Articles | Volume 12, issue 9
https://doi.org/10.5194/tc-12-2803-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-12-2803-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Consumption of atmospheric methane by the Qinghai–Tibet Plateau alpine steppe ecosystem
Hanbo Yun
State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
Key Laboratory for Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of Sciences, Lanzhou, 730000, China
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana 47907, USA
Qingbai Wu
CORRESPONDING AUTHOR
State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana 47907, USA
Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana 47907, USA
Tong Yu
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana 47907, USA
Zhou Lyu
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana 47907, USA
Yuzhong Yang
State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
Huijun Jin
State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
Guojun Liu
State Key Laboratory of Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
Yang Qu
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana 47907, USA
Licheng Liu
Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, Indiana 47907, USA
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Cited articles
Bohn, T. J., Melton, J. R., Ito, A., Kleinen, T., Spahni, R., Stocker, B. D.,
Zhang, B., Zhu, X., Schroeder, R., Glagolev, M. V., Maksyutov, S., Brovkin,
V., Chen, G., Denisov, S. N., Eliseev, A. V., Gallego-Sala, A., McDonald, K.
C., Rawlins, M. A., Riley, W. J., Subin, Z. M., Tian, H., Zhuang, Q., and
Kaplan, J. O.: WETCHIMP-WSL: intercomparison of wetland methane emissions
models over West Siberia, Biogeosciences, 12, 3321–3349,
https://doi.org/10.5194/bg-12-3321-2015, 2015.
Burba, G. G., Mcdermitt, D. K., and Grelle, A.: Addressing the influence of
instrument surface heat exchange on the measurements of CO2 flux from
open–path gas analyzers, Glob. Change Biol., 14, 1854–1876, 2008.
Cao, B., Gruber, S., and Zhang, T.: Spatial variability of active layer
thickness detected by ground–penetrating radar in the Qilian Mountains,
Western China, J. Geophys. Res.-Earth, 122, 574–591, 2017.
Cao, G., Xu, X., and Long, R.: Methane emissions by alpine plant communities
in the Qinghai–Tibet Plateau, Biol. Lett., 4, 681–684, 2008.
Cate, R. B. and Nelson, L. A.: A simple statistical procedure for
partitioning soil test correlation data into two classes, Soil Sci. Soc.
Am. J., 35, 658–660, 1971.
Chang, R., Miller, C., and Dinardo, S.: Methane emissions from Alaska in 2012
from CARVE airborne observations, P. Natl. Acad. Sci. USA, 111, 16694–16699,
2014.
Chang, S. and Shi, P.: A review of research on responses of leaf traits to
climate change, Chinese Journal of Plant Ecology, 39, 206–216, 2015.
Chen, W., Wolf, B., and Zheng, X.: Annual methane uptake by temperate semiarid
steppes as regulated by stocking rates, aboveground plant biomass and
topsoil air permeability, Glob. Change Biol., 17, 2803–2816, 2011.
Curry, C.: Modeling the soil consumption at atmospheric methane at the global
scale, Global Biogeochem. Cy., 21, GB4012, https://doi.org/10.1029/2006GB002818, 2007.
Del, G., Parton, W., and Mosier, A. R.: General CH4 oxidation model
and comparisons of CH4 oxidation in natural and managed systems,
Global Biogeochem. Cy., 14, 999–1019, 2000.
Dengel, S., Zona, D., Sachs, T., Aurela, M., Jammet, M., Parmentier, F. J.
W., Oechel, W., and Vesala, T.: Testing the applicability of neural networks
as a gap-filling method using CH4 flux data from high latitude
wetlands, Biogeosciences, 10, 8185–8200, https://doi.org/10.5194/bg-10-8185-2013,
2013.
Falge, E., Baldocchi, D., and Olson, R.: Gap filling strategies for
defensible annual sums of net ecosystem exchange, Agr. Forest Meteorol., 107,
43–69, 2001.
Foken, T. and Wichura, B.: Tools for quality assessment of surface-based flux
measurements, Agr. Forest Meteorol., 78, 83–105, 1996.
Gažovič, M., Kutzbach, L., and Schreiber, P.: Diurnal dynamics of
CH4 from a boreal peatland during snowmelt, Tellus B, 62, 133–139,
2010.
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of
Working Group I to the Fifth Assessment Report of the Intergovernmental Panel
on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K.,
Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and
Midgley, P.M., Cambridge University Press, Cambridge, United Kingdom and New
York, NY, USA, 1535 pp., 2013.
Jansson, J. K. and Tas, N.: The microbial ecology of permafrost, Nat. Rev.
Microbiol., 12, 414–425, 2014.
Jiang, C., Yu, G., and Fang, H.: Short–term effect of increasing nitrogen
deposition on CO2, CH4 and N2O fluxes in an alpine
meadow on the Qinghai–Tibetan Plateau, China, Atmos. Environ., 44,
2920–2926, 2010.
