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Carbon fractions in the world’s dead wood

  • 1.

    Pugh, T. A. et al. Role of forest regrowth in global carbon sink dynamics. Proc. Natl Acad. Sci. USA 116, 4382–4387 (2019).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 2.

    Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 3.

    Hubau, W. et al. Asynchronous carbon sink saturation in African and Amazonian tropical forests. Nature 579, 80–87 (2020).

  • 4.

    Domke, G. M., Oswalt, S. N., Walters, B. F. & Morin, R. S. Tree planting has the potential to increase carbon sequestration capacity of forests in the United States. Proc. Natl Acad. Sci. USA 117, 24649–24651 (2020).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 5.

    Baccini, A. et al. Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science 358, 230–234 (2017).

    ADS  MathSciNet  CAS  PubMed  MATH  Article  PubMed Central  Google Scholar 

  • 6.

    Luyssaert, S. et al. CO2 balance of boreal, temperate, and tropical forests derived from a global database. Glob. Change Biol. 13, 2509–2537 (2007).

    ADS  Article  Google Scholar 

  • 7.

    Harmon, M. E. et al. Ecology of coarse woody debris in temperate ecosystems. Adv. Ecol. Res. 15, 133–302 (1986).

    Article  Google Scholar 

  • 8.

    Weedon, J. T. et al. Global meta‐analysis of wood decomposition rates: a role for trait variation among tree species? Ecol. Lett. 12, 45–56 (2009).

    PubMed  Article  PubMed Central  Google Scholar 

  • 9.

    McGee, G. G. The contribution of beech bark disease-induced mortality to coarse woody debris loads in northern hardwood stands of Adirondack Park, New York, USA. Can. J. Res. 30, 1453–1462 (2000).

    Article  Google Scholar 

  • 10.

    Woodall, C. W. et al. Net carbon flux of dead wood in forests of the Eastern US. Oecologia 177, 861–874 (2015).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 11.

    Campbell, J. L. et al. Estimating uncertainty in the volume and carbon storage of downed coarse woody debris. Ecol. Appl. 29, e01844 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  • 12.

    Russell, M. B. et al. Quantifying carbon stores and decomposition in dead wood: a review. Ecol. Manag. 350, 107–128 (2015).

    Article  Google Scholar 

  • 13.

    Campbell, J., Alberti, G., Martin, J. & Law, B. E. Carbon dynamics of a ponderosa pine plantation following a thinning treatment in the northern Sierra Nevada. Ecol. Manag. 257, 453–463 (2009).

    Article  Google Scholar 

  • 14.

    Chambers, J. Q. et al. Response of tree biomass and wood litter to disturbance in a Central Amazon forest. Oecologia 141, 596–611 (2004).

    ADS  PubMed  Article  PubMed Central  Google Scholar 

  • 15.

    Domke, G. M., Woodall, C. W. & Smith, J. E. Accounting for density reduction and structural loss in standing dead trees: implications for forest biomass and carbon stock estimates in the United States. Carbon Balance Manag. 6, 14 (2011).

    PubMed  PubMed Central  Article  Google Scholar 

  • 16.

    Janisch, J. E. & Harmon, M. E. Successional changes in live and dead wood carbon stores: implications for net ecosystem productivity. Tree Physiol. 22, 77–89 (2002).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 17.

    Keith, H., Mackey, B. G. & Lindenmayer, D. B. Re-evaluation of forest biomass carbon stocks and lessons from the world’s most carbon-dense forests. Proc. Natl Acad. Sci. USA 106, 11635–11640 (2009).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 18.

    Martin, A. R., Doraisami, M. & Thomas, S. C. Global patterns in wood carbon concentration across the world’s trees and forests. Nat. Geosci. 11, 915–922 (2018).

    ADS  CAS  Article  Google Scholar 

  • 19.

    Thomas, S. C. & Martin, A. R. Carbon content of tree tissues: a synthesis. Forests 3, 332–352 (2012).

    Article  Google Scholar 

  • 20.

    Martin, A. R. & Thomas, S. C. A reassessment of carbon content in tropical trees. PLoS ONE 6, e23533 (2011).

    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

  • 21.

    Weggler, K., Dobbertin, M., Jüngling, E., Kaufmann, E. & Thürig, E. Dead wood volume to dead wood carbon: the issue of conversion factors. Eur. J. Res. 131, 1423–1438 (2012).

    Article  Google Scholar 

  • 22.

    Gorgolewski, A., Rudz, P., Jones, T., Basiliko, N. & Caspersen, J. Assessing coarse woody debris nutrient dynamics in managed northern hardwood forests using a matrix transition model. Ecosystems 23, 541–554 (2019).

    Article  CAS  Google Scholar 

  • 23.

    Moreira, A. B., Gregoire, T. G. & do Couto, H. T. Z. Wood density and carbon concentration of coarse woody debris in native forests. Braz. Ecosyst. 6, 18 (2019).

    Article  Google Scholar 

  • 24.

