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.

Why win–wins are rare in complex environmental management

Nature Sustainability volume 5, pages 674–680 (2022)Cite this article

Subjects

Abstract

High-profile modelling studies often project that large-scale win–win solutions are widely available, but practitioners are often sceptical of win–win narratives, due to real-world complexity. Here we bridge this divide by showing mathematically why complexity makes win–wins elusive. We provide a general proof that increasing the number of objectives, the number of stakeholders or the number of constraints decreases the availability of win–win outcomes (here meaning Pareto improvements). We also show that a measure of tradeoff severity increases in the number of objectives. As the number of objectives approaches infinity, we show that this tradeoff severity measure approaches a limit unaffected by the curvature of the tradeoff surface. This is surprising because concave tradeoff-surface curvature results in less severe tradeoffs with fewer objectives. Our theory suggests that this difference gradually dissipates as objectives are added. In a meta-analysis, we show that 77% of empirically estimated two-objective tradeoff surfaces are concave. We then show how to approximately extrapolate our tradeoff severity measure to higher numbers of objectives, starting from estimated tradeoffs between fewer objectives. Our results provide modellers with precise intuition into practitioners’ scepticism of win–win narratives and practitioners with guidance for assessing the implications of simple tradeoff models.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

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

Fig. 1: Hypothetical fishery example.
Fig. 2: Tradeoff severity and number of objectives.
Fig. 3: Measuring and extrapolating empirical tradeoff severities.

Data availability

All data used in this study are available in Supplementary Data 1.

Code availability

Mathematica code for Figs. 2d and 3c,d is available as Supplementary Software 1. Supplementary Data 2 is the input data file for this code. It is a subset of the data contained in Supplementary Data 1.

References

  1. Nelson, E. et al. Modeling multiple ecosystem services, biodiversity conservation, commodity production, and tradeoffs at landscape scales. Front. Ecol. Environ. 7, 4–11 (2009).

    Article  Google Scholar 

  2. Tilman, D., Balzer, C., Hill, J. & Befort, B. L. Global food demand and the sustainable intensification of agriculture. Proc. Natl Acad. Sci. USA 108, 20260–20264 (2011).

    Article  CAS  Google Scholar 

  3. Mueller, N. D. et al. A tradeoff frontier for global nitrogen use and cereal production. Environ. Res. Lett. 9, 054002 (2014).

    Article  CAS  Google Scholar 

  4. Costello, C. et al. Global fishery prospects under contrasting management regimes. Proc. Natl Acad. Sci. USA 113, 5125–5129 (2016).

    Article  CAS  Google Scholar 

  5. Burgess, M. G. et al. Protecting marine mammals, turtles, and birds by rebuilding global fisheries. Science 359, 1255–1258 (2018).

    Article  CAS  Google Scholar 

  6. Pascual, U. et al. Social equity matters in payments for ecosystem services. Bioscience 64, 1027–1036 (2014).

    Article  Google Scholar 

  7. Muradian, R. et al. Payments for ecosystem services and the fatal attraction of win–win solutions. Conserv. Lett. 6, 274–279 (2013).

    Article  Google Scholar 

  8. Hopkins, S. R. et al. How to identify win-win interventions that benefit human health and conservation. Nat. Sustain. 4, 298–304 (2021).

    Article  Google Scholar 

  9. Birkenbach, A. M., Smith, M. D. & Stefanski, S. Feature—taking stock of catch shares: lessons from the past and directions for the future. Rev. Environ. Econ. Policy 13, 130–139 (2019).

    Article  Google Scholar 

  10. Perfecto, I. & Vandermeer, J. The agroecological matrix as alternative to the land-sparing/agriculture intensification model. Proc. Natl Acad. Sci. USA 107, 5786–5791 (2010).

    Article  CAS  Google Scholar 

  11. Howe, C., Suich, H., Vira, B. & Mace, G. M. Creating win–wins from trade-offs? Ecosystem services for human well-being: a meta-analysis of ecosystem service trade-offs and synergies in the real world. Glob. Environ. Change 28, 263–275 (2014).