Jin, H., Li, S., and Cheng, G.: Permafrost and climatic change in China,
Global Planet. Change, 26, 387–404, 2000.
Jørgensen, C. J., Johansen, K. M. L., and Westergaard-Nielsen, A.: Net
regional methane sink in High Arctic soils of northeast Greenland, Nat.
Geosci., 8, 20–23, 2015.
Kirschke, S., Bousquet, P., and Ciais, P.: Three decades of global methane
sources and sinks, Nat. Geosci., 6, 813–823, 2013.
Kolb, S.: The quest for atmospheric methane oxidizers in forest soils, Env.
Microbiol. Rep., 1, 336–346, 2009
Koven, C. D., Ringeval, B., and Friedlingstein, P.: Permafrost
carbon–climate feedbacks accelerate global warming, P. Natl. Acad. Sci. USA,
108, 14769–14774, 2011.
Lau, M., Stackhouse, B. T., and Layton, A. C.: An active atmospheric methane
sink in high Arctic mineral cryosols, ISME J., 9, 1880–1891, 2015.
Lecher, A. L., Dimova, N., and Sparrow K.,J.: Methane transport from the
active layer to lakes in the Arctic using Toolik Lake, Alaska, as a case
study, P. Natl. Acad. Sci. USA, 112, 3636–3640, 2015.
Lee, X., Massman, W., and Law, B. (Eds.): Handbook of Micrometeorology: A
Guide for Surface Flux Measurement and Analysis, Springer Science and
Business Media, Part of the Atmospheric and Oceanographic Sciences Library
book series (ATSL), 29, https://doi.org/10.1007/1-4020-2265-4, 2006.
Li, K., Gong, Y., and Song, W.: Responses of CH4, CO2 and
N2O fluxes to increasing nitrogen deposition in alpine grassland of
the Tianshan Mountains, Chemosphere, 88, 140–143, 2012.
Liebner, S., Zeyer, J., and Wagner, D.: Methane oxidation associated with
submerged brown mosses reduces methane emissions from Siberian polygonal
tundra, J. Ecol., 99, 914–922, 2011.
Lin, Z., Burn, C. R., and Niu, F.: The Thermal Regime, including a Reversed
Thermal Offset, of Arid Permafrost Sites with Variations in Vegetation Cover
Density, Wudaoliang Basin, Qinghai–Tibet Plateau, Permafrost Periglac., 26,
142–159, 2015.
Loescher, H. W., Law, B. E., and Mahrt, L: Uncertainties in, and
interpretation of, carbon flux estimates using the eddy covariance technique,
J. Geophys. Res., 111, D21S90, https://doi.org/10.1029/2005JD006932, 2006.
Lund, M., Lafleur, P. M., and Roulet, N. T.:Variability in exchange of CO2 across 12 northern peatland and tundra sites. Glob. Change Biol., 16, 2436–2448, 2010.
Luo, G. J., Brüggemann, N., Wolf, B., Gasche, R., Grote, R., and
Butterbach-Bahl, K.: Decadal variability of soil CO2, NO,
N2O, and CH4 fluxes at the Höglwald Forest, Germany,
Biogeosciences, 9, 1741–1763, https://doi.org/10.5194/bg-9-1741-2012, 2012.
Mastepanov, M., Sigsgaard, C., and Dlugokencky, E. J.: Large tundra methane
burst during onset of freezing, Nature, 456, 628–630, 2008.
Mastepanov, M., Sigsgaard, C., Tagesson, T., Ström, L., Tamstorf, M. P.,
Lund, M., and Christensen, T. R.: Revisiting factors controlling methane
emissions from high-Arctic tundra, Biogeosciences, 10, 5139–5158,
https://doi.org/10.5194/bg-10-5139-2013, 2013.
Mauder, M., Cuntz, M., and Drüe, C.: A strategy for quality and
uncertainty assessment of long–term eddy–covariance measurements, Agr.
Forest Meteorol., 169, 122–135, 2013.
McGuire, A. D., Christensen, T. R., Hayes, D., Heroult, A., Euskirchen, E.,
Kimball, J. S., Koven, C., Lafleur, P., Miller, P. A., Oechel, W., Peylin,
P., Williams, M., and Yi, Y.: An assessment of the carbon balance of Arctic
tundra: comparisons among observations, process models, and atmospheric
inversions, Biogeosciences, 9, 3185–3204, https://doi.org/10.5194/bg-9-3185-2012,
2012.
Moncrieff, J., Clement, R., and Finnigan, J.: Averaging, detrending, and
filtering of eddy covariance time series, in: Handbook of micrometeorology,
edited by: Lee, X., Massman, W., and Law, B., Springer Netherlands, 29,
7–31, 2004.
