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.
Access optionsAccess options
Subscribe to Journal
Get full journal access for 1 year
only $15.58 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
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/.
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).
Erb, K.-H. et al. Unexpectedly large impact of forest management and grazing on global vegetation biomass. Nature 553, 73–76 (2018).
Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).
Le Quéré, C. et al. Global carbon budget 2017. Earth Syst. Sci. Data 10, 405–448 (2018).
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).
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).
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).
Carvalhais, N. et al. Global covariation of carbon turnover times with climate in terrestrial ecosystems. Nature 514, 213–217 (2014).
Erb, K.-H. et al. Biomass turnover time in terrestrial ecosystems halved by land use. Nat. Geosci. 9, 674–678 (2016).
Waring, R. H. Characteristics of trees predisposed to die. BioScience 37, 569–574 (1987).
McDowell, N. G. et al. The interdependence of mechanisms underlying climate-driven vegetation mortality. Trends Ecol. Evol. 26, 523–532 (2011).
Pickett, S. T. A. & White, P. S. The Ecology of Natural Disturbances and Patch Dynamics. (Academic, 1985).
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).
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).
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).
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).
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).
Cole, L. E. S., Bhagwat, S. A. & Willis, K. J. Recovery and resilience of tropical forests after disturbance. Nat. Commun. 5, 3906 (2014).
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).
Seidl, R. et al. Forest disturbances under climate change. Nat. Clim. Change 7, 395–402 (2017).
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).
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
Poulter, B. et al. The Global Forest Age Dataset and its Uncertainties (GFADv1.1) (PANGAEA, 2019); https://doi.org/10.1594/PANGAEA.897392
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).
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).
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).
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).
Avitabile, V. et al. An integrated pan-tropical biomass map using multiple reference datasets. Glob. Change Biol. 22, 1406–1420 (2016).
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).
Avitabile, V. et al. in GV2M: Global Vegetation Monitoring and Modeling (INRA, 2014).
Thurner, M. et al. Carbon stock and density of northern boreal and temperate forests. Glob. Ecol. Biogeogr. 23, 297–310 (2014).
Espírito-Santo, F. D. B. et al. Storm intensity and old-growth forest disturbances in the Amazon region. Geophys. Res. Lett. 37, L11403 (2010).
van der Werf, G. R. et al. Global fire emissions estimates during 1997–2016. Earth Syst. Sci. Data 9, 697–720 (2017).
Poorter, L. et al. Biomass resilience of neotropical secondary forests. Nature 530, 211–214 (2016).
Scheffer, M., Carpenter, S., Foley, J. A., Folke, C. & Walker, B. Catastrophic shifts in ecosystems. Nature 413, 591–596 (2001).
Johnstone, J. F. et al. Changing disturbance regimes, ecological memory, and forest resilience. Front. Ecol. Environ. 14, 369–378 (2016).
Marra, D. M. et al. Large-scale wind disturbances promote tree diversity in a Central Amazon forest. PLoS ONE 9, e103711 (2014).
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).
Marra, D. M. et al. Windthrows control biomass patterns and functional composition of Amazon forests. Glob. Change Biol. 24, 5867–5881 (2018).
McDowell, N. G. et al. Global satellite monitoring of climate-induced vegetation disturbances. Trends Plant Sci. 20, 114–123 (2015).
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).
Fisher, R. A. et al. Vegetation demographics in Earth system models: a review of progress and priorities. Glob. Change Biol. 24, 35–54 (2018).
Marvin, D. C. & Asner, G. P. Branchfall dominates annual carbon flux across lowland Amazonian forests. Environ. Res. Lett. 11, 094027 (2016).
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).
Dolan, K. A. et al. Disturbance distance: quantifying forests’ vulnerability to disturbance under current and future conditions. Environ. Res. Lett. 12, 114015 (2017).
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
Kalamandeen, M. et al. Pervasive rise of small-scale deforestation in Amazonia. Sci. Rep. 8, 1600 (2018).
de Groot, W. J. et al. A comparison of Canadian and Russian boreal forest fire regimes. Ecol. Manag. 294, 23–34 (2013).
Pugh, T. A. M. et al. Role of forest regrowth in global carbon sink dynamics. Proc. Natl Acad. Sci. USA 116, 4382–4387 (2019).
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).
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).
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).
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).
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).
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).
Le Quéré, C. et al. Global carbon budget 2016. Earth Syst. Sci. Data 8, 605–649 (2016).
van Mantgem, P. J. et al. Widespread increase of tree mortality rates in the western United States. Science 323, 521–524 (2009).
Zhao, M. & Running, S. W. Drought-Induced reduction in global terrestrial net primary production from 2000 through 2009. Science 329, 940–944 (2010).
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.
The authors declare no competing interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary description, Supplementary Figs. 1–13 and Supplementary Tables 1 and 2.