    Article  Google Scholar 

  12. Hajjar, R. et al. A global analysis of the social and environmental outcomes of community forests. Nat. Sustain. 4, 216–224 (2021).

    Article  Google Scholar 

  13. Tallis, H., Kareiva, P., Marvier, M. & Chang, A. An ecosystem services framework to support both practical conservation and economic development. Proc. Natl Acad. Sci. USA 105, 9457–9464 (2008).

    Article  CAS  Google Scholar 

  14. O’Connell, C. S. et al. Balancing tradeoffs: reconciling multiple environmental goals when ecosystem services vary regionally. Environ. Res. Lett. 13, 064008 (2018).

    Article  Google Scholar 

  15. Lester, S. E. et al. Marine spatial planning makes room for offshore aquaculture in crowded coastal waters. Nat. Commun. 9, 945 (2018).

    Article  CAS  Google Scholar 

  16. Fukuyama, F. Political Order and Political Decay: From the Industrial Revolution to the Globalization of Democracy (Macmillan, 2014).

  17. Coello, C. A. C., Lamont, G. B. & Van Veldhuizen, D. A. Evolutionary Algorithms for Solving Multi-Objective Problems 2nd edn (Springer, 2007).

  18. Lester, S. E. et al. Evaluating tradeoffs among ecosystem services to inform marine spatial planning. Mar. Policy 38, 80–89 (2013).

    Article  Google Scholar 

  19. Hegwood, M., Langendorf, R. E. & Burgess, M. G. Supplementary video for Hegwood, Langendorf, and Burgess tradeoff analysis. Zenodo https://doi.org/10.5281/zenodo.6087610 (2022).

  20. Plaza‐Úbeda, J. A., Burgos‐Jiménez, J., Vazquez, D. A. & Liston‐Heyes, C. The ‘win–win’ paradigm and stakeholder integration. Bus. Strategy Environ. 18, 487–499 (2009).

    Article  Google Scholar 

  21. Polasky, S. et al. Where to put things? Spatial land management to sustain biodiversity and economic returns. Biol. Conserv. 141, 1505–1524 (2008).

    Article  Google Scholar 

  22. Halpern, B. S. et al. Achieving the triple bottom line in the face of inherent trade-offs among social equity, economic return, and conservation. Proc. Natl Acad. Sci. USA 110, 6229–6234 (2013).

    Article  CAS  Google Scholar 

  23. White, C., Halpern, B. S. & Kappel, C. V. Ecosystem service tradeoff analysis reveals the value of marine spatial planning for multiple ocean uses. Proc. Natl Acad. Sci. USA 109, 4696–4701 (2012).

    Article  CAS  Google Scholar 

  24. Groot, J. C. et al. Exploring multi-scale trade-offs between nature conservation, agricultural profits and landscape quality—a methodology to support discussions on land-use perspectives. Agric. Ecosyst. Environ. 120, 58–69 (2007).

    Article  Google Scholar 

  25. Groot, J. C., Jellema, A. & Rossing, W. A. Designing a hedgerow network in a multifunctional agricultural landscape: balancing trade-offs among ecological quality, landscape character and implementation costs. Eur. J. Agron. 32, 112–119 (2010).

    Article  Google Scholar 

  26. Law, E. A. et al. Fading opportunities for mitigating agriculture–environment trade-offs in a South American deforestation hotspot. Biol. Conserv. 262, 109310 (2021).

    Article  Google Scholar 

  27. Rabotyagov, S. et al. Spatial multiobjective optimization of agricultural conservation practices using a SWAT model and an evolutionary algorithm. J. Vis. Exp. 70, 4009 (2012).

    Google Scholar 

  28. Ruijs, A., Wossink, A., Kortelainen, M., Alkemade, R. & Schulp, C. J. E. Trade-off analysis of ecosystem services in Eastern Europe. Ecosyst. Serv. 4, 82–94 (2013).

    Article  Google Scholar 

  29. Tóth, S. F. & McDill, M. E. Finding efficient harvest schedules under three conflicting objectives. For. Sci. 55, 117–131 (2009).

