Mapping tree density at a global scale

Journal name:
Nature
Volume:
525,
Pages:
201–205
Date published:
DOI:
doi:10.1038/nature14967
Received
Accepted
Published online
Updated online
Updated online

Abstract

The global extent and distribution of forest trees is central to our understanding of the terrestrial biosphere. We provide the first spatially continuous map of forest tree density at a global scale. This map reveals that the global number of trees is approximately 3.04 trillion, an order of magnitude higher than the previous estimate. Of these trees, approximately 1.30 trillion exist in tropical and subtropical forests, with 0.74 trillion in boreal regions and 0.66 trillion in temperate regions. Biome-level trends in tree density demonstrate the importance of climate and topography in controlling local tree densities at finer scales, as well as the overwhelming effect of humans across most of the world. Based on our projected tree densities, we estimate that over 15 billion trees are cut down each year, and the global number of trees has fallen by approximately 46% since the start of human civilization.

At a glance

Figures

  1. Map of data points and raw biome-level forest density data.
    Figure 1: Map of data points and raw biome-level forest density data.

    a, Image highlighting the ecoregions (shapefiles provided by The Nature Conservancy (http://www.nature.org)) from which the 429,775 ground-sourced measurements of tree density were collected. Shading indicates the total number of plot measurements collected in each ecoregion. A global forest map was overlaid in green to highlight that collected data span the majority of forest ecosystems on a global scale. b, The median and interquartile range of tree density values collected in the forested areas of each biome.

  2. Heat plots showing the relationships between predicted and measured tree density data.
    Figure 2: Heat plots showing the relationships between predicted and measured tree density data.

    al, Predictions were generated using generalized linear models (n = 429,775). Diagonal lines indicate 1:1 lines (perfect correspondence) between predicted and observed points, scaled to the kilometre level. Colours indicate the proportion of data points from that biome that fall within each pixel. Biomes with a greater number of plot measurements have greater variability but higher confidence in the mean estimates, highlighting the trade-off between broad-scale precision and fine-scale accuracy. Axes are log-transformed to account for exceptionally high variability in tree density.

  3. Validation plots for biome-level predictions.
    Figure 3: Validation plots for biome-level predictions.

    a, Biome-level regression models predict the mean values of the omitted validation plot measurements in 12 biomes. Overall, the models underestimated mean tree density by ~3% (slope = 0.97) but this difference was not statistically significant (P = 0.51). Bars show ± one standard deviation for the predicted mean and the grey area represents the 95% confidence interval for the mean. The values plotted here represent mean densities for the plot measurements (that is, for forested ecosystems), rather than those predicted for each entire biome. b, The standard deviation of the predicted mean values as a function of sample size. As sample size increases, the variability of the predicted mean tree density reaches a threshold, beyond which an increase in sample size results in a minimal increase in precision. Standard deviations were calculated using a bootstrapping approach (see Methods), and smooth curves were modelled using standard linear regression with a log–log transformation.

  4. The global map of tree density at the 1-km2 pixel (30 arc-seconds) scale.
    Figure 4: The global map of tree density at the 1-km2 pixel (30 arc-seconds) scale.

    a, The scale refers to the number of trees in each pixel. b, c, We highlight the map predictions for two areas (South American Andes (b) and Sardinia (c)) and include the corresponding images for visual comparison. All maps and images were generated using ESRI basemap imagery. d, A scatterplot as validation for our broad-scale estimates of total tree number. This shows the relationship between our predicted tree estimates and reported totals for regions with previous broad-scale tree inventories (see Methods for details). The straight line and the dotted line are the predicted best fit line and the 1:1 line, respectively.

  5. Standardized coefficients for the variables included in final biome-level regression models.
    Figure 5: Standardized coefficients for the variables included in final biome-level regression models.

    Coefficients represent relative per cent change in tree density for one standard deviation increase in the variable. Red and blue circles indicate negative and positive effects on tree density, respectively. Circle size indicates the magnitude of effects. All layers are available at the global scale. Human development = per cent developed and managed land; LAI = leaf area index; EVI = enhanced vegetation index; EVI: ASM = angular second moment of EVI; EVI: contrast = contrast of EVI; and EVI: dissimilarity = dissimilarity of EVI (see Extended Data Table 1).

  6. Histogram of the collected measurements of forest tree density in each biome around the world (n = 429,775).
    Extended Data Fig. 1: Histogram of the collected measurements of forest tree density in each biome around the world (n = 429,775).

    The red line and the blue dotted lines indicate the mean and median for the collected data, respectively. Data in each biome fitted a negative binomial error structure.

