Quantifying the difference that nature recovery can make to selected risk events in the National Risk Register (informed by the State of Natural Capital Report)

Natural England · Research & development · United Kingdom

Buyer
Natural England
Value
£41,250
Deadline
Closes in 31 days (4 Sept 2026)
Published
29 July 2026
Sector
Research & development
Where
United Kingdom

What the buyer wants

This commission sits within Natural England's Natural Capital and Economics Teams, which work on evidence to ensure that nature, and the multiple benefits it provides, are considered in decision-making.

In 2024, Natural England published a State of Natural Capital Report State of Natural Capital Report (SONC). It brings together the best available evidence on the state of England's natural capital. It aims to wake up policymakers, and other decision-makers, to risks from natural capital loss and convince them to invest in, and protect, nature.

SONC contains significant quantitative information. However, its output is qualitative. The lack of quantification means that audiences who are unfamiliar with environmental evidence are unable to weigh the importance of our risk ratings against other risk ratings in their own policy area. This project aims to extend the SONC work into quantification, specifically through reference to 7 risks in the National Risk Register National Risk Register 2025 (NRR).

We are working with the idea that changes in the chronic risks impact on the future likelihood and impact of the event risks in the NRR. Specifically, we are interested in the potential of nature recovery to mitigate expected increases in the likelihood and impacts of a selected group of NRR risks which are nature related.

Project Aims:

This project has two aims. These are:

1) to make the case for nature recovery, through demonstrating the potential for nature recovery to mitigate increases in selected NRR risks.

2) to develop our ability to make quantified connections from SONC to other policy areas to support future work. We are looking for strategic, proportionate and complexity-sensitive quantification, and set out further what we mean by this below.

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