Water availability limits plant growth and production in almost all terrestrial ecosystems1,2,3,4,5. However, biomes differ substantially in sensitivity of aboveground net primary production (ANPP) to between-year variation in precipitation6,7,8. Average rain-use efficiency (RUE; ANPP/precipitation) also varies between biomes, supposedly because of differences in vegetation structure and/or biogeochemical constraints8. Here we show that RUE decreases across biomes as mean annual precipitation increases. However, during the driest years at each site, there is convergence to a common maximum RUE (RUEmax) that is typical of arid ecosystems. RUEmax was also identified by experimentally altering the degree of limitation by water and other resources. Thus, in years when water is most limiting, deserts, grasslands and forests all exhibit the same rate of biomass production per unit rainfall, despite differences in physiognomy and site-level RUE. Global climate models9,10 predict increased between-year variability in precipitation, more frequent extreme drought events, and changes in temperature. Forecasts of future ecosystem behaviour should take into account this convergent feature of terrestrial biomes.

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We thank J. Bronstein, J. Cable, G. Davidowitz, A. Eilts, B. Enquist, D. Ignace, A. Kerkhoff, D. Potts, D. Schimel, L. Venable and M. Pavao-Zuckerman for comments on the manuscript. This work derived from an NCEAS working group, PrecipNet (principal investigator M.E.L.), supported by the National Science Foundation, the University of California, and the Santa Barbara campus. We acknowledge the support of the United States Department of Energy, the National Park Service, the National Science Foundation, and the United States Department of Agriculture.

Author information

Author notes

    • Travis E. Huxman
    •  & Melinda D. Smith

    These authors contributed equally to this work


  1. Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, USA

    • Travis E. Huxman
  2. National Center for Ecological Analysis and Synthesis, Santa Barbara, California 93101, USA

    • Melinda D. Smith
  3. Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06511, USA

    • Melinda D. Smith
  4. Natural Resources Research Institute, Duluth, Minnesota 55811, USA

    • Philip A. Fay
  5. Department of Biology, Colorado State University, Fort Collins, Colorado 80523, USA

    • Alan K. Knapp
  6. Department of Global Ecology, Carnegie Institution of Washington, Stanford, California 94305, USA

    • M. Rebecca Shaw
  7. Department of Environmental Studies, University of California, Santa Cruz, California 95064, USA

    • Michael E. Loik
    •  & Brent M. Haddad
  8. Department of Biological Sciences, University of Nevada, Las Vegas, Nevada 89154, USA

    • Stanley D. Smith
  9. Department of Biological Sciences, Texas Tech University, Lubbock, Texas 79409, USA

    • David T. Tissue
    •  & John C. Zak
  10. Ecology and Evolutionary Biology, University of Tennessee, Knoxville, Tennessee 37919, USA

    • Jake F. Weltzin
  11. Department of Biology, University of New Mexico, Albuquerque, New Mexico 87131, USA

    • William T. Pockman
  12. Department of Ecology and IFEVA, Faculty of Agronomy, University of Buenos Aires, Buenos Aires C1417DSE, Argentina

    • Osvaldo E. Sala
  13. Energy and Resources Group, University of California, Berkeley, California 94720, USA

    • John Harte
  14. Biological Sciences and Merriam-Powell Center for Environmental Research, Northern Arizona University, Flagstaff, Arizona 86011, USA

    • George W. Koch
  15. Biosphere 2 Center, Columbia University, Oracle, Arizona 85623, USA

    • Susan Schwinning
  16. Department of Geological Sciences, University of Colorado, Boulder, Colorado 80309, USA

    • Eric E. Small
  17. Renewable Resources and Botany, University of Wyoming, Laramie, Wyoming 82071, USA

    • David G. Williams


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Competing interests

The authors declare that they have no competing financial interests.

Corresponding authors

Correspondence to Travis E. Huxman or Melinda D. Smith.

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  1. 1.

    Supplementary Tables

    Table 1) Site information, mean annual precipitation, mean annual net primary production for the 14 study sites; Table 2) Stepwise multiple linear regression analysis of aboveground net primary production using annual precipitation, measures of intra-annual precipitation variability, maximum growing season temperature, and previous yr ANPP, for the 14 study sites categorized by their long-term mean ANPP.

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