Muller, S. W.: Permafrost or permanently frozen ground and related
engineering problems, Military Intelligence Division Office, Chief of Engineers, U. S. Army, 2, 6–10, 1947.
Oh, Y., Stackhouse, B., and Lau, M.: A scalable model for methane consumption
in arctic mineral soils, Geophys. Res. Lett., 43, 5143–5150, 2016.
Panikov, N. S. and Dedysh, S. N.: Cold season CH4 and CO2
emission from boreal peat bogs (West Siberia): Winter fluxes and thaw
activation dynamics, Global Biogeochem. Cy., 14, 1071–1080, 2000.
Papale, D., Reichstein, M., Aubinet, M., Canfora, E., Bernhofer, C., Kutsch,
W., Longdoz, B., Rambal, S., Valentini, R., Vesala, T., and Yakir, D.:
Towards a standardized processing of Net Ecosystem Exchange measured with
eddy covariance technique: algorithms and uncertainty estimation,
Biogeosciences, 3, 571–583, https://doi.org/10.5194/bg-3-571-2006, 2006.
Patra, P. K. and Kort, E. A.: Regional Methane Emission Estimation Based on
Observed Atmospheric Concentrations (2002–2012), J. Meteorol. Soc. Jpn.,
Ser. II, 94, 91–113, 2016.
Qin, Y., Wu, T., and Li, R.: Using ERA-Interim reanalysis dataset to assess
the changes of ground surface freezing and thawing condition on the
Qinghai–Tibet Plateau, Environ. Earth Sci., 75, 1–13, 2016.
Rigby, M., Prinn, R. G., and Fraser, P. J.: Renewed growth of atmospheric
methane, Geophys. Res. Lett., 35, 2–7, 2008.
Rivkina, E., Laurinavichius, K., and McGrath, J.: Microbial life in
permafrost, Adv. Space Res., 33, 1215–1221, 2004.
Segers, R.: Methane production and methane consumptiona–review of processes
underlying wetland methane fluxes [Review], Biogeochemistry, 41, 23–51,
1998.
Shi, P., Sun, X., and Xu, L.: Net ecosystem CO2 exchange and
controlling factors in a steppe–Kobresia meadow on the Tibetan Plateau, Sci.
China Ser. D, 49, 207–218, 2006.
Song, W., Wang, H., and Wang, G.: Methane emissions from an alpine wetland on
the Tibetan Plateau: Neglected but vital contribution of the nongrowing
season, J. Geophys. Res.-Biogeo., 120, 1475–1490, 2015.
Spahni, R., Wania, R., Neef, L., van Weele, M., Pison, I., Bousquet, P.,
Frankenberg, C., Foster, P. N., Joos, F., Prentice, I. C., and van Velthoven,
P.: Constraining global methane emissions and uptake by ecosystems,
Biogeosciences, 8, 1643–1665, https://doi.org/10.5194/bg-8-1643-2011, 2011.
Steinkamp, R., Butterbach-Bahl, K., and Papen, H.: Methane oxidation by
soils of an N limited and N fertilized spruce forest in the Black Forest,
Germany, Soil. Biol. Biochem., 33, 145–153, 2001.
Sturtevant, C. S., Oechel, W. C., Zona, D., Kim, Y., and Emerson, C. E.: Soil
moisture control over autumn season methane flux, Arctic Coastal Plain of
Alaska, Biogeosciences, 9, 1423–1440, https://doi.org/10.5194/bg-9-1423-2012, 2012.
Tang, Y., Wan, S., and He, J.: Foreword to the special issue: looking into the impacts of global warming from the roof of the world, J. Plant Ecol., 2, 169–171, 2009.
Treat, C. C., Wollheim, W. M., and Varner, R. K.: Temperature and peat type
control CO2 and CH4 production in Alaskan permafrost peats,
Glob. Change Biol., 20, 2674–2686, 2014.
Vickers, D. and Mahrt, L.: Quality control and flux sampling problems for
tower and aircraft data, J. Atmos. Ocean. Tech., 14, 512–526, 1997.
Wang, G., Li, Y., and Wang, Y.: Effects of permafrost thawing on vegetation
and soil carbon pool losses on the Qinghai–Tibet Plateau, China, Geoderma,
143, 143– 52, 2008.
Wang, S., Jin, H., and Li, S.: Permafrost degradation on the Qinghai–Tibet
Plateau and its environmental impacts, Permafrost Periglac., 11, 43–53,
2000.
Wang, Y., Liu, H., and Chung, H.: Non-growing season soil respiration is
controlled by freezing and thawing processes in the summer monsoon-dominated
Tibetan alpine grassland, Global Biogeochem. Cy., 28, 1081–1095, 2014.
