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Decadal changes in fire frequencies shift tree communities and functional traits

Abstract

Global change has resulted in chronic shifts in fire regimes. Variability in the sensitivity of tree communities to multi-decadal changes in fire regimes is critical to anticipating shifts in ecosystem structure and function, yet remains poorly understood. Here, we address the overall effects of fire on tree communities and the factors controlling their sensitivity in 29 sites that experienced multi-decadal alterations in fire frequencies in savanna and forest ecosystems across tropical and temperate regions. Fire had a strong overall effect on tree communities, with an average fire frequency (one fire every three years) reducing stem density by 48% and basal area by 53% after 50 years, relative to unburned plots. The largest changes occurred in savanna ecosystems and in sites with strong wet seasons or strong dry seasons, pointing to fire characteristics and species composition as important. Analyses of functional traits highlighted the impact of fire-driven changes in soil nutrients because frequent burning favoured trees with low biomass nitrogen and phosphorus content, and with more efficient nitrogen acquisition through ectomycorrhizal symbioses. Taken together, the response of trees to altered fire frequencies depends both on climatic and vegetation determinants of fire behaviour and tree growth, and the coupling between fire-driven nutrient losses and plant traits.

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Fig. 1: Tree stem density declines with both fire frequency and duration of fire regime.
Fig. 2: Tree basal area declines with both fire frequency and duration of fire regime.
Fig. 3: Climate and ecosystem type modify effects of fire frequencies on tree basal area.
Fig. 4: Functional composition of tree communities both responds to and modifies the effects of frequent burning.

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Data availability

Wood density data are from refs. 50,51,52, plant tissue stoichiometry and mycorrhizal type data are from ref. 38, and bark thickness data are from the Fire and Fuels Extension to the Forest Vegetation Simulator (https://www.fs.fed.us/fmsc/ftp/fvs/docs/gtr/FFEaddendum.pdf). Supplementary Data 1 and 2 contain the woody population size data and Supplementary Data 3 contains land use data. Refs. 53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76 describe the fire experiments.

References

  1. Andela, N. et al. A human-driven decline in global burned area. Science 356, 1356–1362 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Westerling, A. L., Hidalgo, H. G., Cayan, D. R. & Swetnam, T. W. Warming and earlier spring increase western US forest wildfire activity. Science 313, 940–943 (2006).

    Article  CAS  PubMed  Google Scholar 

  3. Turner, M. G. Disturbance and landscape dynamics in a changing world. Ecology 91, 2833–2849 (2010).

    Article  PubMed  Google Scholar 

  4. Higgins, S. I. & Scheiter, S. Atmospheric CO2 forces abrupt vegetation shifts locally, but not globally. Nature 488, 209–212 (2012).

    Article  CAS  PubMed  Google Scholar 

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

    Article  Google Scholar 

  6. Schoennagel, T. et al. Adapt to more wildfire in western North American forests as climate changes. Proc. Natl Acad. Sci. USA 114, 4582–4590 (2017).

    Article  CAS  PubMed  Google Scholar 

  7. Westerling, A. L., Turner, M. G., Smithwick, E. A. H., Romme, W. H. & Ryan, M. G. Continued warming could transform Greater Yellowstone fire regimes by mid-21st century. Proc. Natl Acad. Sci. USA 108, 13165–13170 (2011).

    Article  CAS  PubMed  Google Scholar 

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

    Article  Google Scholar 

  9. Lewis, T. Very frequent burning encourages tree growth in sub-tropical Australian eucalypt forest. Forest Ecol. Manag. 459, 117842 (2020).

    Article  Google Scholar 

  10. Peterson, D. W. & Reich, P. B. Prescribed fire in oak savanna: fire frequency effects on stand structure and dynamics. Ecol. Appl. 11, 914–927 (2001).

    Article  Google Scholar 

  11. Tilman, D. et al. Fire suppression and ecosystem carbon storage. Ecology 81, 2680–2685 (2000).

    Article  Google Scholar 

  12. Pellegrini, A. F. A., Hedin, L. O., Staver, A. C. & Govender, N. Fire alters ecosystem carbon and nutrients but not plant nutrient stoichiometry or composition in tropical savanna. Ecology 96, 1275–1285 (2015).

