Mapping tree density at a global scale (original) (raw)

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Acknowledgements

We thank P. Peterkins for her support throughout the study. We also thank Plant for the Planet for initial discussions and for collaboration during the study. The main project was funded by grants to T.W.C. from the Yale Climate and Energy Institute and the British Ecological Society. We acknowledge various sources for tree density measurements and estimates: the Canadian National Forest Inventory (https://nfi.nfis.org/index.php), the US Department of Agriculture Forest Service for their National Forest Inventory and Analysis (http://fia.fs.fed.us/), the Taiwan Forestry Bureau (which provided the National Vegetation Database of Taiwan), the DFG (German Research Foundation), BMBF (Federal Ministry of Education and Science of Germany), the Floristic and Forest Inventory of Santa Catarina (IFFSC), the National Vegetation Database of South Africa, and the Chilean research grants FONDECYT no. 1151495. For Europe NFI plot data were brought together with input from J. Rondeux and M. Waterinckx, Belgium, T. Bélouard, France, H. Polley, Germany, W. Daamen and H. Schoonderwoerd, Netherlands, S. Tomter, Norway, J. Villanueva and A. Trasobares, Spain, G. Kempe, Sweden. New Zealand Natural Forest plot data were collected by the LUCAS programme for the Ministry for the Environment (New Zealand) and sourced from the National Vegetation Survey Databank (New Zealand) (http://nvs.landcareresearch.co.nz). We also acknowledge the BCI forest dynamics research project, which was funded by National Science Foundation grants to S. P. Hubbell, support from the Center for Tropical Forest Science, the Smithsonian Tropical Research Institute, the John D. and Catherine T. MacArthur Foundation, the Mellon Foundation, the Small World Institute Fund, numerous private individuals, the Ucross High Plains Stewardship Initiative, and the hard work of hundreds of people from 51 countries over the past two decades. The plot project is part of the Center for Tropical Forest Science, a global network of large-scale demographic tree plots.

Author information

Authors and Affiliations

  1. Yale School of Forestry and Environmental Studies, Yale University, New Haven, 06511, Connecticut, 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, 06511, Connecticut, 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, 84103, Utah, USA
    C. Stam
  7. Universidade Federal do Sul da Bahia, Ferradas, 45613-204, Itabuna, Brazil
    D. Piotto
  8. Forestry Department, Food and Agriculture Organization of the United Nations, Rome, 00153, Italy
    R. Tavani
  9. Operation Wallacea, Spilbsy, PE23 4EX, Lincolnshire, 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, Orsay Cedex, 91401, 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, Birmensdorf, 8903, Switzerland
    M. O. Huber
  14. Environmental Science Group, Wageningen University & Research Centre, PB, 6708, 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, Bern, 3013, Switzerland
    M. Fischer
  20. Senckenberg Gesellschaft für Naturforschung, Biodiversity and Climate Research Centre (BIK-F), Frankfurt, 60325, Germany
    M. Fischer
  21. Department of Plant Systematics, University of Bayreuth, Bayreuth, 95447, Germany
    A. Hemp
  22. Albrecht von Haller Institute of Plant Sciences, Georg August University of Göttingen, Göttingen, 37073, Germany
    J. Homeier
  23. Tropical Ecology Research Group, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK
    P. Cho
  24. Departamento de Engenharia Florestal, Universidade Regional de Blumenau, 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

Authors

  1. T. W. Crowther
  2. H. B. Glick
  3. K. R. Covey
  4. C. Bettigole
  5. D. S. Maynard
  6. S. M. Thomas
  7. J. R. Smith
  8. G. Hintler
  9. M. C. Duguid
  10. G. Amatulli
  11. M.-N. Tuanmu
  12. W. Jetz
  13. C. Salas
  14. C. Stam
  15. D. Piotto
  16. R. Tavani
  17. S. Green
  18. G. Bruce
  19. S. J. Williams
  20. S. K. Wiser
  21. M. O. Huber
  22. G. M. Hengeveld
  23. G.-J. Nabuurs
  24. E. Tikhonova
  25. P. Borchardt
  26. C.-F. Li
  27. L. W. Powrie
  28. M. Fischer
  29. A. Hemp
  30. J. Homeier
  31. P. Cho
  32. A. C. Vibrans
  33. P. M. Umunay
  34. S. L. Piao
  35. C. W. Rowe
  36. M. S. Ashton
  37. P. R. Crane
  38. M. A. Bradford

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.

Corresponding author

Correspondence toT. W. Crowther.

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Competing interests

The authors declare no competing financial interests.

Additional information

Extended data figures and tables

Extended Data Figure 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.

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).

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.

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).

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).

Extended Data Figure 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.

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)

Full size table

Supplementary information

Supplementary Table 1 (download XLSX )

Summary Table showing the number of plot estimates and total tree numbers (with 95% confidence interval) at the biome and global scale. (XLSX 15 kb)

Supplementary Table 2 (download XLSX )

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/). (XLSX 53 kb)

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Crowther, T., Glick, H., Covey, K. et al. Mapping tree density at a global scale.Nature 525, 201–205 (2015). https://doi.org/10.1038/nature14967

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