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.
Subscribe to Journal
Get full journal access for 1 year
only $3.90 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011)
Medvigy, D., Wofsy, S. C., Munger, J. W., Hollinger, D. Y. & Moorcroft, P. R. Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2. J. Geophys. Res. 114, G01002 (2009)
Caspersen, J. P., Vanderwel, M. C., Cole, W. G. & Purves, D. W. How stand productivity results from size- and competition-dependent growth and mortality. PLoS ONE 6, e28660 (2011)
Kutsch, W. L. et al. in Old-Growth Forests: Function, Fate and Value (eds Wirth, C., Gleixner, G. & Heimann, M. ) 57–79 (Springer, 2009)
Meinzer F. C., Lachenbruch B., Dawson T. E., eds. Size- and Age-Related Changes in Tree Structure and Function (Springer, 2011)
Enquist, B. J., West, G. B., Charnov, E. L. & Brown, J. H. Allometric scaling of production and life-history variation in vascular plants. Nature 401, 907–911 (1999)
Sillett, S. C. et al. Increasing wood production through old age in tall trees. For. Ecol. Manage. 259, 976–994 (2010)
Mencuccini, M. et al. Size-mediated ageing reduces vigour in trees. Ecol. Lett. 8, 1183–1190 (2005)
Drake, J. E., Raetz, L. M., Davis, S. C. & DeLucia, E. H. Hydraulic limitation not declining nitrogen availability causes the age-related photosynthetic decline in loblolly pine (Pinus taeda L.). Plant Cell Environ. 33, 1756–1766 (2010)
Ryan, M. G., Binkley, D. & Fownes, J. H. Age-related decline in forest productivity: pattern and process. Adv. Ecol. Res. 27, 213–262 (1997)
Thomas, S. C. in Size- and Age-Related Changes in Tree Structure and Function (eds Meinzer, F. C., Lachenbruch, B. & Dawson, T. E. ) 33–64 (Springer, 2011)
Thomas, H. Senescence, ageing and death of the whole plant. New Phytol. 197, 696–711 (2013)
Carey, E. V., Sala, A., Keane, R. & Callaway, R. M. Are old forests underestimated as global carbon sinks? Glob. Change Biol. 7, 339–344 (2001)
Phillips, N. G., Buckley, T. N. & Tissue, D. T. Capacity of old trees to respond to environmental change. J. Integr. Plant Biol. 50, 1355–1364 (2008)
Piper, F. I. & Fajardo, A. No evidence of carbon limitation with tree age and height in Nothofagus pumilio under Mediterranean and temperate climate conditions. Ann. Bot. 108, 907–917 (2011)
Weiner, J. & Thomas, S. C. The nature of tree growth and the “age-related decline in forest productivity”. Oikos 94, 374–376 (2001)
Jenkins, J. C., Chojnacky, D. C., Heath, L. S. & Birdsey, R. A. Comprehensive Database of Diameter-based Biomass Regressions for North American Tree Species General Technical Report NE-319, http://www.nrs.fs.fed.us/pubs/6725 (USDA Forest Service, Northeastern Research Station, 2004)
Niklas, K. J. & Enquist, B. J. Canonical rules for plant organ biomass partitioning and annual allocation. Am. J. Bot. 89, 812–819 (2002)
Thomas, S. C. Photosynthetic capacity peaks at intermediate size in temperate deciduous trees. Tree Physiol. 30, 555–573 (2010)
Steppe, K., Niinemets, Ü. & Teskey, R. O. in Size- and Age-Related Changes in Tree Structure and Function (eds Meinzer, F. C., Lachenbruch, B. & Dawson, T. E. ) 235–253 (Springer, 2011)
Gilmore, D. W. & Seymour, R. S. Alternative measures of stem growth efficiency applied to Abies balsamea from four canopy positions in central Maine, USA. For. Ecol. Manage. 84, 209–218 (1996)
Kaufmann, M. R. & Ryan, M. G. Physiographic, stand, and environmental effects on individual tree growth and growth efficiency in subalpine forests. Tree Physiol. 2, 47–59 (1986)
Coomes, D. A., Holdaway, R. J., Kobe, R. K., Lines, E. R. & Allen, R. B. A general integrative framework for modelling woody biomass production and carbon sequestration rates in forests. J. Ecol. 100, 42–64 (2012)
Binkley, D. A hypothesis about the interaction of tree dominance and stand production through stand development. For. Ecol. Manage. 190, 265–271 (2004)
Pretzsch, H. & Biber, P. A re-evaluation of Reineke’s rule and stand density index. For. Sci. 51, 304–320 (2005)
Kashian, D. M., Turner, M. G., Romme, W. H. & Lorimer, C. G. Variability and convergence in stand structural development on a fire-dominated subalpine landscape. Ecology 86, 643–654 (2005)