  7. Histogram of the predicted forest tree density values for the locations that density measurements were collected in each biome around the world (n = 429,775).
    Extended Data Fig. 2: Histogram of the predicted forest tree density values for the locations that density measurements were collected in each biome around the world (n = 429,775).

    The red line and the blue dotted lines indicate the mean and median for the collected data, respectively. As our models were based on mean values, the majority of points fall on or close to the mean values in each biome.

  8. Histogram of the total predicted forest tree density values for each pixel within each biome around the world (n = 429,775).
    Extended Data Fig. 3: Histogram of the total predicted forest tree density values for each pixel within each biome around the world (n = 429,775).

    This illustrates the spread of pixels throughout each biome, and highlights that our map accounts for the sampling bias in tree density plots (for example, although we had no zero values in our desert plots, the vast majority of desert pixels contain no trees).

  9. Comparison between approaches to generate the global tree density map.
    Extended Data Fig. 4: Comparison between approaches to generate the global tree density map.

    The initial map was generated using 14 biome-level models (biomes delineated by The Nature Conservancy http://www.nature.org) to account for broad-scale variations in terrestrial vegetation types. With several thousand plot-level density measurements in most biomes, this approach provided highly accurate estimates at the global scale. However, to improve precision at the local scale, we also generated a map using ecoregion-scale models. Separate models were generated within each of 813 global ecoregions (also delineated by The Nature Conservancy to reflect smaller-scale vegetation types) using exactly the same statistical approach (see Methods). The same 429,775 data points were used to construct each map. Biome-level and ecoregion-level maps provide total tree estimates of 3.041 and 3.253 trillion trees, respectively.

Tables

  1. Estimates of the total tree number for each of the biomes that contain forested land, as delineated by The Nature Conservancy (http://www.nature.org)
    Extended Data Table 1: Estimates of the total tree number for each of the biomes that contain forested land, as delineated by The Nature Conservancy (http://www.nature.org)

Change history

Updated online 09 September 2015
Minor changes were made to the Author Contributions statements.
Updated online 13 April 2016
The link for the global tree density map was added to the Author Information section.

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Author information

Affiliations

  1. Yale School of Forestry and Environmental Studies, Yale University, New Haven, Connecticut 06511, USA

    • T. W. Crowther,
    • H. B. Glick,
    • K. R. Covey,
    • C. Bettigole,
    • D. S. Maynard,
    • J. R. Smith,
    • G. Hintler,
    • M. C. Duguid,
    • W. Jetz,
    • P. M. Umunay,
    • C. W. Rowe,
    • M. S. Ashton,
    • P. R. Crane &
    • M. A. Bradford
  2. Department of Environmental Sciences, University of Helsinki, Helsinki 00014, Finland

    • S. M. Thomas
  3. Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06511, USA

    • G. Amatulli,
    • M.-N. Tuanmu &
    • W. Jetz
  4. Department of Life Sciences, Silwood Park, Imperial College, London SL5 7PY, UK

    • W. Jetz
  5. Departamento de Ciencias Forestales, Universidad de La Frontera, Temuco 4811230, Chile

    • C. Salas
  6. RedCastle Resources, Salt Lake City, Utah 84103, USA

    • C. Stam
  7. Universidade Federal do Sul da Bahia, Ferradas, Itabuna 45613-204, Brazil

    • D. Piotto
  8. Forestry Department, Food and Agriculture Organization of the United Nations, Rome 00153, Italy

    • R. Tavani
  9. Operation Wallacea, Spilbsy, Lincolnshire PE23 4EX, UK

    • S. Green &
    • G. Bruce
  10. Durrell Institute of Conservation and Ecology (DICE), School of Anthropology and Conservation (SAC), University of Kent, Canterbury ME4 4AG, UK

    • S. Green
  11. Molecular Imaging Research Center MIRCen/CEA, CNRS URA 2210, 91401 Orsay Cedex, France

    • S. J. Williams
  12. Landcare Research, Lincoln 7640, New Zealand

    • S. K. Wiser
  13. WSL, Swiss Federal Institute for Forest, Snow and Landscape Research, 8903 Birmensdorf, Switzerland

    • M. O. Huber
  14. Environmental Science Group, Wageningen University & Research Centre, 6708 PB, The Netherlands

    • G. M. Hengeveld &
    • G.-J. Nabuurs
  15. Center for Forest Ecology and Productivity RAS, Moscow 117997, Russia

    • E. Tikhonova
  16. CEN Center for Earth System Research and Sustainability, Institute of Geography, University of Hamburg, Hamburg 20146, Germany

