Biospheric feedback effects in a synchronously coupled model of human and Earth systems

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.
Figure 2: Integrated biospheric change for the twenty-first century, as communicated from ESM to IAM.
Figure 3: Changes in crop price and land-use area resulting from biospheric feedback.
Figure 4: Change in global carbon stocks caused by biospheric feedback to human systems.

References

  1. 1

    IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1535 (Cambridge Univ. Press, 2013).

  2. 2

    Hoffman, F. M. et al. Causes and implications of persistent atmospheric carbon dioxide biases in Earth System Models. J. Geophys. Res. 119, 141–162 (2014).

    CAS  Article  Google Scholar 

  3. 3

    Shevliakova, E. et al. Carbon cycling under 300 years of land use change: importance of the secondary vegetation sink. Glob. Biogeochem. Cycles 23, 1–16 (2009).

    Article  Google Scholar 

  4. 4

    Andres, R. J. et al. A synthesis of carbon dioxide emissions from fossil-fuel combustion. Biogeosciences 9, 1845–1871 (2012).

    CAS  Article  Google Scholar 

  5. 5

    Hurtt, G. et al. Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands. Climatic Change 109, 117–161 (2011).

    Article  Google Scholar 

  6. 6

    Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).

    CAS  Article  Google Scholar 

  7. 7

    Thomson, A. et al. RCP4.5: a pathway for stabilization of radiative forcing by 2100. Climatic Change 109, 77–94 (2011).

    CAS  Article  Google Scholar 

  8. 8

    Di Vittorio, A. V. et al. From land use to land cover: restoring the afforestation signal in a coupled integrated assessment—earth system model and the implications for CMIP5 RCP simulations. Biogeosciences 11, 6435–6450 (2014).

    Article  Google Scholar 

  9. 9

    Jones, A. D. et al. Greenhouse gas policy influences climate via direct effects of land-use change. J. Clim. 26, 3657–3670 (2013).

    Article  Google Scholar 

  10. 10

    Ciais, P. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (IPCC, Cambridge Univ. Press, 2013).

    Google Scholar 

  11. 11

    van Vuuren, D. et al. The representative concentration pathways: an overview. Climatic Change 109, 5–31 (2011).

    Article  Google Scholar 

  12. 12

    Meinshausen, M. et al. The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change 109, 213–241 (2011).

    CAS  Article  Google Scholar 

  13. 13

    Lamarque, J.-F. et al. Global and regional evolution of short-lived radiatively-active gases and aerosols in the Representative Concentration Pathways. Climatic Change 109, 191–212 (2011).

    CAS  Article  Google Scholar 

  14. 14

    Nelson, G. C. et al. Climate change effects on agriculture: economic responses to biophysical shocks. Proc. Natl Acad. Sci. USA 111, 3274–3279 (2014).

    CAS  Article  Google Scholar 

  15. 15

    Humpenöder, F. et al. Land-use and carbon cycle responses to moderate climate change: implications for land-based mitigation? Environ. Sci. Technol. 49, 6731–6739 (2015).

    Article  Google Scholar 

  16. 16

    Ruane, A. C. et al. Climate change impact uncertainties for maize in Panama: farm information, climate projections, and yield sensitivities. Agr. Forest Meteorol. 170, 132–145 (2013).

    Article  Google Scholar 

  17. 17

    Welch, J. R. et al. Rice yields in tropical/subtropical Asia exhibit large but opposing sensitivities to minimum and maximum temperatures. Proc. Natl Acad. Sci. USA 107, 14562–14567 (2010).

    CAS  Article  Google Scholar 

  18. 18

    Long, S. P., Ainsworth, E. A., Leakey, A. D. B., Nösberger, J. & Ort, D. R. Food for thought: lower-than-expected crop yield stimulation with rising CO2 concentrations. Science 312, 1918–1921 (2006).

    CAS  Article  Google Scholar 

  19. 19

    Norby, R. J. et al. Forest response to elevated CO2 is conserved across a broad range of productivity. Proc. Natl Acad. Sci. USA 102, 18052–18056 (2005).

    CAS  Article  Google Scholar 

  20. 20

    Sutton, M. A. et al. Uncertainties in the relationship between atmospheric nitrogen deposition and forest carbon sequestration. Glob. Change Biol. 14, 2057–2063 (2008).

    Article  Google Scholar 

  21. 21

    Norby, R. J., Warren, J. M., Iversen, C. M., Medlyn, B. E. & McMurtrie, R. E. CO2 enhancement of forest productivity constrained by limited nitrogen availability. Proc. Natl Acad. Sci. USA 107, 19368–19373 (2010).

    CAS  Article  Google Scholar 

  22. 22

    Rosenzweig, C. et al. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc. Natl Acad. Sci. USA 111, 3268–3273 (2014).

    CAS  Article  Google Scholar 

  23. 23

    Stehfest, E. et al. Integrated Assessment of Global Environmental Change with IMAGE 3.0. Model Description and Policy Applications 370 (The Hague: PBL Netherlands Environmental Assessment Agency, 2014).

    Google Scholar 

  24. 24

    Voldoire, A., Eickhout, B., Schaeffer, M., Royer, J.-F. & Chauvin, F. Climate simulation of the twenty-first century with interactive land-use changes. Clim. Dynam. 29, 177–193 (2007).

    Article  Google Scholar 

  25. 25

    Wise, M., Calvin, K., Kyle, P., Luckow, P. & Edmonds, J. Economic and physical modeling of land use in GCAM 3.0 and an application to agricultural productivity, land, and terrestrial carbon. Clim. Change Econ. 5, 1450003 (2014).

    Article  Google Scholar 

  26. 26

    Hurrell, J. W. et al. The Community Earth System Model: a framework for collaborative research. Bull. Am. Meteorol. Soc. 94, 1339–1360 (2013).

    Article  Google Scholar 

  27. 27

    Collins, W. D. et al. The integrated Earth system model version 1: formulation and functionality. Geosci. Model Dev. 8, 2203–2219 (2015).

    Article  Google Scholar 

  28. 28

    Bond-Lamberty, B. et al. On linking an Earth system model to the equilibrium carbon representation of an economically optimizing land use model. Geosci. Model Dev. 7, 2545–2555 (2014).

    Article  Google Scholar 

  29. 29

    Stainforth, D. A., Allen, M. R., Tredger, E. R. & Smith, L. A. Confidence, uncertainty and decision-support relevance in climate predictions. Phil. Trans. R. Soc. A 365, 2145–2161 (2007).

    CAS  Article  Google Scholar 

  30. 30

    Strachan, N., Pye, S. & Kannan, R. The iterative contribution and relevance of modelling to UK energy policy. Energ. Policy 37, 850–860 (2009).

    Article  Google Scholar 

  31. 31

    Food and Agriculture Organization of the United Nations (FAOSTAT, 2014); faostat3.fao.org

  32. 32

    Kyle, P. et al. GCAM 3.0 Agriculture and Land Use: Data Sources and Methods (Pacific Northwest National Laboratory, 2011).

    Google Scholar 

  33. 33

    Thornton, P. E., Lamarque, J.-F., Rosenbloom, N. A. & Mahowald, N. M. Influence of carbon-nitrogen cycle coupling on land model response to CO2 fertilization and climate variability. Glob. Biogeochem. Cycles 21, GB4018 (2007).

    Article  Google Scholar 

Download references

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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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.

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Correspondence to Peter 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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