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Rate of tree carbon accumulation increases continuously with tree size

Nature volume 507, pages 90–93 (2014)Cite this article

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Abstract

Forests are major components of the global carbon cycle, providing substantial feedback to atmospheric greenhouse gas concentrations1. Our ability to understand and predict changes in the forest carbon cycle—particularly net primary productivity and carbon storage—increasingly relies on models that represent biological processes across several scales of biological organization, from tree leaves to forest stands2,3. Yet, despite advances in our understanding of productivity at the scales of leaves and stands, no consensus exists about the nature of productivity at the scale of the individual tree4,5,6,7, in part because we lack a broad empirical assessment of whether rates of absolute tree mass growth (and thus carbon accumulation) decrease, remain constant, or increase as trees increase in size and age. Here we present a global analysis of 403 tropical and temperate tree species, showing that for most species mass growth rate increases continuously with tree size. Thus, large, old trees do not act simply as senescent carbon reservoirs but actively fix large amounts of carbon compared to smaller trees; at the extreme, a single big tree can add the same amount of carbon to the forest within a year as is contained in an entire mid-sized tree. The apparent paradoxes of individual tree growth increasing with tree size despite declining leaf-level8,9,10 and stand-level10 productivity can be explained, respectively, by increases in a tree’s total leaf area that outpace declines in productivity per unit of leaf area and, among other factors, age-related reductions in population density. Our results resolve conflicting assumptions about the nature of tree growth, inform efforts to undertand and model forest carbon dynamics, and have additional implications for theories of resource allocation11 and plant senescence12.

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Figure 1: Example model fits for tree mass growth rates.
Figure 2: Aboveground mass growth rates for the 403 tree species, by continent.
Figure 3: Aboveground mass growth rates of species in our data set compared with E. regnans and S. sempervirens.

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Acknowledgements

We thank the hundreds of people who have established and maintained the forest plots and their associated databases; M. G. Ryan for comments on the manuscript; C. D. Canham and T. Hart for supplying data; C. D. Canham for discussions and feedback; J. S. Baron for hosting our workshops; and Spain’s Ministerio de Agricultura, Alimentación y Medio Ambiente (MAGRAMA) for granting access to the Spanish Forest Inventory Data. Our analyses were supported by the United States Geological Survey (USGS) John Wesley Powell Center for Analysis and Synthesis, the USGS Ecosystems and Climate and Land Use Change mission areas, the Smithsonian Institution Global Earth Observatory—Center for Tropical Forest Science (CTFS), and a University of Nebraska-Lincoln Program of Excellence in Population Biology Postdoctoral Fellowship (to N.G.B.). In addition, X.W. was supported by National Natural Science Foundation of China (31370444) and State Key Laboratory of Forest and Soil Ecology (LFSE2013-11). Data collection was funded by a broad range of organizations including the USGS, the CTFS, the US National Science Foundation, the Andrews LTER (NSF-LTER DEB-0823380), the US National Park Service, the US Forest Service (USFS), the USFS Forest Inventory and Analysis Program, the John D. and Catherine T. MacArthur Foundation, the Andrew W. Mellon Foundation, MAGRAMA, the Council of Agriculture of Taiwan, the National Science Council of Taiwan, the National Natural Science Foundation of China, the Knowledge Innovation Program of the Chinese Academy of Sciences, Landcare Research and the National Vegetation Survey Database (NVS) of New Zealand, the French Fund for the Global Environment and Fundación ProYungas. This paper is a contribution from the Western Mountain Initiative, a USGS global change research project. Any use of trade names is for descriptive purposes only and does not imply endorsement by the USA government.

Author information

Author notes

  1. N. G. Beckman & N. Rüger

    Present address: Present addresses: Mathematical Biosciences Institute, Ohio State University, Columbus, Ohio 43210, USA (N.G.B.); German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, 04103 Leipzig, Germany (N.R.).,