    Article  PubMed  Google Scholar 

  13. Russell-Smith, J., Whitehead, P. J., Cook, G. D. & Hoare, J. L. Response of eucalyptus-dominated savanna to frequent fires: lessons from Munmarlary, 1973–1996. Ecol. Monogr. 73, 349–375 (2003).

    Article  Google Scholar 

  14. Uhl, C. & Kauffman, J. B. Deforestation, fire susceptibility, and potential tree responses to fire in the eastern Amazon. Ecology 71, 437–449 (1990).

    Article  Google Scholar 

  15. Case, M. F., Wigley‐Coetsee, C., Nzima, N., Scogings, P. F. & Staver, A. C. Severe drought limits trees in a semi‐arid savanna. Ecology 100, e02842 (2019).

    Article  PubMed  Google Scholar 

  16. Keeley, J. E., Pausas, J. G., Rundel, P. W., Bond, W. J. & Bradstock, R. A. Fire as an evolutionary pressure shaping plant traits. Trends Plant Sci. 16, 406–411 (2011).

    Article  CAS  PubMed  Google Scholar 

  17. Schoennagel, T., Turner, M. G. & Romme, W. H. The influence of fire interval and serotiny on postfire lodgepole pine density in Yellowstone National Park. Ecology 84, 2967–2978 (2003).

    Article  Google Scholar 

  18. Higgins, S. I. et al. Which traits determine shifts in the abundance of tree species in a fire-prone savanna? J. Ecol. 100, 1400–1410 (2012).

    Article  Google Scholar 

  19. Lehmann, C. E. R. et al. Savanna vegetation–fire–climate relationships differ among continents. Science 343, 548–552 (2014).

    Article  CAS  PubMed  Google Scholar 

  20. Staver, A. C., Archibald, S. & Levin, S. A. The global extent and determinants of savanna and forest as alternative biome states. Science 334, 230–232 (2011).

    Article  CAS  PubMed  Google Scholar 

  21. Higgins, S. I., Bond, J. I. & Trollope, W. S. Fire, resprouting and variability: a recipe for grass–tree coexistence in savanna. J. Ecol. 88, 213–229 (2000).

    Article  Google Scholar 

  22. Pellegrini, A. F. A. et al. Fire frequency drives decadal changes in soil carbon and nitrogen and ecosystem productivity. Nature 553, 194–198 (2018).

    Article  CAS  PubMed  Google Scholar 

  23. Reich, P. B., Peterson, D. W., Wedin, D. A. & Wrage, K. Fire and vegetation effects on productivity and nitrogen cycling across a forest–grassland continuum. Ecology 82, 1703–1719 (2001).

    Google Scholar 

  24. Phillips, R., Brzostek, E. & Midgley, M. The mycorrhizal‐associated nutrient economy: a new framework for predicting carbon–nutrient couplings in temperate forests. New Phytol. 99, 41–51 (2013).

    Article  Google Scholar 

  25. Hobbie, S. E. Plant species effects on nutrient cycling: revisiting litter feedbacks. Trends Ecol. Evol. 30, 357–363 (2015).

    Article  PubMed  Google Scholar 

  26. Read, D. J. & Perez‐Moreno, J. Mycorrhizas and nutrient cycling in ecosystems – a journey towards relevance? New Phytol. 157, 475–492 (2003).

    Article  Google Scholar 

  27. Dixon, R. K. et al. Carbon pools and flux of global forest ecosystems. Science 263, 185–190 (1994).

    Article  CAS  PubMed  Google Scholar 

  28. Jackson, R. B. et al. Trading water for carbon with biological carbon sequestration. Science 310, 1944–1947 (2005).

    Article  CAS  PubMed  Google Scholar 

  29. Whitman, E., Parisien, M. A., Thompson, D. K. & Flannigan, M. D. Short-interval wildfire and drought overwhelm boreal forest resilience. Sci. Rep. 9, 18796 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Hart, S. J. et al. Examining forest resilience to changing fire frequency in a fire-prone region of boreal forest. Glob. Change Biol. 25, 869–884 (2019).

    Article  Google Scholar 

  31. Stephens, S. L. et al. Managing forests and fire in changing climates. Science 342, 41–42 (2013).

    Article  CAS  PubMed  Google Scholar 

  32. Steel, Z. L., Safford, H. D. & Viers, J. H. The fire frequency–severity relationship and the legacy of fire suppression in California forests. Ecosphere 6, 1–23 (2015).