    Sandström, F., Petersson, H., Kruys, N. & Ståhl, G. Biomass conversion factors (density and carbon concentration) by decay classes for dead wood of Pinus sylvestris, Picea abies and Betula spp. in boreal forests of Sweden. Ecol. Manag. 243, 19–27 (2007).

    Article  Google Scholar 

  • 25.

    Cousins, S. J., Battles, J. J., Sanders, J. E. & York, R. A. Decay patterns and carbon density of standing dead trees in California mixed conifer forests. Ecol. Manag. 353, 136–147 (2015).

    Article  Google Scholar 

  • 26.

    Harmon, M. E., Fasth, B., Woodall, C. W. & Sexton, J. Carbon concentration of standing and downed woody detritus: effects of tree taxa, decay class, position, and tissue type. For. Ecol. Manag. 291, 259–267 (2013).

  • 27.

    Köster, K., Metslaid, M., Engelhart, J. & Köster, E. Dead wood basic density, and the concentration of carbon and nitrogen for main tree species in managed hemiboreal forests. Ecol. Manag. 354, 35–42 (2015).

    Article  Google Scholar 

  • 28.

    Clark, D. B., Clark, D. A., Brown, S., Oberbauer, S. F. & Veldkamp, E. Stocks and flows of coarse woody debris across a tropical rain forest nutrient and topography gradient. Ecol. Manag. 164, 237–248 (2002).

    Article  Google Scholar 

  • 29.

    Yang, F. F. et al. Dynamics of coarse woody debris and decomposition rates in an old-growth forest in lower tropical China. Ecol. Manag. 259, 1666–1672 (2010).

    Article  Google Scholar 

  • 30.

    Chao, K. J. et al. Carbon concentration declines with decay class in tropical forest woody debris. Ecol. Manag. 391, 75–85 (2017).

    Article  Google Scholar 

  • 31.

    Guo, J., Chen, G., Xie, J., Yang, Z. & Yang, Y. Patterns of mass, carbon and nitrogen in coarse woody debris in five natural forests in southern China. Ann. Sci. 71, 585–594 (2014).

    Article  Google Scholar 

  • 32.

    Martin, A. R., Gezahegn, S. & Thomas, S. C. Variation in carbon and nitrogen concentration among major woody tissue types in temperate trees. Can. J. Res. 45, 744–757 (2015).

    CAS  Article  Google Scholar 

  • 33.

    Gao, B., Taylor, A. R., Chen, H. Y. & Wang, J. Variation in total and volatile carbon concentration among the major tree species of the boreal forest. Ecol. Manag. 375, 191–199 (2016).

    Article  Google Scholar 

  • 34.

    Dossa, G. G. et al. The cover uncovered: bark control over wood decomposition. J. Ecol. 106, 2147–2160 (2018).

    Article  Google Scholar 

  • 35.

    Jones, D. A. & O’Hara, K. L. Variation in carbon fraction, density, and carbon density in conifer tree tissues. Forests 9, 430 (2018).

    Article  Google Scholar 

  • 36.

    Fukasawa, Y. The geographical gradient of pine log decomposition in Japan. For. Ecol. Manag. 349, 29–35 (2015).

  • 37.

    IPCC. in 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Vol. 4: Agriculture, Forestry and Other Land Use (eds Blain, D., Agus, F., Alfaro, M. A. & Vreuls, H.) 68 (IPCC, 2019).

  • 38.

    Jones, D. A. & O’Hara, K. L. The influence of preparation method on measured carbon fractions in tree tissues. Tree Physiol. 36, 1177–1189 (2016).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 39.

    Beech, E., Rivers, M., Oldfield, S. & Smith, P. GlobalTreeSearch: the first complete global database of tree species and country distributions. J. Sustain. 36, 454–489 (2017).

    Article  Google Scholar 

  • 40.

    Lamlom, S. H. & Savidge, R. A. A reassessment of carbon content in wood: variation within and between 41 North American species. Biomass Bioenergy 25, 381–388 (2003).

    CAS  Article  Google Scholar 

  • 41.

    Thomas, S. C. & Malczewski, G. Wood carbon content of tree species in Eastern China: interspecific variability and the importance of the volatile fraction. J. Environ. Manag. 85, 659–662 (2007).

    CAS  Article  Google Scholar 

  • 42.

    Hafner, S. D., Groffman, P. M. & Mitchell, M. J. Leaching of dissolved organic carbon, dissolved organic nitrogen, and other solutes from coarse woody debris and litter in a mixed forest in New York State. Biogeochemistry 74, 257–282 (2005).

    CAS  Article  Google Scholar 

  • 43.

    Hillis, W. Chemical aspects of heartwood formation. Wood Sci. Technol. 2, 241–259 (1968).

    CAS  Article  Google Scholar 

  • 44.

    Meerts, P. Mineral nutrient concentrations in sapwood and heartwood: a literature review. Ann. Sci. 59, 713–722 (2002).

    Article  Google Scholar 

  • 45.

    Bert, D. & Danjon, F. Carbon concentration variations in the roots, stem and crown of mature Pinus pinaster (Ait.). Ecol. Manag. 222, 279–295 (2006).

    Article  Google Scholar 

  • 46.

