum).

c Classes of shrub-dry, shrub-moist and dry-tussock are distinguished at the site scale (Table S1).

d Green-moss/Sphagnum-dry mixed (Green-moss [as above] and Sphagnum spp. [S. warnstorfii and S. girgensohnii]).

e Sphagnum-dry (Sphagnum spp. [S. warnstorfii, S. girgensohnii, and S. balticum]).

f Sphagnum-wet (S. squarrosum and S. angustifolium).

g Moss-wet (Drepanocladus spp., Warnstorfia spp.).

Table 2.

Area and coverage of classification at the site scale (400 × 400 m).

ClassArea (km2)Coverage (%)Cotton-sedge0.04528Willow0.03522Tree0.02314Shrub0.02113Sphagnum0.0159.1River0.0137.9Bare-land0.0063.5Emergent0.0042.2total0.160
Fig. 4.

Vegetation map showing the nine classes at the local scale (10 × 10 km) obtained by the MLC-DTC (maximum-likelihood classification and decision tree classification combined) method.

Fig. 5.

In situ CH4 flux measured by the chamber method in 2009–2016 during the summer growing season (3 July–9 August 2009–16, n (total) = 230). Only river CH4 flux was derived from dissolved CH4 concentration using the diffusive fraction with the transfer velocity method. Details are shown in Text S1 and Fig. S7.

Language: English
Page range: 1581004 - 1581004
Published on: Jan 1, 2019
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2019 T. Morozumi, R. Shingubara, R. Suzuki, H. Kobayashi, S. Tei, S. Takano, R. Fan, M. Liang, T. C. Maximov, A. Sugimoto, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.