    Article  Google Scholar 

  33. Scott, J. & Burgan, R. Standard Fire Behavior Fuel Models: A Comprehensive Set for Use with Rothermel’s Surface Fire Spread Model General Technical Report RMRS-GTR-153 (USDA, Forest Service and Rocky Mountain Research Station, 2005).

  34. Liu, Y. Y. et al. Recent reversal in loss of global terrestrial biomass. Nat. Clim. Change 5, 470–474 (2015).

    Article  Google Scholar 

  35. Brandt, M. et al. Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands. Nat. Ecol. Evol. 2, 827–835 (2018).

    Article  PubMed  Google Scholar 

  36. Butler, O. M., Elser, J. J., Lewis, T., Mackey, B. & Chen, C. The phosphorus-rich signature of fire in the soil–plant system: a global meta-analysis. Ecol. Lett. 21, 335–344 (2018).

    Article  PubMed  Google Scholar 

  37. Raison, R. J., Khanna, P. K. & Woods, P. V. Transfer of elements to the atmosphere during low-intensity prescribed fires in three Australian subalpine eucalypt forests. Can. J. Forest Res. 15, 657–664 (1985).

    Article  CAS  Google Scholar 

  38. Averill, C., Bhatnagar, J. M., Dietze, M. C., Pearse, W. D. & Kivlin, S. N. Global imprint of mycorrhizal fungi on whole-plant nutrient economics. Proc. Natl. Acad. Sci. USA https://doi.org/10.1073/pnas.1906655116 (2019).

  39. Shah, F. et al. Ectomycorrhizal fungi decompose soil organic matter using oxidative mechanisms adapted from saprotrophic ancestors. New Phytol. 209, 1705–1719 (2016).

    Article  CAS  PubMed  Google Scholar 

  40. Woinarski, J. C. Z., Risler, J. & Kean, L. Response of vegetation and vertebrate fauna to 23 years of fire exclusion in a tropical eucalyptus open forest, Northern Territory, Australia. Austral Ecol. 29, 156–176 (2004).

    Article  Google Scholar 

  41. Steidinger, B. S. et al. Climatic controls of decomposition drive the global biogeography of forest–tree symbioses. Nature 569, 404–408 (2019).

    Article  CAS  PubMed  Google Scholar 

  42. Pellegrini, A. F. A. et al. Repeated fire shifts carbon and nitrogen cycling by changing plant inputs and soil decomposition across ecosystems. Ecol. Monogr. 90, e01409 (2020).

    Article  Google Scholar 

  43. Newland, J. A. & DeLuca, T. H. Influence of fire on native nitrogen-fixing plants and soil nitrogen status in ponderosa pine - Douglas-fir forests in western Montana. Can. J. Forest Res. 30, 274–282 (2000).

    Article  Google Scholar 

  44. Johnson, D. W. & Curtis, P. S. Effects of forest management on soil C and N storage: meta analysis. Forest Ecol. Manag. 140, 227–238 (2001).

    Article  Google Scholar 

  45. Pellegrini, A. F. A. Nutrient limitation in tropical savannas across multiple scales and mechanisms. Ecology 97, 313–324 (2016).

    Article  PubMed  Google Scholar 

  46. Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).

    Article  Google Scholar 

  47. Harrison, X. A. et al. A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ 2018, e4794 (2018).

    Article  Google Scholar 

  48. Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article  Google Scholar 

  49. Jackson, J. F., Adams, D. C. & Jackson, U. B. Allometry of constitutive defense: a model and a comparative test with tree bark and fire regime. Am. Nat. 153, 614–632 (1999).

    Article  PubMed  Google Scholar 

  50. Chave, J. et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351–366 (2009).

    Article  PubMed  Google Scholar 

  51. Hoffmann, W. A., Marchin, R. M., Abit, P. & Lau, O. L. Hydraulic failure and tree dieback are associated with high wood density in a temperate forest under extreme drought. Glob. Change Biol. 17, 2731–2742 (2011).

    Article  Google Scholar 

  52. Harmon, M. E. Decomposition of standing dead trees in the southern Appalachian Mountains. Oecologia 52, 214–215 (1982).

