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Global patterns in wood carbon concentration across the world’s trees and forests

Abstract

Wood carbon concentrations play a central role in forest carbon accounting, and are fundamentally linked to the growth strategies of woody plants. Yet there are no comprehensive assessments of wood carbon among trees globally, and coarse approximations of wood carbon (for example, 50%) are employed in virtually all benchmark models and assessments of forest carbon. We consolidated the largest database for any wood chemical trait—2,228 wood carbon observations from 636 species across all forested biomes—to derive robust wood carbon fractions for forest carbon accounting. Carbon fractions show substantial variation among forest biomes, and indicate errors in the existing forest carbon estimates of 4.8%, on average, and most extreme errors of 8.9% in tropical forests. The data also demonstrate that wood carbon concentrations show a phylogenetic signal and are co-evolved with, and negatively related to, wood density, thus representing a key plant trait that links plant functional biology to ecosystem processes worldwide.

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Fig. 1: Tree C concentration sampling sites.
Fig. 2: Variation in wood C concentrations across the entire wood C database.
Fig. 3: Relationships between wood C concentration and WD.
Fig. 4: Phylogenetic variation in wood C concentrations.

Data availability

The compiled data set used in our analyses is available through the TRY Functional Trait Database (data set ID number 433), and is available from the corresponding author upon request.

References

  1. 1.

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

    Article  Google Scholar 

  2. 2.

    Kohl, M. et al. Changes in forest production, biomass and carbon: results from the 2015 UN FAO Global Forest Resource Assessment. Forest Ecol. Manag. 352, 21–34 (2015).

    Article  Google Scholar 

  3. 3.

    Keenan, R. J. et al. Dynamics of global forest area: results from the FAO Global Forest Resources Assessment 2015. Forest Ecol. Manag. 352, 9–20 (2015).

    Article  Google Scholar 

  4. 4.

    van der Werf, G. R. et al. CO2 emissions from forest loss. Nat. Geosci. 2, 829–829 (2009).

    Article  Google Scholar 

  5. 5.

    Canadell, J. G. & Raupach, M. R. Managing forests for climate change mitigation. Science 320, 1456–1457 (2008).

    Article  Google Scholar 

  6. 6.

    Asner, G. P. et al. High-resolution forest carbon stocks and emissions in the Amazon. Proc. Natl Acad. Sci. USA 107, 16738–16742 (2010).

    Article  Google Scholar 

  7. 7.

    Asner, G. P. Tropical forest carbon assessment: integrating satellite and airborne mapping approaches. Environ. Res. Lett. 4, 034009 (2009).

    Article  Google Scholar 

  8. 8.

    Clark, D. B. & Kellner, J. R. Tropical forest biomass estimation and the fallacy of misplaced concreteness. J. Veg. Sci. 23, 1191–1196 (2012).

    Article  Google Scholar 

  9. 9.

    USDA Agriculture and Forestry Greenhouse Gas Inventory: 1990–2008 Tech. Bull. 1930 (USDA, OCE, CCPO, 2011).

  10. 10.

    Saatchi, S. S. et al. Benchmark map of forest carbon stocks in tropical regions across three continents. Proc. Natl Acad. Sci. USA 108, 9899–9904 (2011).

    Article  Google Scholar 

  11. 11.

    Baccini, A. et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nat. Clim. Change 2, 182–185 (2012).

    Article  Google Scholar 

  12. 12.

    Aalde, U. et al. in IPCC Guidelines for National Greenhouse Gas Inventories Vol. 4 (eds Eggleston, S., Buendia, L., Miwa, K., Ngara, T. & Tanabe, K.) Ch. 4 (IPPC, 2006).

  13. 13.

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

    Article  Google Scholar 

  14. 14.

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

    Article  Google Scholar 

  15. 15.

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

    Article  Google Scholar 

  16. 16.

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

  17. 17.

    Martin, A. R., Thomas, S. C. & Zhao, Y. Size-dependent changes in wood chemical traits: a comparison of neotropical saplings and large trees. AoB Plants 5, plt039 (2013).

    Article  Google Scholar 

  18. 18.

    Becker, G. S., Braun, D., Gliniars, R. & Dalitz, H. Relations between wood variables and how they relate to tree size variables of tropical African tree species. Trees Struct. Funct. 26, 1101–1112 (2012).

    Article  Google Scholar 

  19. 19.

    Elias, M. & Potvin, C. Assessing inter- and intra-specific variation in trunk carbon concentration for 32 neotropical tree species. Can. J. Forest Res. 33, 1039–1045 (2003).

    Article  Google Scholar 

  20. 20.

    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).

    Article  Google Scholar 

  21. 21.

    Zanne, A. et al. Global Wood Density Database (DRYAD, accessed 1 November 2017); https://doi.org/10.5061/dryad.234/1

  22. 22.

    Chave, J. et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351–366 (2009).

    Article  Google Scholar 

  23. 23.

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

    Article  Google Scholar 

  24. 24.

    Poorter, L. et al. Biomass resilience of Neotropical secondary forests. Nature 530, 211–214 (2016).

    Article  Google Scholar 

  25. 25.

    Boerjan, W., Ralph, J. & Baucher, M. Lignin biosynthesis. Annu. Rev. Plant Biol. 54, 519–546 (2003).