    • P. Borchardt
  17. Department of Botany and Zoology, Masaryk University, Brno 61137, Czech Republic

    • C.-F. Li
  18. South African National Biodiversity Institute, Kirstenbosch Research Centre, Claremont 7735, South Africa

    • L. W. Powrie
  19. Institute of Plant Sciences, Botanical Garden, and Oeschger Centre for Climate Change Research, University of Bern, 3013 Bern, Switzerland

    • M. Fischer
  20. Senckenberg Gesellschaft für Naturforschung, Biodiversity and Climate Research Centre (BIK-F), 60325 Frankfurt, Germany

    • M. Fischer
  21. Department of Plant Systematics, University of Bayreuth, 95447 Bayreuth, Germany

    • A. Hemp
  22. Albrecht von Haller Institute of Plant Sciences, Georg August University of Göttingen, 37073 Göttingen, Germany

    • J. Homeier
  23. Tropical Ecology Research Group, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK

    • P. Cho
  24. Universidade Regional de Blumenau, Departamento de Engenharia Florestal, Blumenau/Santa Catarina 89030-000, Brazil

    • A. C. Vibrans
  25. Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China

    • S. L. Piao

Contributions

The study was conceived by T.W.C and G.H. and designed by T.W.C., K.R.C. and M.A.B. Statistical analyses were conducted by H.B.G., S.M.T., J.R.S., C.B., D.S.M. and T.W.C. and mapping was conducted by H.B.G. and C.B. The manuscript was written by T.W.C. with input from M.A.B., P.C., D.S.M., H.B.G. and C.B., with comments provided by all other authors. Tree density measurements or geospatial data from all over the world were contributed by K.R.C., S.M.T., M.C.D., G.A., M.N.T., W.J., C.Sa., C.St., D.P., T.T., S.G., G.B., S.J.W., S.K.W., M.O.H., G.M.H., G.J.N., E.T., P.B., C.F.L., L.W.P.,M.F., A.H., J.H., P.C., A.C.V., P.M.U., S.L.P., C.W.R. and M.S.A.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

The global tree density map can be found at http://elischolar.library.yale.edu/yale_fes_data/1/.

Author details

Extended data figures and tables

Extended Data Figures

  1. Extended Data Figure 1: Histogram of the collected measurements of forest tree density in each biome around the world (n = 429,775). (264 KB)

    The red line and the blue dotted lines indicate the mean and median for the collected data, respectively. Data in each biome fitted a negative binomial error structure.

  2. Extended Data Figure 2: Histogram of the predicted forest tree density values for the locations that density measurements were collected in each biome around the world (n = 429,775). (257 KB)

    The red line and the blue dotted lines indicate the mean and median for the collected data, respectively. As our models were based on mean values, the majority of points fall on or close to the mean values in each biome.

  3. Extended Data Figure 3: Histogram of the total predicted forest tree density values for each pixel within each biome around the world (n = 429,775). (184 KB)

    This illustrates the spread of pixels throughout each biome, and highlights that our map accounts for the sampling bias in tree density plots (for example, although we had no zero values in our desert plots, the vast majority of desert pixels contain no trees).

  4. Extended Data Figure 4: Comparison between approaches to generate the global tree density map. (646 KB)

    The initial map was generated using 14 biome-level models (biomes delineated by The Nature Conservancy http://www.nature.org) to account for broad-scale variations in terrestrial vegetation types. With several thousand plot-level density measurements in most biomes, this approach provided highly accurate estimates at the global scale. However, to improve precision at the local scale, we also generated a map using ecoregion-scale models. Separate models were generated within each of 813 global ecoregions (also delineated by The Nature Conservancy to reflect smaller-scale vegetation types) using exactly the same statistical approach (see Methods). The same 429,775 data points were used to construct each map. Biome-level and ecoregion-level maps provide total tree estimates of 3.041 and 3.253 trillion trees, respectively.

Extended Data Tables

  1. Extended Data Table 1: Estimates of the total tree number for each of the biomes that contain forested land, as delineated by The Nature Conservancy (http://www.nature.org) (362 KB)

Supplementary information

Excel files

  1. Supplementary Table 1 (15 KB)

    Summary Table showing the number of plot estimates and total tree numbers (with 95% confidence interval) at the biome and global scale.

  2. Supplementary Table 2 (53 KB)

    This table shows the number of trees and tree densities for countries of the world, as estimated using 2 independent approaches (biome and ecoregion-level models) and the database of Global Administrative Areas, version 2.7 (http://gadm.org/).

Additional data