    Article  PubMed  Google Scholar 

  53. Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).

    Article  Google Scholar 

  54. Gurevitch, J., Morrow, L. L., Wallace, A. & Walsh, J. S. A meta-analysis of competition in field experiments. Am. Nat. 140, 539–572 (1992).

    Article  Google Scholar 

  55. Zanne, A. E. et al. Three keys to the radiation of angiosperms into freezing environments. Nature 506, 89–92 (2014).

    Article  CAS  PubMed  Google Scholar 

  56. Pearse, W. D. et al. pez: phylogenetics for the environmental sciences. Bioinformatics 31, 2888–2890 (2015).

    Article  CAS  PubMed  Google Scholar 

  57. Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).

    Article  CAS  PubMed  Google Scholar 

  58. Brockway, D. G. & Lewis, C. E. Long-term effects of dormant-season prescribed fire on plant community diversity, structure and productivity in a longleaf pine wiregrass ecosystem. Forest Ecol. Manag. 96, 167–183 (1997).

    Article  Google Scholar 

  59. Lewis, T. & Debuse, V. J. Resilience of a eucalypt forest woody understorey to long-term (34–55 years) repeated burning in subtropical Australia. Int. J. Wildl. Fire 21, 980–991 (2012).

    Article  Google Scholar 

  60. Scudieri, C. A., Sieg, C. H., Haase, S. M., Thode, A. E. & Sackett, S. S. Understory vegetation response after 30 years of interval prescribed burning in two ponderosa pine sites in northern Arizona, USA. Forest Ecol. Manag. 260, 2134–2142 (2010).

    Article  Google Scholar 

  61. Lewis, T., Reif, M., Prendergast, E. & Tran, C. The effect of long-term repeated burning and fire exclusion on above- and below-ground blackbutt (Eucalyptus pilularis) forest vegetation assemblages. Austral Ecol. 37, 767–778 (2012).

    Article  Google Scholar 

  62. Stratton, R. Effects of Long-Term Late Winter Prescribed Fire on Forest Stand Dynamics, Small Mammal Populations, and Habitat Demographics in a Tennessee Oak Barrens. MSc thesis, Univ. Tennessee (2007).

  63. Wade, D. D. Long-Term Site Responses to Season and Interval of Underburns on the Georgia Piedmont (Forest Service Research Data Archive, 2016).

  64. Pellegrini, A. F. A., Hoffmann, W. A. & Franco, A. C. Carbon accumulation and nitrogen pool recovery during transitions from savanna to forest in central Brazil. Ecology 95, 342–352 (2014).

    Article  PubMed  Google Scholar 

  65. Nesmith, C. B., Caprio, A. C., Pfaff, A. H., McGinnis, T. W. & Keeley, J. E. A comparison of effects from prescribed fires and wildfires managed for resource objectives in Sequoia and Kings Canyon National Parks. Forest Ecol. Manag. 261, 1275–1282 (2011).

    Article  Google Scholar 

  66. Haywood, J. D., Harris, F. L., Grelen, H. E. & Pearson, H. A. Vegetative response to 37 years of seasonal burning on a Louisiana longleaf pine site. South. J. Appl. For. 25, 122–130 (2001).

    Article  Google Scholar 

  67. Higgins, S. I. et al. Effects of four decades of fire manipulation on woody vegetation structure in savanna. Ecology 88, 1119–1125 (2007).

    Article  PubMed  Google Scholar 

  68. Gignoux, J., Lahoreau, G., Julliard, R. & Barot, S. Establishment and early persistence of tree seedlings in an annually burned savanna. J. Ecol. 97, 484–495 (2009).

    Article  Google Scholar 

  69. Tizon, F. R., Pelaez, D. V. & Elia, O. R. The influence of controlled fires on a plant community in the south of the Caldenal and its relationship with a regional state and transition model. Int. J. Exp. Bot. 79, 141–146 (2010).

    Google Scholar 

  70. Neill, C., Patterson, W. A. & Crary, D. W. Responses of soil carbon, nitrogen and cations to the frequency and seasonality of prescribed burning in a Cape Cod oak–pine forest. Forest Ecol. Manag. 250, 234–243 (2007).