    Article  Google Scholar 

  26. 26.

    Martin, A. R., Erickson, D. L., Kress, W. J. & Thomas, S. C. Wood nitrogen concentrations in tropical trees: phylogenetic patterns and ecological correlates. New Phytol. 204, 484–495 (2014).

    Article  Google Scholar 

  27. 27.

    Myers, J. A. & Kitajima, K. Carbohydrate storage enhances seedling shade and stress tolerance in a neotropical forest. J. Ecol. 95, 383–395 (2007).

    Article  Google Scholar 

  28. 28.

    Diaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).

    Article  Google Scholar 

  29. 29.

    Vance, C. P., Kirk, T. K. & Sherwood, R. T. Lignification as a mechanism of disease resistance. Annu. Rev. Phytopathol. 18, 259–288 (1980).

    Article  Google Scholar 

  30. 30.

    Thomas, S. & Martin, A. Data From: Carbon Content of Tree Tissues: A Synthesis (DRYAD, 2012); https://doi.org/10.5061/dryad.69sg2

  31. 31.

    Kattge, J. et al. TRY—a global database of plant traits. Global Change Biol. 17, 2905–2935 (2011).

    Article  Google Scholar 

  32. 32.

    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. Forest Ecol. Manag. 291, 259–267 (2013).

    Article  Google Scholar 

  33. 33.

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

    Article  Google Scholar 

  34. 34.

    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).

    Article  Google Scholar 

  35. 35.

    Pompa-Garcia, M., Sigala-Rodriguez, J. A., Jurado, E. & Flores, J. Tissue carbon concentration of 175 Mexican forest species. iForest 10, 754–758 (2017).

    Article  Google Scholar 

  36. 36.

    Delignette-Muller, M. L. & Dutang, C. fitdistrplus: an R package for fitting distributions. J. Stat. Softw. 64, 1–34 (2015).

    Article  Google Scholar 

  37. 37.

    Pinheiro, J et al. nlme: Linear and Nonlinear Mixed Effects Models (CRAN-R, 2016).

  38. 38.

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

    Article  Google Scholar 

  39. 39.

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

    Article  Google Scholar 

  40. 40.

    Webb, C. O. & Donoghue, M. J. Phylomatic: tree assembly for applied phylogenetics. Mol. Ecol. Notes 5, 181–183 (2005).

    Article  Google Scholar 

  41. 41.

    Webb, C. O., Ackerly, D. D. & Kembel, S. W. Phylocom: software for the analysis of phylogenetic community structure and trait evolution. Bioinformatics 24, 2098–2100 (2008).

    Article  Google Scholar 

  42. 42.

    Wikstrom, N., Savolainen, V. & Chase, M. W. Evolution of the angiosperms: calibrating the family tree. Proc. R. Soc B 268, 2211–2220 (2001).

    Article  Google Scholar 

  43. 43.

    Gastauer, M. & Meira-Neto, J. A. A. An enhanced calibration of a recently released megatree for the analysis of phylogenetic diversity. Braz. J. Biol. 76, 619–628 (2016).

    Article  Google Scholar 

  44. 44.

    Blomberg, S. P., Garland, T. & Ives, A. R. Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution 57, 717–745 (2003).

    Article  Google Scholar 

  45. 45.

    Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).

    Article  Google Scholar 

  46. 46.

    Chave, J. et al. Regional and phylogenetic variation of wood density across 2456 neotropical tree species. Ecol. Appl. 16, 2356–2367 (2006).

    Article  Google Scholar 

  47. 47.

    Lefcheck, J. S. piecewiseSEM: Piecewise structural equation modeling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).

    Article  Google Scholar 

  48. 48.

    Felsenstein, J. Phylogenies and the comparative method. Am. Nat. 125, 1–15 (1985).

    Article  Google Scholar 

  49. 49.

    Garland, T., Harvey, P. H. & Ives, A. R. Procedures for the analysis of comparative data using phylogenetically independent contrasts. Syst. Biol. 41, 18–32 (1992).

    Article  Google Scholar 

  50. 50.

    Thomas, S. C., Martin, A. R. & Mycroft, E. E. Tropical trees in a wind-exposed island ecosystem: height–diameter allometry and size at onset of maturity. J. Ecol. 103, 594–605 (2015).

    Article  Google Scholar 

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Acknowledgements

The authors thank K. L. Smith for helpful comments that improved the manuscript. This research was supported by a graduate research bursary to D.M. provided by the Department of Physical and Environmental Sciences at the University of Toronto Scarborough, Canada. S. C. Thomas was supported by funding from the Natural Science and Engineering Research Council of Canada.

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A.R.M. and S.C.T. conceived the study. A.R.M. led the manuscript preparation and final analyses. M.D. led the data compilation and preliminary data analysis. S.C.T. and M.D. helped write and edit the manuscript.

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Correspondence to Adam R. Martin.

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Supplementary Figures 1–3 and Supplementary Tables 1–4.

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Martin, A.R., Doraisami, M. & Thomas, S.C. Global patterns in wood carbon concentration across the world’s trees and forests. Nature Geosci 11, 915–920 (2018). https://doi.org/10.1038/s41561-018-0246-x

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