By embedding a spatially explicit ecosystem services modelling tool within a policy simulator we examine the insights that natural capital analysis can bring to the design of policies for nature recovery. Our study is illustrated through a case example of policies incentivising the establishment of new natural habitat in England. We find that a policy mirroring the current practice of offering payments per hectare of habitat creation fails to break even, delivering less value in improved flows of ecosystem services than public money spent and only 26% of that which is theoretically achievable. Using optimization methods, we discover that progressively more efficient outcomes are delivered by policies that optimally price activities (34%), quantities of environmental change (55%) and ecosystem service value flows (81%). Further, we show that additionally attaining targets for unmonetized ecosystem services (in our case, biodiversity) demands trade-offs in delivery of monetized services. For some policy instruments it is not even possible to achieve the targets. Finally, we establish that extending policy instruments to offer payments for unmonetized services delivers target-achieving and value-maximizing policy designs. Our findings reveal that policy design is of first-order importance in determining the efficiency and efficacy of programmes pursuing nature recovery.This article is part of the theme issue 'Bringing nature into decision-making'.

Natural capital approaches for the optimal design of policies for nature recovery / Day, Brett; Mancini, Mattia; Bateman, Ian J.; Binner, Amy; Cho, Frankie; de Gol, Anthony; Ferguson-Gow, Henry; Fezzi, Carlo; Lee, Christopher; Liuzzo, Lorena; Lovett, Andrew; Owen, Nathan; Pearson, Richard G.; Smith, Greg. - In: PHILOSOPHICAL TRANSACTIONS - ROYAL SOCIETY. BIOLOGICAL SCIENCES. - ISSN 0962-8436. - 379:1903(2024). [10.1098/rstb.2022.0327]

Natural capital approaches for the optimal design of policies for nature recovery

Fezzi, Carlo;
2024-01-01

Abstract

By embedding a spatially explicit ecosystem services modelling tool within a policy simulator we examine the insights that natural capital analysis can bring to the design of policies for nature recovery. Our study is illustrated through a case example of policies incentivising the establishment of new natural habitat in England. We find that a policy mirroring the current practice of offering payments per hectare of habitat creation fails to break even, delivering less value in improved flows of ecosystem services than public money spent and only 26% of that which is theoretically achievable. Using optimization methods, we discover that progressively more efficient outcomes are delivered by policies that optimally price activities (34%), quantities of environmental change (55%) and ecosystem service value flows (81%). Further, we show that additionally attaining targets for unmonetized ecosystem services (in our case, biodiversity) demands trade-offs in delivery of monetized services. For some policy instruments it is not even possible to achieve the targets. Finally, we establish that extending policy instruments to offer payments for unmonetized services delivers target-achieving and value-maximizing policy designs. Our findings reveal that policy design is of first-order importance in determining the efficiency and efficacy of programmes pursuing nature recovery.This article is part of the theme issue 'Bringing nature into decision-making'.
2024
1903
Day, Brett; Mancini, Mattia; Bateman, Ian J.; Binner, Amy; Cho, Frankie; de Gol, Anthony; Ferguson-Gow, Henry; Fezzi, Carlo; Lee, Christopher; Liuzzo,...espandi
Natural capital approaches for the optimal design of policies for nature recovery / Day, Brett; Mancini, Mattia; Bateman, Ian J.; Binner, Amy; Cho, Frankie; de Gol, Anthony; Ferguson-Gow, Henry; Fezzi, Carlo; Lee, Christopher; Liuzzo, Lorena; Lovett, Andrew; Owen, Nathan; Pearson, Richard G.; Smith, Greg. - In: PHILOSOPHICAL TRANSACTIONS - ROYAL SOCIETY. BIOLOGICAL SCIENCES. - ISSN 0962-8436. - 379:1903(2024). [10.1098/rstb.2022.0327]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/436311
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