Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Determinants of woody cover in African savannas


Savannas are globally important ecosystems of great significance to human economies. In these biomes, which are characterized by the co-dominance of trees and grasses, woody cover is a chief determinant of ecosystem properties1,2,3. The availability of resources (water, nutrients) and disturbance regimes (fire, herbivory) are thought to be important in regulating woody cover1,2,4,5, but perceptions differ on which of these are the primary drivers of savanna structure. Here we show, using data from 854 sites across Africa, that maximum woody cover in savannas receiving a mean annual precipitation (MAP) of less than 650 mm is constrained by, and increases linearly with, MAP. These arid and semi-arid savannas may be considered ‘stable’ systems in which water constrains woody cover and permits grasses to coexist, while fire, herbivory and soil properties interact to reduce woody cover below the MAP-controlled upper bound. Above a MAP of 650 mm, savannas are ‘unstable’ systems in which MAP is sufficient for woody canopy closure, and disturbances (fire, herbivory) are required for the coexistence of trees and grass. These results provide insights into the nature of African savannas and suggest that future changes in precipitation6 may considerably affect their distribution and dynamics.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Figure 1: Change in woody cover of African savannas as a function of MAP.
Figure 2: Woody cover as a function of MAP, soil properties and disturbance regimes in arid and semi-arid savannas.
Figure 3: Regression tree showing generalized relationships between woody cover and MAP, fire-return interval and percentage of sand.
Figure 4: The distributions of MAP-determined (‘stable’) and disturbance-determined (‘unstable’) savannas in Africa.


  1. Scholes, R. J. & Archer, S. R. Tree–grass interactions in savannas. Annu. Rev. Ecol. Syst. 28, 517–544 (1997)

    Article  Google Scholar 

  2. House, J. et al. Conundrums in mixed woody–herbaceous plant systems. J. Biogeog. 30, 1763–1777 (2003)

    Article  Google Scholar 

  3. Jackson, R. B., Banner, J. L., Jobaggy, E. G., Pockman, W. T. & Wall, D. H. Ecosystem carbon loss with woody plant invasion of grasslands. Nature 418, 623–626 (2002)

    Article  ADS  CAS  PubMed  Google Scholar 

  4. Sankaran, M., Ratnam, J. & Hanan, N. P. Tree grass coexistence in savannas revisited—insights from an examination of assumptions and mechanisms invoked in existing models. Ecol. Letters 7, 480–490 (2004)

    Article  Google Scholar 

  5. Jeltsch, F., Weber, G. E. & Grimm, V. Ecological buffering mechanisms in savannas: a unifying theory of long-term tree–grass coexistence. Plant Ecol. 150, 161–171 (2000)

    Article  Google Scholar 

  6. Intergovernmental Panel on Climate Change. Climate Change 2001: Synthesis Report. A Contribution of Working Groups I, II, and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change (eds Watson, R. T., Core Writing Team) (Cambridge Univ. Press, Cambridge, UK, 2001)

    Google Scholar 

  7. Simioni, G., Gignoux, J. & Le Roux, X. How does the spatial structure of the tree layer influence water balance and primary production in savannas? Results of a 3D modeling approach. Ecology 84, 1879–1894 (2003)

    Article  Google Scholar 

  8. Sala, O. E. et al. Biodiversity—global biodiversity scenarios for the year 2100. Science 287, 1770–1774 (2000)

    Article  CAS  PubMed  Google Scholar 

  9. Bond, W. J., Midgley, G. F. & Woodward, W. I. The importance of low atmospheric CO2 and fire in promoting the spread of grasslands and savannas. Glob. Change Biol. 9, 973–982 (2003)

    Article  ADS  Google Scholar 

  10. Weltzin, J. F. & McPherson, G. R. (eds) Changing Precipitation Regimes and Terrestrial Ecosystems: A North American Perspective (Univ. Arizona Press, Tucson, 2003)

  11. Walter, H. Ecology of Tropical and Subtropical Vegetation (Oliver and Boyd, Edinburgh, 1971)

    Google Scholar 

  12. Walker, B. H. & Noy-Meir, I. in Ecology of Tropical Savannas (eds Huntley, B. J. & Walker, B. H.) 556–590 (Springer, Berlin, 1982)

    Book  Google Scholar 

  13. Walker, B. H., Ludwig, D., Holling, C. S. & Peterman, R. M. Stability of semi-arid savanna grazing systems. J. Ecol. 69, 473–498 (1981)

    Article  Google Scholar 

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

    Article  Google Scholar 

  15. Frost, P. G. et al. (eds) Response of Savannas to Stress and Disturbance (IUBS, Paris, 1986)

  16. van Langevelde, F. et al. Effects of fire and herbivory on the stability of savanna ecosystems. Ecology 84, 337–350 (2003)

