Biospheric feedback effects in a synchronously coupled model of human and Earth systems (original) (raw)

Nature Climate Change volume 7, pages 496–500 (2017) Cite this article

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Abstract

Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO2 concentration1. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing2,3. While historical data sets are available to inform past and current climate analyses4,5, assessments of future climate change have relied on projections of energy and land use from energy–economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories6. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low–mid-range forcing scenario7. The feedbacks between climate-induced biospheric change and human system forcings to the climate system—demonstrated here—are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy–economic models to ESMs used to date1,8,9.

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Figure 1: Interactions between human and Earth systems using one-way (black) and two-way (black and red) coupling.

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Figure 2: Integrated biospheric change for the twenty-first century, as communicated from ESM to IAM.

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Figure 3: Changes in crop price and land-use area resulting from biospheric feedback.

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Figure 4: Change in global carbon stocks caused by biospheric feedback to human systems.

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Acknowledgements

This work was supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research, including support from the Accelerated Climate Modeling for Energy (ACME) project. This research used resources of the Oak Ridge Leadership Computing Facility, which is a US Department of Energy Office of Science User Facility supported under Contract DE-AC05-00OR22725. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231. This work used the Community Earth System Model, CESM and the Global Change Assessment Model, GCAM. The National Science Foundation and the Office of Science of the US Department of Energy support the CESM project. The authors acknowledge long-term support for GCAM development from the Integrated Assessment Research Program in the Office of Science of the US Department of Energy. Lawrence Berkeley National Laboratory is supported by the US Department of Energy under Contract No. DE-AC02-05CH11231. Initial research by P.E.T., J.M. and X.S. was sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the US Department of Energy. We thank J. Gulledge for comments on the manuscript.

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Author notes

  1. John Truesdale and Anthony Craig: Unaffiliated: jet@ucar.edu (J.T.); anthony.p.craig@gmail.com (A.C.).

Authors and Affiliations

  1. Environmental Sciences Division/Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, 37831, USA
    Peter E. Thornton, Xiaoying Shi & Jiafu Mao
  2. Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, Maryland, 20740, USA
    Katherine Calvin, Ben Bond-Lamberty & Jae Edmonds
  3. Lawrence Berkeley National Laboratory, Berkeley, California, 94720, USA
    Andrew D. Jones, Alan V. Di Vittorio, William D. Collins, John Truesdale & Anthony Craig
  4. University of Maryland, College Park, Maryland, 20742, USA
    Louise Chini & George Hurtt
  5. Field to Market: The Alliance for Sustainable Agriculture, 777 N Capitol St NE, Washington DC, 20002, USA
    Allison Thomson
  6. Computer Science and Mathematics Division/Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, 37831, USA
    Marcia L. Branstetter

Authors

  1. Peter E. Thornton
  2. Katherine Calvin
  3. Andrew D. Jones
  4. Alan V. Di Vittorio
  5. Ben Bond-Lamberty
  6. Louise Chini
  7. Xiaoying Shi
  8. Jiafu Mao
  9. William D. Collins
  10. Jae Edmonds
  11. Allison Thomson
  12. John Truesdale
  13. Anthony Craig
  14. Marcia L. Branstetter
  15. George Hurtt

Contributions

W.D.C., J.E., A.T., B.B.-L., A.D.J. and P.E.T. conceived the study. All authors contributed to development of algorithms. J.T. and A.C. led the software engineering development, X.S. configured and executed simulations, and M.L.B., J.M., K.C., L.C., B.B.-L. and A.V.D.V. performed diagnostics. All authors contributed to analysis of results. P.E.T., B.B.-L., A.D.J., A.V.D.V., K.C., L.C., X.S. and W.D.C. wrote the text, with comments and edits from all authors.

Corresponding author

Correspondence toPeter E. Thornton.

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The authors declare no competing financial interests.

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Thornton, P., Calvin, K., Jones, A. et al. Biospheric feedback effects in a synchronously coupled model of human and Earth systems.Nature Clim Change 7, 496–500 (2017). https://doi.org/10.1038/nclimate3310

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