    Google Scholar 

  30. Zhou, Z. X., Li, J., Guo, Z. Z. & Li, T. Trade-offs between carbon, water, soil and food in Guanzhong–Tianshui economic region from remotely sensed data. Int. J. Appl. Earth Obs. Geoinf. 58, 145–156 (2017).

    Google Scholar 

  31. Yang, W. et al. Trade-offs among ecosystem services in coastal wetlands under the effects of reclamation activities. Ecol. Indic. 92, 354–366 (2018).

    Article  Google Scholar 

  32. Lautenbach, S., Volk, M., Strauch, M., Whittaker, G. & Seppelt, R. Optimization-based trade-off analysis of biodiesel crop production for managing an agricultural catchment. Environ. Model. Softw. 48, 98–112 (2013).

    Article  Google Scholar 

  33. Zhong, J. et al. Analysis of environmental and economic tradeoffs in switchgrass supply chains for biofuel production. Energy 107, 791–803 (2016).

    Article  Google Scholar 

  34. Kanter, D. R. et al. Evaluating agricultural trade-offs in the age of sustainable development. Agric. Syst. 163, 73–88 (2018).

    Article  Google Scholar 

  35. Bryan, B. A. et al. Land use efficiency: anticipating future demand for land‐sector greenhouse gas emissions abatement and managing trade‐offs with agriculture, water, and biodiversity. Glob. Change Biol. 21, 4098–4114 (2015).

    Article  Google Scholar 

  36. Juutinen, A. et al. Trade-offs between economic returns, biodiversity, and ecosystem services in the selection of energy peat production sites. Ecosyst. Serv. 40, 101027 (2019).

    Article  Google Scholar 

  37. Nalle, D. J., Montgomery, C. A., Arthur, J. L., Polasky, S. & Schumaker, N. H. Modeling joint production of wildlife and timber. J. Environ. Econ. Manage. 48, 997–1017 (2004).

    Article  Google Scholar 

  38. Burgess, M. G., Clemence, M., McDermott, G. R., Costello, C. & Gaines, S. D. Five rules for pragmatic blue growth. Mar. Policy 87, 331–339 (2018).

    Article  Google Scholar 

Download references

Acknowledgements

We thank P. Newton, T. Ippolito, W. Eichhorst and R. Marshall for feedback on earlier drafts of the manuscript, and C. Brooks, B. Wallace, D. Dorman, C. Burgess, D. Kaffine and attendees of several seminars for helpful feedback on and discussion of the concepts and mathematics discussed here. M.H. and M.G.B. acknowledge funding from the US Department of Agriculture (USDA) and National Institute of Food and Agriculture (NIFA) (Award number: 2020-38420-30727 to M.G.B.). R.E.L. and M.G.B. acknowledge funding from the University of Colorado Boulder (start-up grant to M.G.B.).

Author information

Authors and Affiliations

  1. Department of Environmental Studies, University of Colorado Boulder, Boulder, CO, USA

    Margaret Hegwood, Ryan E. Langendorf & Matthew G. Burgess

  2. Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA

    Margaret Hegwood, Ryan E. Langendorf & Matthew G. Burgess

  3. Department of Economics, University of Colorado Boulder, Boulder, CO, USA

    Matthew G. Burgess

Authors
  1. Margaret Hegwood
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ryan E. Langendorf
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Matthew G. Burgess
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.G.B. conceived the project, M.H. and R.E.L. assembled and analysed the data, and M.G.B., R.E.L. and M.H. completed the mathematical proofs. M.G.B., M.H. and R.E.L. wrote the paper.

Corresponding author

Correspondence to Matthew G. Burgess.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Sustainability thanks Rebecca Shaw, Alex Strang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

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

Supplementary information

Supplementary Information

Supplementary methods.

Reporting Summary

Supplementary Data 1

Full meta-analysis data.

Supplementary Data 2

Data input file for Mathematica code.

Supplementary Software 1

Mathematica code for Figs. 2d and 3c,d.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hegwood, M., Langendorf, R.E. & Burgess, M.G. Why win–wins are rare in complex environmental management. Nat Sustain 5, 674–680 (2022). https://doi.org/10.1038/s41893-022-00866-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41893-022-00866-z

Search

Advanced 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