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. ...
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 breakeven,
delivering less value in improved flows of ecosystem services than public money spent and
only 26% of that which is theoretically-achievable. Using optimisation 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 unmonetised ecosystem
services (in our case, biodiversity) demands trade-offs in delivery of monetised 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 unmonetised services delivers targetachieving
and value-maximising policy designs. Our findings reveal that policy design is of
first-order importance in determining the efficiency and efficacy of programmes pursuing
nature recovery.