NbS Triple Win Toolkit: Economics and Finance 81 not be possible. What is important is therefore being able to understand the source of the cost information per ecosystem and NbS intervention, what drives costs in the local context and therefore the caveats of extrapolating locally generated data or simplifying assumptionsacross large spatial scales. Use of proxy studies for economic efficiency of NbS Since it is often recognised that data required to perform detailed economic analyses are not obtainable and such analyses are complex, in many cases the benefits of a comprehensive economic analysis may not be proportionate to the cost of collecting, interpreting and synthesising the data from disparate sources with varying levels of reliability122. Analyses are contingent on local data, capacity and resources which may be too costly or technically challenging to undertake for individual, smaller scale projects. The temporal and spatial scale, along with the proposed costs of the NbS project, may also preclude a rigorous economic assessment from being deemed a cost-effective use of resources. For this reason, the Green Climate Fund guidance states that whilst economic and financial efficiency or effectiveness should be demonstrated in project proposals, a formal cost-benefit analysis is not mandatory123. The guidance provides a range of evidence deemed ‘acceptable’, which varies from formalised economic analysis which include the full suite of monetised benefits, costs and modelling assumptions, to qualitative evaluations which compare the project proposal with similar project which did complete economic analysis. Many case study project proposals rely on the results of similar studies which have either already performed a similar type of analysis required to demonstrate cost-effectiveness or value for money or make the broad economic case for similar types of NbS projects. These studies are often referenced to demonstrate that a) the wider economic casefor investment in ecosystems is strong48, b) ecosystem-based interventions can be more cost-effective than grey infrastructure102, or c) climate services, modelling and risk information can be extremely cost-effective124. The use of similar studies to justify intervention is perhaps reasonable if the economic case is strong for local livelihoods or other strategic objectives important for the donor and recipient. In the absence of strategic objectives for biodiversity, there is a risk that benefits for biodiversity continue to be misapplied or unquantified, rather than measured and incorporated actively into project planning and appraisal. At the same time, a reliance on monetised benefits to guide the decision-making process risks the qualitative but strategically significant benefits being ignored. In addition, publication dates of the studies most regularly referenced date back to 201348,102,124. Continued reliance on the same studies risks stagnating the evidence base for NbS.