    Jones, D. A. & O’Hara, K. L. Carbon density in managed coast redwood stands: implications for forest carbon estimation. Forestry 85, 99–110 (2012).

    Article  Google Scholar 

  • 47.

    Ma, S. et al. Variations and determinants of carbon content in plants: a global synthesis. Biogeosciences 15, 693 (2018).

    ADS  CAS  Article  Google Scholar 

  • 48.

    Cornelissen, J. H. C. et al. Leaf digestibility and litter decomposability are related in a wide range of subarctic plant species and types. Funct. Ecol. 18, 779–786 (2004).

    Article  Google Scholar 

  • 49.

    Ganjegunte, G. K., Condron, L. M., Clinton, P. W., Davis, M. R. & Mahieu, N. Decomposition and nutrient release from radiata pine (Pinus radiata) coarse woody debris. Ecol. Manag. 187, 197–211 (2004).

    Article  Google Scholar 

  • 50.

    Pettersen, R. C. in The Chemistry of Solid Wood (ed. Rowell, R.) 57–126 (American Chemical Society, 1984).

  • 51.

    Berg, B., Ekbohm, G. & McClaugherty, C. Lignin and holocellulose relations during long-term decomposition of some forest litters. Long-term decomposition in a Scots pine forest. IV. Can. J. Bot. 62, 2540–2550 (1984).

    CAS  Article  Google Scholar 

  • 52.

    Schowalter, T. D., Zhang, Y. L. & Sabin, T. E. Decomposition and nutrient dynamics of oak Quercus spp. logs after five years of decomposition. Ecography 21, 3–10 (1998).

    Article  Google Scholar 

  • 53.

    Buxton, R. D. Termites and the turnover of dead wood in an arid tropical environment. Oecologia 51, 379–384 (1981).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 54.

    Riley, R. et al. Extensive sampling of basidiomycete genomes demonstrates inadequacy of the white-rot/brown-rot paradigm for wood decay fungi. Proc. Natl Acad. Sci. USA 111, 9923–9928 (2014).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 55.

    Moore, T. R., Trofymow, J. A., Prescott, C. E., Titus, B. D. & Group, C. W. Can short-term litter-bag measurements predict long-term decomposition in northern forests? Plant Soil 416, 419–426 (2017).

    CAS  Article  Google Scholar 

  • 56.

    vandenEnden, L., Frey, S. D., Nadelhoffer, K. J., LeMoine, J. M., Lajtha, K. & Simpson, M. J. Molecular-level changes in soil organic matter composition after 10 years of litter, root and nitrogen manipulation in a temperate forest. Biogeochemistry 141, 183–197 (2018).

    CAS  Article  Google Scholar 

  • 57.

    Warner, D. L., Villarreal, S., McWilliams, K., Inamdar, S. & Vargas, R. Carbon dioxide and methane fluxes from tree stems, coarse woody debris, and soils in an upland temperate forest. Ecosystems 20, 1205–1216 (2017).

    CAS  Article  Google Scholar 

  • 58.

    Van Mantgem, P. J. et al. Widespread increase of tree mortality rates in the western United States. Science 323, 521–524 (2009).

    ADS  PubMed  Article  CAS  PubMed Central  Google Scholar 

  • 59.

    Brando, P. M. et al. Abrupt increases in Amazonian tree mortality due to drought–fire interactions. Proc. Natl Acad. Sci. USA 111, 6347–6352 (2014).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  • 60.

    Brad, B. et al. The taxonomic name resolution service: an online tool for automated standardization of plant names. BMC Bioinform. 14, 16 (2013).

    Article  Google Scholar 

  • 61.

    Krankina, O. N. & Harmon, M. E. Dynamics of the dead wood carbon pool in northwestern Russian boreal forests. Water Air Soil Pollut. 82, 227–238 (1995).

    ADS  CAS  Article  Google Scholar 

  • 62.

    Kattge, J. et al. TRY plant trait database—enhanced coverage and open access. Glob. Change Biol. 26, 119–188 (2020).

    ADS  Article  Google Scholar 

  • 63.

    Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article  Google Scholar 

  • 64.

    Lenth, R. V. Least-squares means: the R Package lsmeans. J. Stat. Softw. 69, 1–33 (2016).

    Article  Google Scholar 

  • 65.

    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2009).

  • 66.

    Fox, J. & Weisberg, S. An R Companion to Applied Regression 2nd edn (Sage, 2011).

  • 67.

    Messier, J., McGill, B. J. & Lechowicz, M. J. How do traits vary across ecological scales? A case for trait-based ecology. Ecol. Lett. 13, 838–848 (2010).

    PubMed  Article  PubMed Central  Google Scholar 

  • 68.

    Martin, A. R. et al. Intraspecific trait variation across multiple scales: the leaf economics spectrum in coffee. Funct. Ecol. 31, 604–612 (2017).

    Article  Google Scholar 

  • 69.

    Pinheiro, J. et al. nlme: linear and nonlinear mixed effects models. R package version 3.1-131. https://CRAN.R-project.org/package=nlme (2017).

  • 70.

    Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).


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