    Article  Google Scholar 

  17. Bond, W. J., Midgley, G. F. & Woodward, F. I. What controls South African vegetation—climate or fire? S. Afr. J. Bot. 69, 79–91 (2003)

    Article  Google Scholar 

  18. McNaughton, S. J. The propagation of disturbance in savannas through food webs. J. Veg. Sci. 3, 301–314 (1992)

    Article  Google Scholar 

  19. Walker, B. H. & Langridge, J. L. Predicting savanna vegetation structure on the basis of plant available moisture (PAM) and plant available nutrients (PAN): a case study from Australia. J. Biogeog. 24, 813–825 (1997)

    Article  Google Scholar 

  20. Hutchinson, M. F., Nix, H. A., McMahon, J. P. & Ord, K. D. Proceedings of the Third International Conference/Workshop on Integrating GIS and Environmental Modeling (National Center for Geographic Information and Analysis, Santa Barbara, 1996)

    Google Scholar 

  21. Barbosa, P. M., Stroppiana, D., Gregoire, J. M. & Pereira, J. M. C. An assessment of vegetation fire in Africa (1981–1991): burned areas, burned biomass, and atmospheric emissions. Glob. Biogeochem. Cycles 13, 933–950 (1999)

    Article  ADS  CAS  Google Scholar 

  22. Chiu, G. S. Bent-cable Regression for Assessing Abruptness of Change. Thesis, Simon Fraser Univ. (2002)

    Google Scholar 

  23. Koenker, R. & Park, B. J. An interior point algorithm for nonlinear quantile regression. J. Econometrics 71, 265–283 (1994)

    Article  MathSciNet  Google Scholar 

  24. Cade, B. S. & Noon, B. R. A gentle introduction to quantile regression for ecologists. Front. Ecol. Environ. 1, 412–420 (2003)

    Article  Google Scholar 

  25. Koenker, R. W. & d'Orey, V. Computing regression quantiles. Appl. Stat. 36, 383–393 (1987)

    Article  Google Scholar 

  26. Koenker, R. W. in Asymptotic Statistics (eds Mandl, P. & Huskova, M.) 349–359 (Springer, New York, 1994)

    Book  Google Scholar 

  27. Breiman, L., Friedman, J. H., Olshen, R. A. & Stone, C. G. Classification and Regression Trees (Wadsworth International Group, Belmont, 1984)

    MATH  Google Scholar 

  28. De'ath, G. & Fabricus, K. E. Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81, 3178–3192 (2000)

    Article  Google Scholar 

  29. Rejwan, C., Collins, N. C., Brunner, L. J., Shuter, B. J. & Ridgway, M. S. Tree regression analysis on the nesting habitat of smallmouth bass. Ecology 80, 341–348 (1999)

    Article  Google Scholar 

  30. White, F. The Vegetation of Africa: A Descriptive Memoir to Accompany the UNESCO/AETFAT/UNSO Vegetation Map of Africa (UNESCO, Paris, 1983)

    Google Scholar 

Download references


This paper arose from a workshop on savanna complexity funded by the NSF. We thank R. Boone, I. McHugh, R. Grant, H. Biggs, W. T. Starmer, P. M. Barbosa, D. Ruess, J. Rettenmayer, C. Williams, J. Klein, M. T. Anderson, W. J. Parton, J. C. Neff, N. Govender and the Kruger Park Scientific Services for comments, help with data collection and analysis, and for providing access to otherwise unpublished data. Author Contributions All authors contributed data or intellectual input to the project.

Author information

Authors and Affiliations


Corresponding author

Correspondence to Mahesh Sankaran.

Ethics declarations

Competing interests

Reprints and permissions information is available at The authors declare no competing financial interests.

Supplementary information

Supplementary Methods

This file provides additional background, methods and results of statistical analyses, and references for data sources. (DOC 40 kb)

Supplementary Tables

This file contains Supplementary Tables 1 and 2 (correlations between soil parameters; summary of results for regression-tree analysis). (DOC 36 kb)

Supplementary Figures

This file contains Supplementary Figures 1–4 (location of sample sites in Africa; relationship between woody cover, MAP and fire-return interval; frequency distributions for soil parameters, herbivore biomass and fire-return intervals; and comparison of woody cover estimates from densiometer and summed canopy area methods). (DOC 135 kb)

Supplementary Data

This file contains the data used for the analysis. (XLS 253 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Sankaran, M., Hanan, N., Scholes, R. et al. Determinants of woody cover in African savannas. Nature 438, 846–849 (2005).

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI:

This article is cited by


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.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing