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Important role of forest disturbances in the global biomass turnover and carbon sinks

Nature Geoscience volume 12, pages 730–735 (2019)Cite this article

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Abstract

Forest disturbances that lead to the replacement of whole tree stands are a cornerstone of forest dynamics, with drivers that include fire, windthrow, biotic outbreaks and harvest. The frequency of disturbances may change over the next century with impacts on the age, composition and biomass of forests. However, the disturbance return time, that is, the mean interval between disturbance events, remains poorly characterized across the world’s forested biomes, which hinders the quantification of the role of disturbances in the global carbon cycle. Here we present the global distribution of stand-replacing disturbance return times inferred from satellite-based observations of forest loss. Prescribing this distribution within a vegetation model with a detailed representation of stand structure, we quantify the importance of stand-replacing disturbances for biomass carbon turnover globally over 2001–2014. The return time varied from less than 50 years in heavily managed temperate ecosystems to over 1,000 years in tropical evergreen forests. Stand-replacing disturbances accounted for 12.3% (95% confidence interval, 11.4–13.7%) of the annual biomass carbon turnover due to tree mortality globally, and in 44% of the forested area, biomass stocks are strongly sensitive to changes in the disturbance return time. Relatively small shifts in disturbance regimes in these areas would substantially influence the forest carbon sink that currently limits climate change by offsetting emissions.

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Fig. 1: Forest-disturbance rotation periods.
Fig. 2: Carbon turnover fluxes from closed-canopy forests for 2001–2014.
Fig. 3: Sensitivity of biomass to changes in τ.

Data availability

Calculations of τO, data from the model simulations and the forest mask used are available from https://dataguru.lu.se/app#PughDisturbance2019 (https://doi.org/10.18161/disturbance_tauo.201905, https://doi.org/10.18161/disturbance_lpj-guess.201905 and https://doi.org/10.18161/disturbance_forestmask.201905). GFAD v1.1 was obtained from PANGAEA (https://doi.org/10.1594/PANGAEA.897392), and the Global Forest Change 2000–2014 v1.2 forest loss product from https://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.2.html. The ESA CCI Landcover v2.0.7 was obtained from http://maps.elie.ucl.ac.be/CCI/viewer/.

Code availability

The Matlab code for the data analysis herein is available from GitHub, https://github.com/pughtam/GlobalDist. The source code for LPJ-GUESS v4.0 can be obtained on request through Lund University (web.nateko.lu.se/lpj-guess).

References

  1. Erb, K.-H. et al. Unexpectedly large impact of forest management and grazing on global vegetation biomass. Nature 553, 73–76 (2018).

    Article  Google Scholar 

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

    Article  Google Scholar 

  3. Le Quéré, C. et al. Global carbon budget 2017. Earth Syst. Sci. Data 10, 405–448 (2018).

    Article  Google Scholar 

  4. Sierra, C. A., Müller, M., Metzler, H., Manzoni, S. & Trumbore, S. E. The muddle of ages, turnover, transit, and residence times in the carbon cycle. Glob. Change Biol. 23, 1763–1773 (2017).

    Article  Google Scholar 

  5. Friend, A. D. et al. Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2. Proc Natl Acad. Sci. USA 111, 3280–3285 (2014).

    Article  Google Scholar 

  6. Ahlström, A., Xia, J., Arneth, A., Luo, Y. & Smith, B. Importance of vegetation dynamics for future terrestrial carbon cycling. Environ. Res. Lett. 10, 054019 (2015).

    Article  Google Scholar 

  7. Carvalhais, N. et al. Global covariation of carbon turnover times with climate in terrestrial ecosystems. Nature 514, 213–217 (2014).

    Article  Google Scholar 

  8. Erb, K.-H. et al. Biomass turnover time in terrestrial ecosystems halved by land use. Nat. Geosci. 9, 674–678 (2016).

    Article  Google Scholar 

  9. Waring, R. H. Characteristics of trees predisposed to die. BioScience 37, 569–574 (1987).

    Article  Google Scholar 

  10. McDowell, N. G. et al. The interdependence of mechanisms underlying climate-driven vegetation mortality. Trends Ecol. Evol. 26, 523–532 (2011).

    Article  Google Scholar 

  11. Pickett, S. T. A. & White, P. S. The Ecology of Natural Disturbances and Patch Dynamics. (Academic, 1985).

  12. Frolking, S. et al. Forest disturbance and recovery: a general review in the context of spaceborne remote sensing of impacts on aboveground biomass and canopy structure. J. Geophys. Res. 114, G00E02 (2009).

    Article  Google Scholar 

  13. Kurz, W., Stinson, G., Rampley, G., Dymond, C. & Neilson, E. Risk of natural disturbances makes future contribution of Canada’s forests to the global carbon cycle highly uncertain. Proc. Natl Acad. Sci. USA 105, 1551–1555 (2008).

    Article  Google Scholar 

  14. Seidl, R., Schelhaas, M.-J., Rammer, W. & Verkerk, P. J. Increasing forest disturbances in Europe and their impact on carbon storage. Nat. Clim. Change 4, 806–810 (2014).

    Article  Google Scholar 

  15. Flannigan, M., Stocks, B., Turetsky, M. & Wotton, M. Impacts of climate change on fire activity and fire management in the circumboreal forest. Glob. Change Biol. 15, 549–560 (2009).

    Article  Google Scholar 

  16. Hurtt, G. C. et al. Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Clim. Change 109, 117–161 (2011).

    Article  Google Scholar 

  17. Cole, L. E. S., Bhagwat, S. A. & Willis, K. J. Recovery and resilience of tropical forests after disturbance. Nat. Commun. 5, 3906 (2014).

    Article  Google Scholar 

  18. Pregitzer, K. S. & Euskirchen, E. S. Carbon cycling and storage in world forests: biome patterns related to forest age. Glob. Change Biol. 10, 2052–2077 (2004).

    Article  Google Scholar 

  19. Seidl, R. et al. Forest disturbances under climate change. Nat. Clim. Change 7, 395–402 (2017).

    Article  Google Scholar 

  20. Reyer, C. P. O. et al. Are forest disturbances amplifying or canceling out climate change-induced productivity changes in European forests? Environ. Res. Lett. 12, 034027 (2017).

    Article  Google Scholar 

  21. Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

    Article  Google Scholar 

  22. Poulter, B. et al. The Global Forest Age Dataset and its Uncertainties (GFADv1.1) (PANGAEA, 2019); https://doi.org/10.1594/PANGAEA.897392

  23. Espírito-Santo, F. D. B. et al. Size and frequency of natural forest disturbances and the Amazon forest carbon balance. Nat. Commun. 5, 3434 (2014).

    Article  Google Scholar 

  24. Chambers, J. Q. et al. The steady-state mosaic of disturbance and succession across an old-growth Central Amazon forest landscape. Proc. Natl Acad. Sci. USA 110, 3949–3964 (2013).

    Article  Google Scholar 

  25. White, J. C., Wulder, M. A., Hermosilla, T., Coops, N. C. & Hobart, G. W. A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sens. Environ. 194, 303–321 (2017).

    Article  Google Scholar 

  26. Kautz, M., Meddens, A. J. H., Hall, R. J. & Arneth, A. Biotic disturbances in Northern Hemisphere forests—a synthesis of recent data, uncertainties and implications for forest monitoring and modelling. Glob. Ecol. Biogeogr. 26, 533–552 (2017).

    Article  Google Scholar 

  27. Avitabile, V. et al. An integrated pan-tropical biomass map using multiple reference datasets. Glob. Change Biol. 22, 1406–1420 (2016).

    Article  Google Scholar 

  28. Santoro, M. et al. Remote sensing of environment forest growing stock volume of the Northern Hemisphere: spatially explicit estimates for 2010 derived from Envisat ASAR. Remote Sens. Environ. 168, 316–334 (2015).

    Article  Google Scholar 

  29. Avitabile, V. et al. in GV2M: Global Vegetation Monitoring and Modeling (INRA, 2014).

  30. Thurner, M. et al. Carbon stock and density of northern boreal and temperate forests. Glob. Ecol. Biogeogr. 23, 297–310 (2014).

    Article  Google Scholar 

  31. Espírito-Santo, F. D. B. et al. Storm intensity and old-growth forest disturbances in the Amazon region. Geophys. Res. Lett. 37, L11403 (2010).

    Article  Google Scholar 

  32. van der Werf, G. R. et al. Global fire emissions estimates during 1997–2016. Earth Syst. Sci. Data 9, 697–720 (2017).

    Article  Google Scholar 

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

    Article  Google Scholar 

  34. Scheffer, M., Carpenter, S., Foley, J. A., Folke, C. & Walker, B. Catastrophic shifts in ecosystems. Nature 413, 591–596 (2001).

    Article  Google Scholar 

  35. Johnstone, J. F. et al. Changing disturbance regimes, ecological memory, and forest resilience. Front. Ecol. Environ. 14, 369–378 (2016).

    Article  Google Scholar 

  36. Marra, D. M. et al. Large-scale wind disturbances promote tree diversity in a Central Amazon forest. PLoS ONE 9, e103711 (2014).

    Article  Google Scholar 

  37. Marra, D. M. et al. Predicting biomass of hyperdiverse and structurally complex Central Amazonian forests—a virtual approach using extensive field data. Biogeosciences 13, 1553–1570 (2016).

    Article  Google Scholar 

  38. Marra, D. M. et al. Windthrows control biomass patterns and functional composition of Amazon forests. Glob. Change Biol. 24, 5867–5881 (2018).

    Article  Google Scholar 

  39. McDowell, N. G. et al. Global satellite monitoring of climate-induced vegetation disturbances. Trends Plant Sci. 20, 114–123 (2015).

    Article  Google Scholar 

  40. Renninger, H. J., Carlo, N., Clark, K. L. & Schäfer, K. V. R. Modeling respiration from snags and coarse woody debris before and after an invasive gypsy moth disturbance. J. Geophys. Res. Biogeosci. 119, 630–644 (2014).

