Skip to main content

Thank you for visiting nature.com. 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.

Use and non-use value of nature and the social cost of carbon

Abstract

Climate change is damaging ecosystems throughout the world with serious implications for human well-being. Quantifying the benefits of reducing emissions requires understanding these costs, but the unique and non-market nature of many goods provided by natural systems makes them difficult to value. Detailed representation of ecological damages in models used to calculate the costs of greenhouse gas emissions has been largely lacking. Here, we have expanded a cost–benefit integrated assessment model to include natural capital as a form of wealth. This brings benefits to people through non-use existence value and as an input into the production of ecosystem services and market goods. In our model, using central estimates for all parameters, optimal emissions reach zero by the year 2050, limiting warming to 1.5 °C by the year 2100. We used Monte Carlo analysis to examine the influence of several key uncertain model parameters, and examined the effect of adaptive investments in natural systems that partially offset climate damages. Overall, we show that accounting for the use and non-use value of nature has large implications for climate policy. Our analysis suggests that better understanding climate impacts on natural systems and associated welfare effects should be a high priority for future research.

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

from$1.95

to$39.95

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

Fig. 1: GreenDICE diagram for modelling the welfare effects of climate change impacts on natural capital.
Fig. 2: Climate policy results derived from the DICE and GreenDICE models.
Fig. 3: Sensitivity analysis of uncertain parameters under welfare maximization conditions.
Fig. 4: Random forest analysis of Monte Carlo simulation.
Fig. 5: Impacts of the Adaptive Investments model on natural capital and climate damage.

Data availability

Results of the simulations are available at https://github.com/BerBastien/GreenDICE/tree/master/Results

Code availability

GreenDICE code is available at www.GitHub.com/BerBastien/GreenDICE

References

  1. Pascual, U. et al. Valuing nature’s contributions to people: the IPBES approach. Curr. Opin. Environ. Sustain. 26, 7–16 (2017).

    Article  Google Scholar 

  2. De Groot, R. S., Alkemade, R., Braat, L., Hein, L. & Willemen, L. Challenges in integrating the concept of ecosystem services and values in landscape planning, management and decision making. Ecol. Complex. 7, 260–272 (2010).

    Google Scholar 

  3. Turner, R. K. et al. Valuing nature: lessons learned and future research directions. Ecol. Econ. 46, 493–510 (2003).

    Article  Google Scholar 

  4. Agarwala, M., Atkinson, G., Baldock, C. & Gardiner, B. Natural capital accounting and climate change. Nat. Clim. Change 4, 520–522 (2014).

    Article  Google Scholar 

  5. Jones-Walters, L. & Mulder, I. Valuing nature: the economics of biodiversity. J. Nat. Conserv. 17, 245–247 (2009).

    Article  Google Scholar 

  6. Gomes, V. H. F., Vieira, I. C. G., Salomão, R. P. & ter Steege, H. Amazonian tree species threatened by deforestation and climate change. Nat. Clim. Change 9, 547–553 (2019).

    Article  Google Scholar 

  7. Rogers, L. A. et al. Shifting habitats expose fishing communities to risk under climate change. Nat. Clim. Change 9, 512–516 (2019).

    Article  Google Scholar 

  8. Roberts, C. P., Allen, C. R., Angeler, D. G. & Twidwell, D. Shifting avian spatial regimes in a changing climate. Nat. Clim. Change 9, 562–566 (2019).

    Article  Google Scholar 

  9. Pecl, G. T. et al. Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).

    Article  Google Scholar 

  10. Settele, J. et al. in Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds. Field, C. B. et al.) 271–360 (IPCC, Cambridge Univ. Press, 2015).

  11. Warszawski, L. et al. A multi-model analysis of risk of ecosystem shifts under climate change. Environ. Res. Lett. 8, 044018 (2013).

    Article  Google Scholar 

  12. Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42 (2003).

    Article  CAS  Google Scholar 

  13. Global Assessment Report on Biodiversity and Ecosystem Services (Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services, 2019).

  14. Millennium Ecosystem Assessment Ecosystems and Human Well-being: Synthesis (Island Press, 2005).

  15. Drupp, M. A. Limits to substitution between ecosystem services and manufactured goods and implications for social discounting. Environ. Resour. Econ. 69, 135–158 (2018).

    Article  Google Scholar 

  16. Hoel, M. & Sterner, T. Discounting and relative prices. Clim. Change 84, 265–280 (2007).

    Article  Google Scholar 

  17. Sterner, T. & Persson, U. M. An even sterner review: introducing relative prices into the discounting debate. Rev. Environ. Econ. Policy 2, 61–76 (2008).

