How to make land use policy decisions: Integrating science and economics to deliver connected climate, biodiversity, and food objectives

Land use change is crucial to addressing the existential threats of climate change and biodiversity loss while enhancing food security [M. Zurek et al.Science 376, 1416–1421 (2022)]. The interconnected and spatially varying nature of the impacts of land use change means that these challenges must be addressed simultaneously [H.-O. Pörtner et al.Science 380, eabl4881 (2023)]. However, governments commonly focus on single issues, incentivizing land use change via “Flat-Rate” subsidies offering constant per hectare payments, uptake of which is determined by the economic circumstances of landowners rather than the integrated environmental outcomes that will be delivered [G. Q. Bull et al.Forest Policy Econ. 9, 13–31 (2006)]. Here, we compare Flat-Rate subsidies to two alternatives: “Land Use Scenario” allocation of subsidies through consultation across stakeholders and interested parties; and a “Natural Capital” approach which targets subsidies according to expected ecosystem service response. This comparison is achieved by developing a comprehensive decision support system, integrating new and existing natural, physical, and economic science models to quantify environmental, agricultural, and economic outcomes. Applying this system to the United Kingdom’s net zero commitment to increase carbon storage via afforestation, we show that the three approaches result in significantly different outcomes in terms of where planting occurs, their environmental consequences, and economic costs and benefits. The Flat-Rate approach actually increases net carbon emissions while Land Use Scenario allocation yields poor economic outcomes. The Natural Capital targeted approach outperforms both alternatives, providing the highest possible social values while satisfying net zero commitments.

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Research theme(s)
Environmental impacts Policy, business & governance
GGR Method(s)
Woodland creation and management
Publication type
Article
Author(s)
Ian J. Bateman, Amy Binner, Ethan T. Addicott, Brett H. Day
Publication date
November 13, 2024
Publisher
Proceedings of the National Academy of Sciences of the United States of America
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