    Article  Google Scholar 

  41. Fisher, R. A. et al. Vegetation demographics in Earth system models: a review of progress and priorities. Glob. Change Biol. 24, 35–54 (2018).

    Article  Google Scholar 

  42. Marvin, D. C. & Asner, G. P. Branchfall dominates annual carbon flux across lowland Amazonian forests. Environ. Res. Lett. 11, 094027 (2016).

    Article  Google Scholar 

  43. Allen, C. D., Breshears, D. D. & McDowell, N. G. On underestimation of global vulnerability to tree mortality and forest die-off from hotter drought in the Anthropocene. Ecosphere 6, 129 (2015).

    Article  Google Scholar 

  44. Dolan, K. A. et al. Disturbance distance: quantifying forests’ vulnerability to disturbance under current and future conditions. Environ. Res. Lett. 12, 114015 (2017).

    Article  Google Scholar 

  45. Land Cover CCI Product User Guide Version 2.0 (ESA, 2017); http://maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdf

  46. Kalamandeen, M. et al. Pervasive rise of small-scale deforestation in Amazonia. Sci. Rep. 8, 1600 (2018).

    Article  Google Scholar 

  47. de Groot, W. J. et al. A comparison of Canadian and Russian boreal forest fire regimes. Ecol. Manag. 294, 23–34 (2013).

    Article  Google Scholar 

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

    Article  Google Scholar 

  49. Marin-Spiotta, E., Cusack, D. F., Ostertag, R. & Silver, W. L. in Post-agricultural Succession in the Neotropics (ed. Myster, R. W.) 22–72 (Springer, 2008).

  50. 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 

  51. Smith, B. et al. Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model. Biogeosciences 11, 2027–2054 (2014).

    Article  Google Scholar 

  52. Herwitz, S., Slye, R., Erwitz, S. T. R. H. & Lye, R. O. E. S. Long-term survivorship and crown area dynamics of tropical rain forest canopy trees. Ecology 81, 585–597 (2000).

    Article  Google Scholar 

  53. Calvo-Alvarado, J. C., McDowell, N. G. & Waring, R. H. Allometric relationships predicting foliar biomass and leaf area:sapwood area ratio from tree height in five Costa Rican rain forest species. Tree Physiol. 28, 1601–1608 (2008).

    Article  Google Scholar 

  54. Thonicke, K., Venevsky, S., Sitch, S. & Cramer, W. The role of fire disturbance for global vegetation dynamics: coupling fire into a dynamic global vegetation model. Glob. Ecol. Biogeogr. 10, 661–677 (2001).

    Article  Google Scholar 

  55. Le Quéré, C. et al. Global carbon budget 2016. Earth Syst. Sci. Data 8, 605–649 (2016).

    Article  Google Scholar 

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

    Article  Google Scholar 

  57. Zhao, M. & Running, S. W. Drought-Induced reduction in global terrestrial net primary production from 2000 through 2009. Science 329, 940–944 (2010).

    Article  Google Scholar 

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Acknowledgements

T.A.M.P. acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 758873, TreeMort). T.A.M.P., A.A. and M.K. acknowledge support from EU FP7 grant LUC4C (grant no. 603542) and the Helmholtz Association in its ATMO programme and its impulse and networking fund. This is paper number 36 of the Birmingham Institute of Forest Research. B.S. acknowledges funding from the Swedish Research Council FORMAS, the Strategic Research Area BECC and the Lund University Centre for Studies of Carbon Cycle and Climate Interactions (LUCCI). B.P. was supported by the NASA Terrestrial Ecology program. S. Hantson, S. Archibald, J. Sadler, T. Matthews and S. Petrovskii are thanked for discussions that helped improve the manuscript, as are M. Wulder for providing the Canadian ecozones mask, E. Ferranti for help with file conversion and V. Lehsten for assistance with the data deposition.

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Authors and Affiliations

  1. School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK

    Thomas A. M. Pugh

  2. Birmingham Institute of Forest Research, University of Birmingham, Birmingham, UK

    Thomas A. M. Pugh

  3. Karlsruhe Institute of Technology, IMK-IFU, Garmisch-Partenkirchen, Germany

    Almut Arneth

  4. Department of Forest Health, Forest Research Institute Baden-Württemberg, Freiburg, Germany

    Markus Kautz

  5. Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA

    Benjamin Poulter

  6. Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden

    Benjamin Smith

  7. Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia

    Benjamin Smith

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Contributions

T.A.M.P. conceived and designed the study with contributions from A.A. and B.S. B.P. and M.K. contributed data. T.A.M.P. carried out the model simulations. T.A.M.P. led the analysis and wrote the paper with contributions from all the authors.

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Correspondence to Thomas A. M. Pugh.

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Supplementary description, Supplementary Figs. 1–13 and Supplementary Tables 1 and 2.

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Pugh, T.A.M., Arneth, A., Kautz, M. et al. Important role of forest disturbances in the global biomass turnover and carbon sinks. Nat. Geosci. 12, 730–735 (2019). https://doi.org/10.1038/s41561-019-0427-2

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