Letter | Published:

Global patterns of tropical forest fragmentation

Nature volume 554, pages 519522 (22 February 2018) | Download Citation

Abstract

Remote sensing enables the quantification of tropical deforestation with high spatial resolution1,2. This in-depth mapping has led to substantial advances in the analysis of continent-wide fragmentation of tropical forests1,2,3,4. Here we identified approximately 130 million forest fragments in three continents that show surprisingly similar power-law size and perimeter distributions as well as fractal dimensions. Power-law distributions5,6,7 have been observed in many natural phenomena8,9 such as wildfires, landslides and earthquakes. The principles of percolation theory7,10,11 provide one explanation for the observed patterns, and suggest that forest fragmentation is close to the critical point of percolation; simulation modelling also supports this hypothesis. The observed patterns emerge not only from random deforestation, which can be described by percolation theory10,11, but also from a wide range of deforestation and forest-recovery regimes. Our models predict that additional forest loss will result in a large increase in the total number of forest fragments—at maximum by a factor of 33 over 50 years—as well as a decrease in their size, and that these consequences could be partly mitigated by reforestation and forest protection.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from $8.99

All prices are NET prices.

References

  1. 1.

    et al. Determination of tropical deforestation rates and related carbon losses from 1990 to 2010. Glob. Change Biol. 20, 2540–2554 (2014)

  2. 2.

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

  3. 3.

    et al. Habitat fragmentation and its lasting impact on Earth’s ecosystems. Sci. Adv. 1, e1500052 (2015)

  4. 4.

    et al. Degradation in carbon stocks near tropical forest edges. Nat. Commun. 6, 10158 (2015)

  5. 5.

    , & Scaling Biodiversity (Cambridge Univ. Press, 2007)

  6. 6.

    et al. Scaling and power-laws in ecological systems. J. Exp. Biol. 208, 1749–1769 (2005)

  7. 7.

    Critical Phenomena in Natural Sciences. Chaos, Fractals, Selforganization and Disorder: Concepts and Tools (Springer, 2006)

  8. 8.

    & Landslides, forest fires, and earthquakes: examples of self-organized critical behavior. Physica A 340, 580–589 (2004)

  9. 9.

    How Nature Works. The Science of Self-Organized Criticality (Copernicus, 1996)

  10. 10.

    & Introduction to Percolation Theory (Taylor & Francis, 1994)

  11. 11.

    & Complexity and Criticality Vol. 1 (Imperial College Press, 2005)

  12. 12.

    et al. Global carbon budget 2014. Earth Syst. Sci. Data 7, 47–85 (2015)

  13. 13.

    Tropical forests in a changing environment. Trends Ecol. Evol. 20, 553–560 (2005)

  14. 14.

    , & Increasing human dominance of tropical forests. Science 349, 827–832 (2015)

  15. 15.

    The worldwide extent of land-use change. Bioscience 44, 305–313 (1994)

  16. 16.

    et al. The fate of Amazonian forest fragments: a 32-year investigation. Biol. Conserv. 144, 56–67 (2011)

  17. 17.

    Recent advances in percolation theory and its applications. Phys. Rep. 578, 1–32 (2015)

  18. 18.

    et al. Detection of critical densities associated with piñon-juniper woodland ecotones. Ecology 77, 805–821 (1996)

  19. 19.

    & Self-organized critical forest-fire model. Phys. Rev. Lett. 69, 1629–1632 (1992)

  20. 20.

    Test of scaling exponents for percolation-cluster perimeters. Phys. Rev. Lett. 56, 545–548 (1986)

  21. 21.

    & Self-Organization in Complex Ecosystems Vol. 42 (Princeton Univ. Press, 2006)

  22. 22.

    , & Landscape Ecology in Theory and Practice (Springer, 2001)

  23. 23.

    , , & Neutral models for the analysis of broadscale landscape pattern. Landsc. Ecol. 1, 19–28 (1987)

  24. 24.

    & Habitat fragmentation and extinction thresholds in spatially explicit models. J. Anim. Ecol. 65, 465–473 (1996)

  25. 25.

    & Global forest transition: prospects for an end to deforestation. Annu. Rev. Environ. Resour. 36, 343–371 (2011)

  26. 26.

    et al. Forest transitions: towards a global understanding of land use change. Glob. Environ. Change 15, 23–31 (2005)

  27. 27.