    Article  Google Scholar 

  18. Drupp, M. A. & Hänsel, M. C. Relative prices and climate policy: how the scarcity of non-market goods drives policy evaluation. Am. Econ. J. Econ. Policy https://www.aeaweb.org/articles?id=10.1257/pol.20180760 (2020).

  19. Tol, R. S. The damage costs of climate change: a note on tangibles and intangibles, applied to DICE. Energy Policy 22, 436–438 (1994).

    Article  Google Scholar 

  20. Kopp, R. E., Golub, A., Keohane, N. O. & Onda, C. The influence of the specification of climate change damages on the social cost of carbon. Economics-Kiel 6, 1–40 (2012).

    Google Scholar 

  21. Moore, F. C. & Diaz, D. B. Temperature impacts on economic growth warrant stringent mitigation policy. Nat. Clim. Change 5, 127–131 (2015).

    Article  Google Scholar 

  22. Tol, R. S. Estimates of the damage costs of climate change. Part 1: benchmark estimates. Environ. Resour. Econ. 21, 47–73 (2002).

    Article  Google Scholar 

  23. Diaz, D. & Moore, F. Quantifying the economic risks of climate change. Nat. Clim. Change 7, 774–782 (2017).

    Article  Google Scholar 

  24. Nordhaus, W. D. & Tobin, J. in Economic Research: Retrospect and Prospect Vol. 5 1–80 (NBER, 1972).

  25. Nordhaus, W. & Sztorc, P. DICE 2013R: Introduction and User’s Manual (retrieved November, 2019); https://go.nature.com/3kmwMc5

  26. Barbier, E. B. The concept of natural capital. Oxf. Rev. Econ. Policy 35, 14–36 (2019).

    Article  Google Scholar 

  27. Arrow, K. J., Dasgupta, P., Goulder, L. H., Mumford, K. J. & Oleson, K. Sustainability and the measurement of wealth. Environ. Dev. Econ. 17, 317–353 (2012).

    Article  Google Scholar 

  28. Lange, G.-M., Wodon, Q. & Carey, K. The Changing Wealth of Nations 2018: Building a Sustainable Future (The World Bank, 2018).

  29. Hackett, S. B. & Moxnes, E. Natural capital in integrated assessment models of climate change. Ecol. Econ. 116, 354–361 (2015).

    Article  Google Scholar 

  30. Dietz, S. & Stern, N. Endogenous growth, convexity of damage and climate risk: how Nordhaus’ framework supports deep cuts in carbon emissions. Econ. J. 125, 574–620 (2015).

    Article  Google Scholar 

  31. Glotter, M. J., Pierrehumbert, R. T., Elliott, J. W., Matteson, N. J. & Moyer, E. J. A simple carbon cycle representation for economic and policy analyses. Clim. Change 126, 319–335 (2014).

    Article  CAS  Google Scholar 

  32. Arrow, K. et al. Report of the NOAA panel on contingent valuation. Fed. Regist. 58, 4601–4614 (1993).

    Google Scholar 

  33. Bateman, I. & Willis, K. (eds) Valuing Environmental Preferences: Theory and Practice of the Contingent Valuation Method in the US, EU, and Developing Countries (Oxford Univ. Press, 2001).

  34. Champ, P. A., Boyle, K. J., Brown, T. C. & Peterson, L. G. (eds) A Primer on Nonmarket Valuation Vol. 3 (Springer, 2003).

  35. Technical Support Document: - Social Cost of Carbon for Regulatory Impact Analysis - Under Executive Order 12866 (Interagency Working Group on Social Cost of Carbon, United States Government, 2010).

  36. Beckage, B. et al. Linking models of human behaviour and climate alters projected climate change. Nat. Clim. Change 8, 79–84 (2018).

    Article  Google Scholar 

  37. Breiman, L. Manual On Setting Up, Using, And Understanding Random Forests V3.1 https://www.stat.berkeley.edu/ breiman/Using_random_forests_V3.1.pdf (2002).

  38. Lemoine, D. & Traeger, C. P. Economics of tipping the climate dominoes. Nat. Clim. Change 6, 514–519 (2016).

    Article  Google Scholar 

  39. Cai, Y. & Lontzek, T. S. The social cost of carbon with economic and climate risks. J. Polit. Econ. 127, 2684–2734 (2019).