Authors and Affiliations

  1. US Geological Survey, Western Ecological Research Center, Three Rivers, 93271, California, USA

    N. L. Stephenson & A. J. Das

  2. Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Republic of Panama,

    R. Condit, N. Rüger & S. P. Hubbell

  3. School of Biological Sciences, University of Nebraska, Lincoln, 68588, Nebraska, USA

    S. E. Russo & N. G. Beckman

  4. Department of Forest and Ecosystem Science, University of Melbourne, Victoria 3121, Australia,

    P. J. Baker

  5. Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK,

    D. A. Coomes

  6. Department of Geography, University College London, London WC1E 6BT, UK,

    E. R. Lines

  7. School of Botany, University of Melbourne, Victoria 3010, Australia,

    W. K. Morris

  8. Spezielle Botanik und Funktionelle Biodiversität, Universität Leipzig, 04103 Leipzig, Germany,

    N. Rüger

  9. Jardín Botánico de Medellín, Calle 73, No. 51D-14, Medellín, Colombia,

    E. Álvarez

  10. Instituto de Ecología Regional, Universidad Nacional de Tucumán, 4107 Yerba Buena, Tucumán, Argentina,

    C. Blundo, H. R. Grau & A. Malizia

  11. Department of National Parks, Research Office, Wildlife and Plant Conservation, Bangkok 10900, Thailand,

    S. Bunyavejchewin

  12. Department of Botany and Plant Physiology, Buea, Southwest Province, Cameroon,

    G. Chuyong

  13. Smithsonian Institution Global Earth Observatory—Center for Tropical Forest Science, Smithsonian Institution, PO Box 37012, Washington, DC 20013, USA,

    S. J. Davies & D. Kenfack

  14. Departamento de Ciencias Forestales, Universidad Nacional de Colombia, Medellín, Colombia

    Á. Duque

  15. Wildlife Conservation Society, Kinshasa/Gombe, Democratic Republic of the Congo

    C. N. Ewango & J.-R. Makana

  16. Unité Mixte de Recherche—Peuplements Végétaux et Bioagresseurs en Milieu Tropical, Université de la Réunion/CIRAD, 97410 Saint Pierre, France,

    O. Flores

  17. School of Environmental and Forest Sciences, University of Washington, Seattle, 98195, Washington, USA

    J. F. Franklin

  18. State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, 110164, China

    Z. Hao & X. Wang

  19. Department of Forest Ecosystems and Society, Oregon State University, Corvallis, 97331, Oregon, USA

    M. E. Harmon & R. J. Pabst

  20. Department of Ecology and Evolutionary Biology, University of California, Los Angeles, 90095, California, USA

    S. P. Hubbell

  21. Department of Life Science, Tunghai University, Taichung City, 40704, Taiwan

    Y. Lin

  22. Facultad de Ciencias Agrarias, Universidad Nacional de Jujuy, 4600 San Salvador de Jujuy, Argentina,

    L. R. Malizia

  23. Faculty of Forestry, Kasetsart University, ChatuChak Bangkok 10900, Thailand,

    N. Pongpattananurak

  24. Taiwan Forestry Research Institute, Taipei 10066, Taiwan,

    S.-H. Su

  25. Department of Natural Resources and Environmental Studies, National Dong Hwa University, Hualien 97401, Taiwan,

    I-F. Sun

  26. Sarawak Forestry Department, Kuching, 93660, Sarawak, Malaysia

    S. Tan

  27. Department of Botany and Plant Pathology, Oregon State University, Corvallis, 97331, Oregon, USA

    D. Thomas

  28. US Geological Survey, Western Ecological Research Center, Arcata, 95521, California, USA

    P. J. van Mantgem

  29. Landcare Research, PO Box 40, Lincoln 7640, New Zealand,

    S. K. Wiser

  30. Department of Life Sciences, Forest Ecology and Restoration Group, University of Alcalá, Alcalá de Henares, 28805 Madrid, Spain,

    M. A. Zavala

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  1. N. L. Stephenson
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Contributions

N.L.S. and A.J.D. conceived the study with feedback from R.C. and D.A.C., N.L.S., A.J.D., R.C. and S.E.R. wrote the manuscript. R.C. devised the main analytical approach and wrote the computer code. N.L.S., A.J.D., R.C., S.E.R., P.J.B., N.G.B., D.A.C., E.R.L., W.K.M. and N.R. performed analyses. N.L.S., A.J.D., R.C., S.E.R., P.J.B., D.A.C., E.R.L., W.K.M., E.Á., C.B., S.B., G.C., S.J.D., Á.D., C.N.E., O.F., J.F.F., H.R.G., Z.H., M.E.H., S.P.H., D.K., Y.L., J.-R.M., A.M., L.R.M., R.J.P., N.P., S.-H.S., I-F.S., S.T., D.T., P.J.v.M., X.W., S.K.W. and M.A.Z. supplied data and sources of allometric equations appropriate to their data.