    & A survey and overview of habitat fragmentation experiments. Conserv. Biol. 14, 342–355 (2000)

  28. 28.

    Effects of habitat fragmentation on birds and mammals in landscapes with different proportions of suitable habitat: a review. Oikos 71, 355–366 (1994)

  29. 29.

    et al. High resolution analysis of tropical forest fragmentation and its impact on the global carbon cycle. Nat. Commun. 8, 14855 (2017)

  30. 30.

    et al. Approaching a state shift in Earth’s biosphere. Nature 486, 52–58 (2012)

  31. 31.

    R Core Team. R: A Language and Environment for Statistical Computing ; (R Foundation for Statistical Computing, 2015)

  32. 32.

    rworldmap: A new R package for mapping global data. R J. 3, 35–43 (2011)

  33. 33.

    , , & Three centuries of dual pressure from land use and climate change on the biosphere. Environ. Res. Lett. 10, 044011 (2015)

  34. 34.

    CDO 2015: Climate Data Operators. The Max Planck Institute for Meteorology, (2017)

  35. 35.

    & Power-law distributions in binned empirical data. Ann. Appl. Stat. 8, 89–119 (2014)

  36. 36.

    & Applications of fractals in ecology. Trends Ecol. Evol. 5, 79–86 (1990)

  37. 37.

    & On calculation of fractal dimension of images. Pattern Recognit. Lett. 22, 631–637 (2001)

Download references

Acknowledgements

The project has been supported by the Helmholtz Alliance Remote Sensing and Earth System Dynamics. A.H. and T.W. were supported by the European Research Council Advanced Grant 233066. We thank A. Hein and A. Bogdanowski for assistance, A. Hartmann for discussion, M. Dantas de Paula for data handling, and S. Paulick and F. Bohn for technical support.

Author information

Affiliations

  1. Helmholtz Centre for Environmental Research – UFZ, Department of Ecological Modelling, Permoserstrasse 15, 04318 Leipzig, Germany

    • Franziska Taubert
    • , Rico Fischer
    • , Jürgen Groeneveld
    • , Sebastian Lehmann
    • , Michael S. Müller
    • , Edna Rödig
    • , Thorsten Wiegand
    •  & Andreas Huth
  2. TU Dresden, Institute of Forest Growth and Forest Computer Sciences, PO 1117, 01735 Tharandt, Germany

    • Jürgen Groeneveld
  3. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany

    • Thorsten Wiegand
    •  & Andreas Huth
  4. University of Osnabrück, Institute of Environmental Systems Research, Barbarastrasse 12, 49076 Osnabrück, Germany

    • Andreas Huth

Authors

  1. Search for Franziska Taubert in:

  2. Search for Rico Fischer in:

  3. Search for Jürgen Groeneveld in:

  4. Search for Sebastian Lehmann in:

  5. Search for Michael S. Müller in:

  6. Search for Edna Rödig in:

  7. Search for Thorsten Wiegand in:

  8. Search for Andreas Huth in:

Contributions

A.H., F.T. and R.F. conceived the project. A.H., F.T. and T.W. supervised the research. S.L. and E.R. processed and analysed vegetation maps. F.T. performed statistical analysis of map observations. F.T. and M.S.M. implemented the simulation models and conducted the simulations. F.T. analysed the results and prepared figures, tables and videos. A.H., F.T., R.F., T.W. and J.G. wrote the manuscript. All authors have participated in discussion and editing of the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Franziska Taubert.

Reviewer Information Nature thanks B. Barzel, B. DeVries, R. Ewers and P. Marquet for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information

PDF files

  1. 1.

    Life Sciences Reporting Summary

Videos

  1. 1.

    Video on the dynamics of forest fragmentation in America using FRAG.

    Fragment size distributions (green bars: FRAG, line: observation from remote sensing) and the spatial patterns of fragments on a map of a selected sub-area of 900 ha is shown (FRAG, cleared sites are white and colours indicate fragment size, see Methods for details). For graphical purposes only, fragments < 10 ha are also shown.

  2. 2.

    Video on the dynamics of forest fragmentation in America using FRAG-B.

    Fragment size distributions (green bars: FRAG-B with dborder = 0.995, line: observation from remote sensing) and the spatial patterns of fragments on a map of a selected sub-area of 900 ha is shown (FRAG-B, cleared sites are white and colours indicate fragment size, see Methods for details). For graphical purposes only, fragments < 10 ha are also shown.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature25508

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.