Munné-Bosch, S. Do perennials really senesce? Trends Plant Sci. 13, 216–220 (2008)
Jump, A. S., Hunt, J. M. & Peñuelas, J. Rapid climate change-related growth decline at the southern range edge of Fagus sylvatica. Glob. Change Biol. 12, 2163–2174 (2006)
Lindenmayer, D. B., Laurance, W. F. & Franklin, J. F. Global decline in large old trees. Science 338, 1305–1306 (2012)
Enquist, B. J., West, G. B. & Brown, J. H. Extensions and evaluations of a general quantitative theory of forest structure and dynamics. Proc. Natl Acad. Sci. USA 106, 7046–7051 (2009)
Condit, R. et al. Tropical forest dynamics across a rainfall gradient and the impact of an El Niño dry season. J. Trop. Ecol. 20, 51–72 (2004)
Condit, R. et al. The importance of demographic niches to tree diversity. Science 313, 98–101 (2006)
Rüger, N., Berger, U., Hubbell, S. P., Vieilledent, G. & Condit, R. Growth strategies of tropical tree species: disentangling light and size effects. PLoS ONE 6, e25330 (2011)
Chave, J. et al. Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145, 87–99 (2005)
Sibly R. M., Brown J. H., Kodric-Brown A., eds. Metabolic Ecology: A Scaling Approach (John Wiley & Sons, 2012)
Zanne, A. E. et al. Data from: Towards a worldwide wood economics spectrum. In Dryad Digital Data Repository, http://dx.doi.org/10.5061/dryad.234 (2009)
Enquist, B. J. & Niklas, K. J. Global allocation rules for patterns of biomass partitioning in seed plants. Science 295, 1517–1520 (2002)
Niklas, K. J. Plant allometry: is there a grand unifying theory? Biol. Rev. 79, 871–889 (2004)
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H. & Teller, E. Equation of state calculations by fast computing machines. J. Chem. Phys. 21, 1087–1092 (1953)
Rüger, N., Huth, A., Hubbell, S. P. & Condit, R. Determinants of mortality across a tropical lowland rainforest community. Oikos 120, 1047–1056 (2011)
R Development Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2009)
Hilborn, R. & Mangel, M. The Ecological Detective: Confronting Models with Data (Princeton Univ. Press, 1997)
Chambers, J. Q., Dos Santos, J., Ribeiro, R. J. & Higuchi, N. Tree damage, allometric relationships, and above-ground net primary production in central Amazon forest. For. Ecol. Manage. 152, 73–84 (2001)
Baskerville, G. L. Use of logarithmic regression in the estimation of plant biomass. Can. J. For. Res. 2, 49–53 (1972)
Canham, C. D. et al. Neighborhood analyses of canopy tree competition along environmental gradients in New England forests. Ecol. Appl. 16, 540–554 (2006)
Coates, K. D., Canham, C. D. & LePage, P. T. Above- versus below-ground competitive effects and responses of a guild of temperate tree species. J. Ecol. 97, 118–130 (2009)
Pretzsch, H. & Biber, P. Size-symmetric versus size-asymmetric competition and growth partitioning among trees in forest stands along an ecological gradient in central Europe. Can. J. For. Res. 40, 370–384 (2010)
Gómez-Aparicio, L., García-Valdés, R., Ruíz-Benito, P. & Zavala, M. A. Disentangling the relative importance of climate, size and competition on tree growth in Iberian forests: implications for forest management under global change. Glob. Change Biol. 17, 2400–2414 (2011)
Das, A. The effect of size and competition on tree growth rate in old-growth coniferous forests. Can. J. For. Res. 42, 1983–1995 (2012)
Zianis, D., Muukkonen, P., Makipaa, R. & Mencuccini, M. Biomass and stem volume equations for tree species in Europe. Silva Fennica Monogr. 4, 1–63 (2005)
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.
The authors declare no competing financial interests.
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
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).
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.
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.
About this article
Cite this article
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
Efficient, Sustainable, and Multifunctional Carbon Offsetting to Boost Forest Management: A Comparative Case Study
Journal of Ecology (2021)
Nature Plants (2021)
Biodiversity, environmental context and structural attributes as drivers of aboveground biomass in shrublands at the middle and lower reaches of the Yellow River basin
Science of The Total Environment (2021)