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Confronting the Food–Energy–Environment Trilemma: Global Land Use in the Long Run

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Economic, agronomic, and biophysical drivers affect global land use, so all three influences need to be considered in evaluating economically optimal allocations of the world’s land resources. A dynamic, forward-looking optimization framework applied over the course of the coming century shows that although some deforestation is optimal in the near term, in the absence of climate change regulation, the desirability of further deforestation is eliminated by mid-century. Although adverse productivity shocks from climate change have a modest effect on global land use, such shocks combined with rapid growth in energy prices lead to significant deforestation and higher greenhouse gas emissions than in the baseline. Imposition of a global greenhouse gas emissions constraint further heightens the competition for land, as fertilizer use declines and land-based mitigation strategies expand. However, anticipation of the constraint largely dilutes its environmental effectiveness, as deforestation accelerates prior to imposition of the target.

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  1. This point requires additional clarification. The biophysical and ecological literature suggests that restoration of forest structure and plant species takes at least 30–40 years and usually many more decades (Chazdon 2008), costs several to ten thousands dollars per hectare (Nesshöver et al. 2009), and is only partially successful in achieving reference conditions (Benayas et al. 2009). Modeling restoration of biodiversity under these assumptions introduces greater computational complexity without making significant changes relative to findings presented in this study.

  2. GHG emissions flows are also sequestered by atmospheric and ocean sinks. We ignore this complication as our model does not provide comprehensive accounting of all GHG emissions flows, and focuses on understanding emissions from land use and related sectors.

  3. This doesn’t necessarily mean that biofuels are ’greener’ than fossil fuels. That will depend on the emissions associated with agricultural production and natural land conversion.

  4. The most popular demand systems estimated in recent applied work are the homothetic Cobb-Douglas system (HCD), the linear expenditure system (LES), the constant difference of elasticities demand system (CDE), and the almost ideal demand system (AIDS).

  5. One of well-known limitations of the AIDS system is that its budget shares fall outside \([0,1]\) interval. This frequently occurs when AIDS is applied to model the demand for staple food when income growth is large (Yu et al. 2004, p. 102).

  6. We do not consider the bequest value of protected forests, as they cannot be “scrapped” in our model.

  7. As this study focuses on optimal path of land based GHG emissions, the emissions from combustion of petroleum products are not shown in Fig. 2.

  8. Direct comparison of model predictions of biofuels penetration is difficult due to considerable uncertainty in variety of factors, such as, e.g., evolution of biofuels’ production technologies, land access costs, yield growth rates, and energy demand projections. We show model sensitivity to these factors in counterfactual simulations below, and in Technical Appendix.

  9. We show the model sensitivity to changes in other important model parameters in Technical Appendix.

  10. Of course there are many factors contributing to a potential decline of highly uncertain fossil fuel costs (Pindyck 1999). Our choice of rising fossil fuel costs in this scenario is motivated by understanding global land use decisions under greater resource scarcity.

  11. In 2008 New Zealand passed legislation to include commercial forestry sector in the emissions trading scheme. Regulation of other land-use emissions is expected to take place in 2015 (Source: the New Zealand’s Ministry of Agriculture and Forestry website: In 2010 the European Commission launched a public consultation on whether emissions and removals of greenhouse gases related to land use, land use change and forestry (LULUCF) should be covered by the EU’s target of cutting GHG emissions to 30 % below 1990 levels by 2020 (Source: the European Commission’s website:

  12. The term “green paradox” was first introduced by Sinn (2008).

  13. The size of intertemporal leakage is reduced to 37 % over the period of 200 years.

  14. Lack of regional disaggregation also impedes our ability to speak to the heterogeneous impacts of climate change in light of geographic shifting of production as an adaptation strategy to changing climate (Nelson et al. 2009). Accounting for such shifts would further moderate the impact of adverse climate change on global land use.

  15. The only exception is the interplay of GHG emissions target and higher discount rate, where the decline in natural land conversion is larger compared to the model baseline.


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We would like to thank Yongyang Cai, Ujjayant Chakravorty, Alla Golub, Kenneth Judd, Todd Munson, Paul Preckel, Brent Sohngen, Farzad Taheripour, Wally Tyner, two anonymous reviewers, and the participants of the 4th International Workshop on Empirical Methods in Energy Economics, the American Geophysical Union Annual Meetings, the American Economic Association Annual Meetings, Cowles Summer Conference “Macroeconomics and Climate Change”, and research seminars at Purdue University and the World Bank for their helpful suggestions and comments. We appreciate the financial support from the National Science Foundation, Grant 0951576 “DMUU: Center for Robust Decision Making on Climate and Energy Policy”.

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Correspondence to Jevgenijs Steinbuks.

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Steinbuks, J., Hertel, T.W. Confronting the Food–Energy–Environment Trilemma: Global Land Use in the Long Run. Environ Resource Econ 63, 545–570 (2016).

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