    Article  Google Scholar 

  71. Ryan, C. M., Williams, M. & Grace, J. Above‐ and belowground carbon stocks in a miombo woodland landscape of Mozambique. Biotropica 43, 423–432 (2011).

    Article  Google Scholar 

  72. Scharenbroch, B. C., Nix, B., Jacobs, K. A. & Bowles, M. L. Two decades of low-severity prescribed fire increases soil nutrient availability in a midwestern, USA oak (Quercus) forest. Geoderma 183184, 80–91 (2012).

    Article  Google Scholar 

  73. Burton, J. A., Hallgren, S. W., Fuhlendorf, S. D. & Leslie, D. M. Jr. Understory response to varying fire frequencies after 20 years of prescribed burning in an upland oak forest. Plant Ecol. 212, 1513–1525 (2011).

    Article  Google Scholar 

  74. Stewart, J. F., Will, R. E., Robertson, K. M. & Nelson, C. D. Frequent fire protects shortleaf pine (Pinus echinata) from introgression by loblolly pine (P. taeda). Conserv. Genet. 16, 491–495 (2015).

    Article  Google Scholar 

  75. Knapp, B. O., Stephan, K. & Hubbart, J. A. Structure and composition of an oak–hickory forest after over 60 years of repeated prescribed burning in Missouri, U.S.A. Forest Ecol. Manag. 344, 95–109 (2015).

    Article  Google Scholar 

  76. Olson, M. G. Tree regeneration in oak–pine stands with and without prescribed fire in the New Jersey Pine Barrens: management implications. North. J. Appl. For. 28, 47–49 (2011).

    Article  Google Scholar 

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Acknowledgements

A.F.A.P. was supported by a NOAA Climate and Global Change postdoctoral fellowship programme and the USDA National Institute of Food and Agriculture grant 2018‐67012‐28077. R.B.J. received support from the Gordon and Betty Moore Foundation. The experiments at the sites were organized and funded through the Cedar Creek Long Term Ecological Research programme (DEB 1234162, 0620652, 1831944 and DBI 2021898), the National Park Service and Sequoia Parks Conservancy, and South African National Parks. C.T. was supported by a Lawrence Fellow award supported by the LLNL-LDRD Program under Project No. 20-ERD-055.

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A.F.A.P. and R.B.J. conceived and designed the overall study. T.R., C.A. and C.T. helped with data acquisition and provided feedback on statistical analyses. D.G.B., A.C.S., W.C., C.C., J.D.H., S.H.E., W.A.H., J.K., T.L., W.K.M., S.T.O., W.A.P., K.G.P., P.B.R., C.R., M.A.S.S., B.C.S., T.S., G.R.S., K.S., C.S., M.G.T. and J.M.V. provided data and/or assisted with interpreting the field data from experiments. All authors contributed to the writing of the manuscript.

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Correspondence to Adam F. A. Pellegrini.

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Extended data

Extended Data Fig. 1 Distribution of sites.

a, Map displaying the distribution of sites (dots) with the surface fire sites filled with black and the crown fire sites filled with white. The coloration indicates the average fire frequency within a gridcell using 1. The sample size of plots is written adjacent to the continent. b, distribution of sites in climate space overlying Whittaker’s biome distribution 77. (1 = tundra, 2=boreal forest, 3=woodland/shrubland, 4=temperate grassland/desert, 5=temperate forest, 6=temperate rainforest, 7=subtropical desert, 8=tropical forest and savanna, 9=tropical rainforest). Dots colored according to broad vegetation type category. Plots span a mean annual temperate range from 5.2–27.3 °C and a mean annual precipitation range from 408–2378 mm yr−1. c, aerial picture of two different fire treatment plots from Cedar Creek, a temperate oak savanna, where different fire frequencies have created a stark biome boundary between forests in unburned plots and savannas in biennial burn plots.

Extended Data Fig. 2 Example of the experimental layout of a fire manipulation experiment.

Example of the experimental layout of a fire manipulation experiment taken from Cedar Creek (a temperate savanna in Minnesota, USA), where fires have been manipulated since 1964. Aerial imagery (taken in 2017) from the National Agriculture Imagery Program from the Farm Service Agency. Plots are outlined with a color corresponding to their fire frequencies expressed in terms of number of fires per year (for example 0.33 is one fire every 3 years).