Webb, E. K., Pearman, G. I., and Leuning, R.: Correction of flux measurements
for density effects due to heat and water vapor transfer, Q. J. Roy.
Meteorol. Soc., 106, 85–100, 1980.
Wei, D., Ri, X., and Wang, Y.: Responses of CO2, CH4 and
N2O fluxes to livestock exclosure in an alpine steppe on the Tibetan
Plateau, China, Plant Soil, 359, 45–55, 2012.
Wei, D., Ri, X., and Tarchen, T.: Considerable methane uptake by alpine
grasslands despite the cold climate: In situ measurements on the central
Tibetan Plateau, 2008–2013, Glob. Change Biol., 21, 777–788, 2015a.
Wei, D., Tarchen, T., and Dai, D.: Revisiting the role of CH4
emissions from alpine wetlands on the Tibetan Plateau: Evidence from two in
situ measurements at 4758 and 4320 m above sea level, J. Geophys.
Res.-Biogeo., 120, 1741–1750, 2015b.
Whalen, S. C.: Biogeochemistry of Methane Exchange between Natural Wetlands
and the Atmosphere, Environ. Eng. Sci., 22, 73–94, 2005.
Whalen, S. C. and Reeburgh, W. S.: Consumption of atmospheric methane by
tundra soils, Nature, 346, 160–162, 1990.
Whalen, S. C., Reeburgh, W. S., and Barber, V. A.: Oxidation of methane in
boreal forest soils: a comparison of seven measures, Biogeochemistry, 16,
181–211, 1992.
Wilson K., Goldstein, A., Falge, E., Aubinet, M., Baldocchi, D., P.,
Berbigier, Bernhofer, C., Ceulemans, R., Dolman, H., Field, C., Grelle, A.,
Ibrom, A., Law, B. E., Kowalski, A., Meyers, T., Moncrieff, J., Monson, R.,
Oechel, W., Tenhunen, J., Valentini, R., and Verma, S.: Energy balance closure at FLUXNET sites, Agr. Forest
Meteorol., 113, 223–243, 2002.
Wu, Q. and Liu, Y.: Ground temperature monitoring and its recent change in
Qinghai–Tibet Plateau, Cold Reg. Sci. Technol., 38, 85–92, 2004.
Wu, Q. and Zhang, T.: Recent permafrost warming on the Qinghai–Tibetan
Plateau, J. Geophys. Res., 113, D13108, https://doi.org/10.1029/2007JD009539, 2008.
Wu, Q. and Zhang, T.: Changes in active layer thickness over the
Qinghai–Tibetan Plateau from 1995 to 2007, J. Geophys. Res., 115, D09107,
https://doi.org/10.1029/2009JD012974, 2010a.
Wu, Q. Zhang, T., and Liu, Y.: Permafrost temperatures and thickness on the
Qinghai–Tibet Plateau, Global Planet. Change, 72, 32–38, 2010b.
Yang, S., Wen, X., and Shi, Y.: Hydrocarbon degraders establish at the costs
of microbial richness, abundance and keystone taxa after crude oil
contamination in permafrost environments, Sci. Rep., 6, 37473,
https://doi.org/10.1038/srep37473, 2016.
Zhu, X., Zhuang, Q., and Chen, M.: Net exchanges of methane and carbon
dioxide on the Qinghai–Tibetan Plateau from 1979 to 2100, Environ. Res.
Lett., 10, 085007, https://doi.org/10.1088/1748-9326/10/8/085007, 2004.
Zhuang, Q., Melillo, J. M., and Kicklighter, D. W.: Methane fluxes between
terrestrial ecosystems and the atmosphere at northern high latitudes during
the past century: A retrospective analysis with a process–based
biogeochemistry model, Global Biogeochem. Cy., 18, GB3010,
https://doi.org/10.1029/2004GB002239, 2004.
Zhuang, Q., Chen, M., and Xu, K.: Response of global soil consumption of
atmospheric methane to changes in atmospheric climate and nitrogen
deposition, Global Biogeochem. Cy., 27, 650–663, 2013.
Zona, D., Gioli, B., and Commane, R.: Cold season emissions dominate the
Arctic tundra methane budget, P. Natl. Acad. Sci. USA, 113, 40–45, 2016.
Short summary
Here we reported the QTP permafrost region was a CH4 sink of −0.86 ± 0.23 g CH4-C m−2 yr−1 over 2012–2016, soil temperature and soil water content were dominant factors controlling CH4 fluxes, and their correlations changed with soil depth due to cryoturbation dynamics. This region was a net CH4 sink in autumn, but a net source in spring, despite both seasons experiencing similar top soil thawing and freezing dynamics.
Here we reported the QTP permafrost region was a CH4 sink of −0.86 ± 0.23 g CH4-C m−2 yr−1 over...