    Article  Google Scholar 

  40. Traeger, C. P. A 4-stated DICE: quantitatively addressing uncertainty effects in climate change. Environ. Resour. Econ. 59, 1–37 (2014).

    Article  Google Scholar 

  41. Crost, B. & Traeger, C. Optimal climate policy: uncertainty versus Monte Carlo. Econ. Lett. 120, 552–558 (2013).

    Article  Google Scholar 

  42. Statistical Office of the European Union Environmental Protection Expenditure Accounts: Handbook (Eurostat, 2017).

  43. Diaz, D. B. Estimating global damages from sea level rise with the Coastal Impact and Adaptation Model (CIAM). Clim. Change 137, 143–156 (2016).

    Article  Google Scholar 

  44. De Bruin, K. C., Dellink, R. B. & Tol, R. S. AD-DICE: an implementation of adaptation in the DICE model. Clim. Change 95, 63–81 (2009).

    Article  Google Scholar 

  45. Urban, M. C. Accelerating extinction risk from climate change. Science 348, 571–573 (2015).

    Article  CAS  Google Scholar 

  46. Chaplin-Kramer et al. Global modeling of nature’s contributions to people. Science 366, 255–258 (2019).

    Article  CAS  Google Scholar 

  47. Moore, F. C. et al. Mimi-PAGE, an open-source implementation of the PAGE09 integrated assessment model. Sci. Data 5, 180187 (2018).

    Article  Google Scholar 

  48. Anthoff, D., Plevin, R., Kingdon, C. & Rennels, L. Mimi: An Integrated Assessment Modeling Framework (2020); https://www.mimiframework.org/

  49. Solow, R. M. Is the end of the world at hand? Challenge 16, 39–50 (1973).

    Article  Google Scholar 

  50. Stiglitz, J. E. in Scarcity and Growth Reconsidered (ed. Smith, V. K.) 36–66 (The Johns Hopkins Univ. Press, 1979).

  51. Brandt, N., Schreyer, P. & Zipperer, V. Productivity measurement with natural capital. Rev. Income Wealth 63, S7–S21 (2017).

    Article  Google Scholar 

  52. Costanza et al. Changes in the global value of ecosystem services. Glob. Environ. Change 26, 152–158 (2014).

    Article  Google Scholar 

  53. Howard, P. H. & Sterner, T. Few and not so far between: a meta-analysis of climate damage estimates. Environ. Resour. Econ. 68, 197–225 (2017).

    Article  Google Scholar 

  54. Hsiang et al. Estimating economic damage from climate change in the United States. Science 356, 1362–1369 (2017).

    Article  CAS  Google Scholar 

  55. Yamaguchi, R. & Managi, S. Backward-and forward-looking shadow prices in inclusive wealth accounting: an example of renewable energy capital. Ecol. Econ. 156, 337–349 (2019).

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the National Science Foundation (award number 1924378: ‘CNH2-S: Understanding the Coupling Between Climate Policy and Ecosystem Change’), the Hellman Fellows Program (F.C.M.), the Fulbright-García Robles Fellowship (B.A.B.-O.) and a UC Davis John Muir Institute of the Environment Fellowship (B.A.B.-O.).

Author information

Authors and Affiliations

Authors

Contributions

B.A.B.-O. and F.C.M. conceived the study, analysed the results and prepared the manuscript. B.A.B.-O. coded the model and performed the simulations.

Corresponding author

Correspondence to Bernardo A. Bastien-Olvera.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Effects of different estimates of natural capital.

Effects of different estimates of the natural capital-adjusted total factor productivity and natural capital current value relative to current manufactured capital. Red stars give values using the preferred parameter estimates. Size of circles represents the current global estimate of natural capital value with respect to manufactured capital.

Extended Data Fig. 2 Three levels of adaptation costs.

Key policy variables under welfare-maximizing conditions of three levels of adaptation costs. Dotted line is standard DICE, and dashed-dotted line is GreenDICE without investments.

Extended Data Fig. 3 Investments on natural capital stock.

Welfare-maximizing investments on natural capital stock.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, Tables 2–6 and notes.

Supplementary Table 1

Key parameters and functional forms introduced in GreenDICE. If not specified, the parameter is the same as in DICE 2013R.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bastien-Olvera, B.A., Moore, F.C. Use and non-use value of nature and the social cost of carbon. Nat Sustain 4, 101–108 (2021). https://doi.org/10.1038/s41893-020-00615-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41893-020-00615-0

This article is cited by

Search

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