Extended Data Fig. 3 Untransformed data on stem density and basal area.

Untransformed data on stem density (a-b) and basal area (c-d) as a function of the duration that plots have been exposed to burning in the experiment (0 = unburned plots). Each dot represents a site and the dashed lines connect treatments within sites. Columns represent two sets of fire frequency contrasts comparing unburned vs. the intermediate frequency in a and c, and unburned vs. the high frequency in b and d (levels defined based on treatments within sites). Dots and bars based on mean and standard error calculated across the replicate plots within a fire treatment in a site. Note y-axis is on a log10 scale.

Extended Data Fig. 4 Comparison between fire types.

Comparison between fire types (surface in a, F1,94.3 = 50.6, p < 0.001, n = 9 sites and n = 104 plots; and crown in b, F1,21 = 10.3, p = 0.004, n = 24 plots) in needleleaf forests with fire expressed in terms of return period (crown fire plots are all 12 years postfire, data subset to include short-interval burn plots). c, illustrates the mean response ratios ± standard error for the fire types with crown fires split into high (>2,400 m) and low (<2,400) elevation sites (Crown 1 and Crown 2, respectively; n = 25 plots for each elevation category). Analyses were robust to considering surface fires in only Western US needleleaf forests: F1,47.1 = 17.2, p = 0.001. Response ratios were split into long and short fire return interval plots (Crown 1 and 2, respectively), with the justification for definition of interval in 17.

Extended Data Fig. 5 Fire frequency effects across precipitation in the wet quarter bins.

Partial residual plot displaying the relationship between loge basal area and precipitation in the wettest quarter cross-sectioned based on fire frequency. This plot is based on the same mixed-effects model presented in Fig. 3 and Supplementary Table 4, just re-arranged to emphasize how precipitation-basal area relationship changes with more frequent burning. n = 25 sites and n = 309 plots.

Extended Data Fig. 6 Differences in fire effects across continents.

Partial residual plot between the length of time plots were exposed to frequent burning and the log basal area (a, n = 25 sites and n = 309 plots) and stem density (b, n = 25 sites and n = 303 plots) in the different continents (from the main mixed-effects model with site as a random intercept in Supplementary Tables 4-5).

Extended Data Fig. 7 Fire effects in sub-vegetation classifications.

Partial residual plot between the length of time plots were exposed to frequent burning and the log basal area in the different sub-vegetation types (from the main mixed-effects model, presented in Supplementary Table 4 but substituting the broad vegetation effect with the more detailed classification. We found no evidence that accounting for the finer-scale variability in ecosystem classification increased the accuracy of the model or changed our conclusions. n = 25 sites and n = 309 plots.

Extended Data Fig. 8 Responses of stem densities to fire across environmental covariates.

Partial residual plots of the mixed-effects model for stem densities illustrating how fire frequency effects changed according to wet-season precipitation, mean annual temperature, and ecosystem type. Panels structured by standard deviations around the median to visualize the spread (−1, 0,1), PWQ: precipitation in the wet quarter, MAT: mean annual temperature. All model fits are p < 0.05 and specific results can be found in Supplementary Table 5. The predictor variables are mean-centered and standard deviations are scaled to facilitate comparisons of variable influence. In needleleaf and broadleaf forests, stem densities actually increased with more frequent burning initially, but declined with increasing experiment duration, potentially because of increased light availability initially stimulating recruitment of small trees (Extended Data Fig. 6, Supplementary Table 5). Stem density in African sites changed little through time (Extended Data Fig. 6). The trends in density may reflect the ability of many of the tree species to re-sprout in between fire events78. n = 25 sites and n = 303 plots.

Extended Data Fig. 9 Effect of fire on phosphorus stoichiometry.

Partial residual plots of the phosphorus (P) stoichiometry of community weighted means as a function of years of repeated burning. Taken from mixed-effects models presented in Supplementary Table 7. The models include a vegetation type effect. Tissue P is rescaled by subtracting the mean and dividing by the standard deviation. n = 16 sites and n = 172 plots.

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Pellegrini, A.F.A., Refsland, T., Averill, C. et al. Decadal changes in fire frequencies shift tree communities and functional traits. Nat Ecol Evol 5, 504–512 (2021). https://doi.org/10.1038/s41559-021-01401-7

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