Corresponding author

Correspondence to N. L. Stephenson.

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Competing interests

The authors declare no competing financial interests.

Additional information

Fitted model parameters for each species have been deposited in USGS’s ScienceBase at http://dx.doi.org/10.5066/F7JS9NFM.

Extended data figures and tables

Extended Data Figure 1 Summary of model fits for tree mass growth rates.

Bars show the percentage of species with mass growth rates that increase with tree mass for each bin; black shading indicates percentage significant at P ≤ 0.05. Tree masses increase with bin number. a, Species fitted with one bin (165 species); b, Species fitted with two bins (139 species); c, Species fitted with three bins (56 species); and d, Species fitted with four bins (43 species).

Extended Data Figure 2 Log–log model fits of mass growth rates for 381 tree species, by continent.

Trees with growth rates ≤ 0 were dropped from the analysis, reducing the number of species meeting our threshold sample size for analysis. a, Africa (33 species); b, Asia (123 species); c, Australasia (22 species); d, Central and South America (73 species); e, Europe (41 species); and f, North America (89 species). Trunk diameters are approximate values for reference, based on the average diameters of trees of a given mass.

Extended Data Figure 3 Aboveground mass growth rates for 41 tree species in the absence of competition.

The ‘+’ or ‘−’ symbol preceding each species code indicates, respectively, species with mass growth rates that increased continuously with tree size or species with mass growth rates that declined in the largest trees. Sources of the diameter growth equations used to calculate mass growth were: a, ref. 45; b, ref. 46; c, ref. 48; d, ref. 47; and e, ref. 49. ABAM, Abies amabilis; ABBA, Abies balsamea; ABCO, Abies concolor; ABLA, Abies lasiocarpa; ABMA, Abies magnifica; ACRU, Acer rubrum; ACSA, Acer saccharum; BEAL, Betula alleghaniensis; BELE, Betula lenta; BEPA, Betula papyrifera; CADE, Calocedrus decurrens; CASA, Castanea sativa; FAGR, Fagus grandifolia; FASY, Fagus sylvatica; FRAM, Fraxinus americana; JUTH, Juniperus thurifera; PIAB, Picea abies; PICO, Pinus contorta; PIHA, Pinus halepensis; PIHY, Picea hybrid (a complex of Picea glauca, P. sitchensis and P. engelmannii); PILA, Pinus lambertiana; PINI, Pinus nigra; PIPINA, Pinus pinaster; PIPINE, Pinus pinea; PIRU, Picea rubens; PIST, Pinus strobus; PISY, Pinus sylvestris; PIUN, Pinus uncinata; POBA, Populus balsamifera ssp. trichocarpa; POTR, Populus tremuloides; PRSE, Prunus serotina; QUFA, Quercus faginea; QUIL, Quercus ilex; QUPE, Quercus petraea; QUPY, Quercus pyrenaica; QURO, Quercus robar; QURU, Quercus rubra; QUSU, Quercus suber; THPL, Thuja plicata; TSCA, Tsuga canadensis; and TSHE, Tsuga heterophylla.

Extended Data Figure 4 Residuals of predicted minus observed tree mass.

a, The allometric equation for moist tropical forests34—used for the majority of tree species—shows no evident systematic bias in predicted aboveground dry mass, M, relative to trunk diameter (n = 1,504 trees). b, In contrast, our simplest form of allometric equation—used for 22% of our species and here applied to nine temperate species—shows an apparent bias towards overestimating M for large trees (n = 1,358 trees). c, New allometries that we created for the nine temperate species removed the apparent bias in predicted M.

Extended Data Figure 5 Estimated mass growth rates of the nine temperate species of Extended Data Fig. 4.

Growth was estimated using the simplest form of allometric model [log(M) = a + blog(D)] (a) and our allometric models fitted with piecewise linear regression (b). Regardless of the allometric model form, all nine species show increasing G in the largest trees.

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Stephenson, N., Das, A., Condit, R. et al. Rate of tree carbon accumulation increases continuously with tree size. Nature 507, 90–93 (2014). https://doi.org/10.1038/nature12914

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