Deadwood, long recognized as playing an important role in storing carbon and releasing it as CO2 in forest ecosystems, is more recently drawing attention for its potential role in the cycling of other greenhouse trace gases. Across three Northeastern and Central US forests, mean methane (CH4) concentrations in deadwood were 23 times atmospheric levels (43.0 μL L−1 ± 12.3; mean ± SE), indicating a lower bound, mean radial wood surface area flux of ~6 × 10−4 μmol CH4 m−2 s−1. Site, decay class, log diameter, and species were all highly significant predictors of CH4 abundance in deadwood, and diameter and decay class interacted as important controls limiting CH4 concentrations in the smallest and most decayed logs. Nitrous oxide (N2O) concentrations were negatively correlated with CH4 (r2 = −0.20, p < 0.001) and on average ~25 % lower than ambient (276.9 nL L−1 ± 2.9; mean ± SE), indicating net consumption of nitrous oxide. Oxygen (O2) concentrations were uniformly near anaerobic (355.8 μL L−1 ±1.2; mean ± SE), and CO2 was elevated from atmospheric (9336.9 μL L−1 ± 600.6; mean ± SE). Most notably, our observations that CH4 concentrations were highest in the least decayed wood, may suggest that methanogenesis is not fuelled by structural wood decomposition but rather by consumption of more labile nonstructural carbohydrates.
KeywordsClimate change Decomposition Methane Methanogenesis Nitrous oxide Nonstructural carbohydrates Trace gases woody debris
The authors acknowledge the staff of the Yale Myers Forest, and the Tyson Research Center. Shannon Murray, Nora Hawkins, Jacqueline Kulig, and Joanna Parkman assisted with fieldwork at the Yale Myers Forest. This work was supported by National Science Foundation awards granted to KRC and MAB (NSF DGE-1405135), and to AEZ (NSF DEB-1302797). Additional funding was provided by the Yale Institute for Biospheric Studies, the Beck Fund, and the Middlebury Senior Research Project Supplement Award.
KRC, CDO, MAB, XL, CPB, ML, and AEZ planned and designed the research. KRC, CPB, BO, DSM, TWC, and MCD conducted fieldwork. KRC, DSM, and CB analyzed data and designed graphics. KRC, MAB, BO, and BS wrote the manuscript. All authors contributed comments to earlier drafts.
- Adair EC, Parton WJ, Del Grosso SJ, Silver WL, Harmon ME, Hall SA, Burke IC, Hart SC (2008) Simple three-pool model accurately describes patterns of long-term litter decomposition in diverse climates. Glob Chang Biol 14(11):2636–2660Google Scholar
- Boddy L (2001) Fungal community ecology and wood decomposition processes in angiosperms: from standing tree to complete decay of coarse woody debris. Ecol Bull 49:43–56Google Scholar
- Ettwig KF, Butler MK, Le Paslier D, Pelletier E, Mangenot S, Kuypers MMM, Schreiber F, Dutilh BE, Zedelius J, de Beer D, Gloerich J, Wessels HJCT, van Alen T, Luesken F, Wu ML, van de Pas-Schoonen KT, Op den Camp HJM, Janssen-Megens EM, Francoijs K-J, Stunnenberg H, Weissenbach J, Jetten MSM, Strous M (2010) Nitrite-driven anaerobic methane oxidation by oxygenic bacteria. Nature 464(7288):543–548CrossRefGoogle Scholar
- Koike I, Hattori A (1975) Energy yield of denitrification: an estimate from growth yield in continuous cultures of Pseudomonas denitrificans under nitrate-, nitrite-and nitrous oxide-limited conditions. Microbiology 88(1):11–19Google Scholar
- Pacala SW, Hurtt GC, Baker D, Peylin P, Houghton RA, Birdsey RA, Heath L, Sundquist ET, Stallard RF, Ciais P, Moorcroft P, Caspersen JP, Shevliakova E, Moore B, Kohlmaier G, Holland E, Gloor M, Harmon ME, Fan S-M, Sarmiento JL, Goodale CL, Schimel D, Field CB (2001) Consistent land- and atmosphere-based US carbon sink estimates. Science 292(5525):2316–2320CrossRefGoogle Scholar
- Pan Y, Birdsey RA, Fang J, Houghton R, Kauppi PE, Kurz WA, Phillips OL, Shvidenko A, Lewis SL, Canadell JG, Ciais P, Jackson RB, Pacala SW, McGuire AD, Piao S, Rautiainen A, Sitch S, Hayes D (2011) A large and persistent carbon sink in the world’s forests. Science 333(6045):988–993CrossRefGoogle Scholar
- Panday U, Singh JS (1982) Leaf-litter decomposition in an oak-conifer forest in Himalaya: the effects of climate and chemical composition. Forestry 55(1):47–59Google Scholar
- R Development Core Team (2015) R: A language and environment for statistical computing. In: R Foundation for Statistical Computing, ViennaGoogle Scholar
- Stams A, Plugge C (2010) The microbiology of methanogenesis. In: Smith P, Reay D, Van Amstel A (eds) Methane and climate change. Taylor & Francis, New York, pp 14–26Google Scholar
- Teskey RO, Saveyn A, Steppe K, McGuire MA (2008) Origin, fate and significance of CO2 in tree stems. New Phytol 177(1):17–32Google Scholar
- Woodall CW, Monleon VJ (2008) Sampling protocol, estimation, and analysis procedures for the down woody materials indicator of the FIA program. General Technical Report NRS, vol 22. U.S. Department of Agriculture, Forest Service, Northern Research Station, Newtown Square, PA, 68 pGoogle Scholar