Letter | Published:

Productivity of North American grasslands is increased under future climate scenarios despite rising aridity

Nature Climate Change volume 6, pages 710714 (2016) | Download Citation

This article has been updated


Grassland productivity is regulated by both temperature and the amount and timing of precipitation1,2. Future climate change is therefore expected to influence grassland phenology and growth, with consequences for ecosystems and economies. However, the interacting effects of major shifts in temperature and precipitation on grasslands remain poorly understood and existing modelling approaches, although typically complex, do not extrapolate or generalize well and tend to disagree under future scenarios3,4. Here we explore the potential responses of North American grasslands to climate change using a new, data-informed vegetation–hydrological model, a network of high-frequency ground observations across a wide range of grassland ecosystems and CMIP5 climate projections. Our results suggest widespread and consistent increases in vegetation fractional cover for the current range of grassland ecosystems throughout most of North America, despite the increase in aridity projected across most of our study area. Our analysis indicates a likely future shift of vegetation growth towards both earlier spring emergence and delayed autumn senescence, which would compensate for drought-induced reductions in summer fractional cover and productivity. However, because our model does not include the effects of rising atmospheric CO2 on photosynthesis and water use efficiency5,6, climate change impacts on grassland productivity may be even larger than our results suggest. Increases in the productivity of North American grasslands over this coming century have implications for agriculture, carbon cycling and vegetation feedbacks to the atmosphere.

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Change history

  • 25 April 2016

    In the version of this Letter originally published, the term for available vegetation (Vt) was mistakenly omitted from the end of equation 2. This has now been corrected in all versions of this Letter.


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The Richardson Lab acknowledges support from the NSF Macrosystems Biology programme (award EF-1065029). T.F.K. acknowledges support from a Macquarie University research fellowship. The Lethbridge ecosystem flux measurements were supported by Discovery grants from the Natural Sciences and Engineering Research Council of Canada to L.B.F. (RGPIN-2014-05882). We thank the World Climate Research Program’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups (listed in Supplementary Table 6) for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Inter-comparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. Furthermore, we acknowledge the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections archive hosted at http://gdo-dcp.ucllnl.org/downscaled_cmip_projections for making their data available. We thank X. Xiao for providing data from the Marena, Oklahoma, site acquired through research grants from the USDA NIFA (Project No. 2012-02355) and National Science Foundation (IIA-1301789). Research at the Continental Divide PhenoCam Site in Butte, Montana is supported by the National Science Foundation-EPSCoR (grant NSF-0701906), OpenDap and Montana Tech of the University of Montana. The Jasper Ridge Biological Preserve is supported by Stanford University and the Carnegie Institution Department of Global Ecology. Research at the Kendall site, Walnut Gulch Experimental Watershed, is funded by the USDA-ARS and the US Department of Energy. Data for PAB01 (Aboveground net primary productivity of tallgrass prairie based on accumulated plant biomass on core LTER watersheds) and climate data (AWE01, APT01) was supported by the NSF Long Term Ecological Research Program (LTER) at the Konza Prairie Biological Station. N.A.B. acknowledges support from the LTER programme at the Konza Prairie Biological Station (DEB-0823341), where the US-Kon Ameriflux site is sponsored by the US Department of Energy under a sub contract from DE-AC02-05CH11231. We thank T. Milliman for maintenance of the PhenoCam data archive, and our PhenoCam collaborators for their efforts in support of this project.

Author information


  1. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA

    • Koen Hufkens
    •  & Andrew D. Richardson
  2. Department of Biological Sciences, Macquarie University, Sydney, New South Wales 02109, Australia

    • Trevor F. Keenan
  3. Department of Biological Sciences, University of Lethbridge, Lethbridge, Alberta T1K3M4, Canada

    • Lawrence B. Flanagan
  4. Southwest Watershed Research Center, USDA-ARS, Tucson, Arizona 85719, USA

    • Russell L. Scott
  5. Department of Plant Biology, University of Illinois, Urbana, Illinois 61801, USA

    • Carl J. Bernacchi
    •  & Eva Joo
  6. USDA-ARS, Global Change and Photosynthesis Research Unit, Urbana, Illinois 61801, USA

    • Carl J. Bernacchi
  7. Department of Geography and Atmospheric Sciences, University of Kansas, Lawrence, Kansas 66045, USA

    • Nathaniel A. Brunsell
  8. Department of Environmental Science, Policy and Management, University of California–Berkeley, Berkeley, California 94720, USA

    • Joseph Verfaillie


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K.H. and A.D.R. designed the study and methodology, with input from T.F.K. A.D.R. contributed PhenoCam imagery. K.H. processed the imagery and performed model simulations. L.B.F., R.L.S., C.J.B., E.J., N.A.B. and J.V. contributed ecosystem flux data. All authors contributed to data analysis and interpretation. K.H. drafted the manuscript with input from T.F.K. and A.D.R. All authors commented on and approved the final manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Koen Hufkens or Andrew D. Richardson.

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