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Old and ancient trees are life history lottery winners and vital evolutionary resources for long-term adaptive capacity


Trees can live for many centuries with sustained fecundity and death is largely stochastic. We use a neutral stochastic model to examine tree demographic patterns that emerge over time, across a range of population sizes and empirically observed mortality rates. A small proportion of trees (~1% at 1.5% mortality) are life-history ‘lottery winners’, achieving ages >10–20× the median age. Maximum age increases with bigger populations and lower mortality rates. One-quarter of trees (~24%) achieve ages that are three to four times greater than the median age. Three age classes (mature, old and ancient) contribute unique evolutionary diversity across complex environmental cycles. Ancient trees are an emergent property of forests that requires many centuries to generate. They radically change variance in generation time and population fitness, bridging centennial environmental cycles. These life-history ‘lottery’ winners are vital to long-term forest adaptive capacity and provide invaluable data about environmental history and individual longevity. Old and ancient trees cannot be replaced through restoration or regeneration for many centuries. They must be protected to preserve their invaluable diversity.

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Fig. 1: Maximum tree and forest climax age, given different population sizes and annual stochastic mortality rates.
Fig. 2: Mean age and standard deviation of three age classes, given different mortality rates and population sizes, across 25 replicates.
Fig. 3: Mean and absolute maximum age achieved across 25 replicates over 15,000 years, given different population sizes and annual mortality.
Fig. 4: Population demographics in relation to changing environmental selection pressure (Supplementary Fig. 4), given an annual mortality rate of 1.5%.
Fig. 5: Major mechanisms evolved by ancient trees to defy ageing.
Fig. 6: Canopy rejuvenation and seed production in old trees.

Data availability

The data used in the analyses were generated from the code provided. The authors strongly recommend that the data be generated directly from the code to demonstrate the reliability of the methods and to verify that the results are the same in different computing environments and settings. Computation time to generate the dataset was less than 8 h on a MacBook Pro with 2.5 Ghz Dual-Core Intel Core i7 processor and 16 GB of RAM. The original dataset used in this publication is available upon request from the corresponding author.

Code availability

The models and analyses were written in the Mathematica 12 programming environment. A notebook containing the simulation model and the code used to produce the results and figures has been uploaded to the publication website. Code can also be provided upon request by the corresponding author.


  1. Blicharska, M. & Mikusiński, G. Incorporating social and cultural significance of large old trees in conservation policy. Conserv. Biol. 28, 1558–1567 (2014).

    Article  PubMed  Google Scholar 

  2. Lindenmayer, D. B. & Laurance, W. F. The ecology, distribution, conservation and management of large old trees. Biol. Rev. Camb. Phil. Soc. 92, 1434–1458 (2017).

    Article  Google Scholar 

  3. Munné-Bosch, S. Limits to tree growth and longevity. Trends Plant Sci. 23, 985–993 (2018).

    Article  PubMed  Google Scholar 

  4. Lindenmayer, D. B. Conserving large old trees as small natural features. Biol. Conserv. 211, 51–59 (2017).

    Article  Google Scholar 

  5. Lutz, J. A. et al. Global importance of large-diameter trees. Glob. Ecol. Biogeogr. 27, 849–864 (2018).

    Article  Google Scholar 

  6. Slik, J. W. F. et al. Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics: large trees and tropical forest biomass. Glob. Ecol. Biogeogr. 22, 1261–1271 (2013).

    Article  Google Scholar 

  7. McMahon, S. M., Arellano, G. & Davies, S. J. The importance and challenges of detecting changes in forest mortality rates. Ecosphere 10, e02615 (2019).

    Article  Google Scholar 

  8. Vieira, S. et al. Slow growth rates of Amazonian trees: consequences for carbon cycling. Proc. Natl Acad. Sci. USA 102, 18502–18507 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Martınez-Ramos, M. & Alvarez-Buylla, E. R. How old are tropical rain forest trees? Trends Plant Sci. 3, 400–405 (1998).

    Article  Google Scholar 

  10. Schöngart, J., Bräuning, A., Barbosa, A. C. M. C., Lisi, C. S. & de Oliveira, J. M. in Dendroecology: Tree-Ring Analyses Applied to Ecological Studies (eds Amoroso, M. M. et al.) 35–73 (Springer, 2017).

  11. Brienen, R. J. W. & Zuidema, P. A. Lifetime growth patterns and ages of Bolivian rain forest trees obtained by tree ring analysis. J. Ecol. 94, 481–493 (2006).

    Article  Google Scholar 

  12. Piovesan, G. & Biondi, F. On tree longevity. New Phytol. 231, 1318–1337 (2021).

    Article  PubMed  Google Scholar 

  13. Esquivel-Muelbert, A. et al. Tree mode of death and mortality risk factors across Amazon forests. Nat. Commun. 11, 5515 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Condit, R., Hubbell, S. P. & Foster, R. B. Mortality rates of 205 neotropical tree and shrub species and the impact of a severe drought. Ecol. Monogr. 65, 419–439 (1995).

    Article  Google Scholar 

  15. Acker, S. A. et al. Recent tree mortality and recruitment in mature and old-growth forests in western Washington. Ecol. Manage. 336, 109–118 (2015).

    Article  Google Scholar 

  16. Thomas, R. Q., Kellner, J. R., Clark, D. B. & Peart, D. R. Low mortality in tall tropical trees. Ecology 94, 920–929 (2013).

    Article  Google Scholar 

  17. Stephenson, N. L. & Mantgem, P. J. Forest turnover rates follow global and regional patterns of productivity. Ecol. Lett. 8, 524–531 (2005).

    Article  PubMed  Google Scholar 

  18. Drobyshev, I. et al. Lifespan and mortality of old oaks—combining empirical and modelling approaches to support their management in Southern Sweden. Ann. Sci. 65, 401–401 (2008).

    Article  Google Scholar 

  19. Richardson, S. J. et al. Large-tree growth and mortality rates in forests of the central North Island, New Zealand. N. Z. J. Ecol. 33, 208–215 (2009).

    Google Scholar 

  20. Chambers, J. Q., Higuchi, N. & Schimel, J. P. Ancient trees in Amazonia. Nature 391, 135–136 (1998).

    Article  CAS  Google Scholar 

  21. Laurance, W. F., Nascimento, H. E. M., Laurance, S. G., Condit, R., D’Angelo, S. & Andrade, A. Inferred longevity of Amazonian rainforest trees based on a long-term demographic study. Ecol. Manage. 190, 131–143 (2004).

    Article  Google Scholar 

  22. Fichtler, E., Clark, D. A. & Worbes, M. Age and long-term growth of trees in an old-growth tropical rain forest, based on analyses of tree rings and C-14. Biotropica 35, 306–317 (2003).

    Article  Google Scholar 

  23. Foster, D. R. Land-use history (1730–1990) and vegetation dynamics in central New England, USA. J. Ecol. 80, 753–771 (1992).

    Article  Google Scholar 

  24. Senf, C., Buras, A., Zang, C. S., Rammig, A. & Seidl, R. Excess forest mortality is consistently linked to drought across Europe. Nat. Commun. 11, 6200 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  26. Qiu, T. et al. Is there tree senescence? The fecundity evidence. Proc. Natl Acad. Sci. USA 118, (2021).

  27. Barrett, S. C. H. Influences of clonality on plant sexual reproduction. Proc. Natl Acad. Sci. USA 112, 8859–8866 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Thomas, H. Senescence, ageing and death of the whole plant. New Phytol. 197, 696–711 (2013).

    Article  PubMed  Google Scholar 

  29. Munné-Bosch, S. Long-lived trees are not immortal. Trends Plant Sci. 25, 846–849 (2020).

    Article  PubMed  Google Scholar 

  30. Sillett, S. C. et al. Comparative development of the four tallest conifer species. Ecol. Manage. 480, 118688 (2021).

    Article  Google Scholar 

  31. Koch, G. W., Sillett, S. C., Jennings, G. M. & Davis, S. D. The limits to tree height. Nature 428, 851–854 (2004).

    Article  CAS  PubMed  Google Scholar 

  32. Thomas, H. Ageing in plants. Mech. Ageing Dev. 123, 747–753 (2002).

    Article  PubMed  Google Scholar 

  33. Dahlgren, J. P., García, M. B. & Ehrlén, J. Nonlinear relationships between vital rates and state variables in demographic models. Ecology 92, 1181–1187 (2011).

    Article  PubMed  Google Scholar 

  34. Klimešová, J., Malíková, L., Rosenthal, J. & Šmilauer, P. Potential bud bank responses to apical meristem damage and environmental variables: matching or complementing axillary meristems? PLoS ONE 9, e88093 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Plomion, C. et al. Oak genome reveals facets of long lifespan. Nat. Plants 4, 440–452 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Hanlon, V. C. T., Otto, S. P. & Aitken, S. N. Somatic mutations substantially increase the per-generation mutation rate in the conifer Picea sitchensis. Evol. Lett. 1, 95 (2019).

    Google Scholar 

  37. Amaral, J. et al. Advances and promises of epigenetics for forest trees. Trees Livelihoods 11, 976 (2020).

    Google Scholar 

  38. Carbó, M. et al. in Epigenetics in Plants of Agronomic Importance: Fundamentals and Applications: Transcriptional Regulation and Chromatin Remodelling in Plants (eds Alvarez-Venegas, R. et al.) 381–403 (Springer, 2019).

  39. Sow, M. D. et al. in Advances in Botanical Research (eds Mirouze, M. et al.) Vol. 88, 387–453 (Academic Press, 2018).

  40. Das, A., Battles, J., Stephenson, N. L. & van Mantgem, P. J. The contribution of competition to tree mortality in old-growth coniferous forests. Ecol. Manage. 261, 1203–1213 (2011).

    Article  Google Scholar 

  41. Etzold, S. et al. One century of forest monitoring data in Switzerland reveals species-and site-specific trends of climate-induced tree mortality. Front. Plant Sci. 10, (2019).

  42. McNellis, B. E., Smith, A. M. S., Hudak, A. T. & Strand, E. K. Tree mortality in western U.S. forests forecasted using forest inventory and Random Forest classification. Ecosphere 12, (2021).

  43. Piovesan, G. et al. Lessons from the wild: slow but increasing long-term growth allows for maximum longevity in European beech. Ecology 100, e02737 (2019).

    Article  PubMed  Google Scholar 

  44. Piovesan, G. et al. Radiocarbon dating of Aspromonte sessile oaks reveals the oldest dated temperate flowering tree in the world. Ecology 101, e03179 (2020).

    Article  PubMed  Google Scholar 

  45. Körner, C. A matter of tree longevity. Science 355, 130–131 (2017).

    Article  PubMed  Google Scholar 

  46. Poulter, B. et al. The global forest age dataset and its uncertainties (GFADv1.1). PANGAEA (2019).

  47. Di Filippo, A., Biondi, F., Piovesan, G. & Ziaco, E. Tree ring-based metrics for assessing old-growth forest naturalness. J. Appl. Ecol. 54, 737–749 (2017).

    Article  Google Scholar 

  48. Caetano-Andrade, V. L. et al. Tropical trees as time capsules of anthropogenic activity. Trends Plant Sci. 25, 369–380 (2020).

    Article  CAS  PubMed  Google Scholar 

  49. Roskilly, B., Keeling, E., Hood, S., Giuggiola, A. & Sala, A. Conflicting functional effects of xylem pit structure relate to the growth–longevity trade-off in a conifer species. Proc. Natl Acad. Sci. USA 116, 15282–15287 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Kingman, J. F. C. The coalescent. Stoch. Process. Appl. 13, 235–248 (1982).

    Article  Google Scholar 

  51. Joly, S., McLenachan, P. A. & Lockhart, P. J. A statistical approach for distinguishing hybridization and incomplete lineage sorting. Am. Nat. 174, E54–E70 (2009).

    Article  PubMed  Google Scholar 

  52. Leaché, A. D., Harris, R. B., Rannala, B. & Yang, Z. The influence of gene flow on species tree estimation: a simulation study. Syst. Biol. 63, 17–30 (2014).

    Article  PubMed  Google Scholar 

  53. Yu, Y., Dong, J., Liu, K. J. & Nakhleh, L. Maximum likelihood inference of reticulate evolutionary histories. Proc. Natl Acad. Sci. USA 111, 16448–16453 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Zhou, Y. et al. Importance of incomplete lineage sorting and introgression in the origin of shared genetic variation between two closely related pines with overlapping distributions. Heredity 118, 211–220 (2017).

    Article  CAS  PubMed  Google Scholar 

  55. Petit, R. J. & Hampe, A. Some evolutionary consequences of being a tree. Annu. Rev. Ecol. Evol. Syst. 37, 187–214 (2006).

    Article  Google Scholar 

  56. Tejo, C. F. & Fontúrbel, F. E. A vertical forest within the forest: millenary trees from the Valdivian rainforest as biodiversity hubs. Ecology 100, e02584 (2019).

    Article  PubMed  Google Scholar 

  57. Stephenson, N. L. et al. Rate of tree carbon accumulation increases continuously with tree size. Nature 507, 90–93 (2014).

    Article  CAS  PubMed  Google Scholar 

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C.H.C. thanks J. R. Harting for discussions about model development during the very early stages of this project. Research in S.M.-B. laboratory is supported by the PID2019-110335GB-I00 /AEI grant from the Spanish Government and through an ICREA Academia award and 2017 SGR 980 grant from the Catalan Government. G.P.’s research on sessile oak and beech longevity was funded respectively by Aspromonte and Pollino National Parks.

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C.H.C. and S.M.-B. conceived the idea. C.H.C. conceived of and wrote the simulation models, performed the analysis and wrote the manuscript. G.P. and S.M.-B. helped improve the analysis and wrote the manuscript.

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Correspondence to Charles H. Cannon.

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Nature Plants thanks Josep Penuelas and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Figs. 1–3.

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Cannon, C.H., Piovesan, G. & Munné-Bosch, S. Old and ancient trees are life history lottery winners and vital evolutionary resources for long-term adaptive capacity. Nat. Plants 8, 136–145 (2022).

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