Knowledge gaps and future research needs for assessing the non-market benefits of Nature-Based Solutions and...

Nature-Based Solutions (NBS) can be defined as solutions based on natural processes that meet societal challenges and simultaneously provide human well-being and biodiversity benefits. These solutions are envisioned to contribute to operationalizing sustainable development strategies, especially in the context of adaptation to climate change (e.g. flood risk reduction). In order to quantify NBS performance, ease their uptake and advocate for them as alternatives to "business-as-usual" infrastructures, a comprehensive, holistic valuation of their multiple benefits (multiple advantages and disadvantages) is needed. This entails quantifying non-market benefits for people and nature in addition to determining the (direct) cost-benefit of the risk-reduction measure. Despite the importance given to the assessment of non-tangible benefits for people and nature in the literature, systematic data collection on these dimensions seems to be missing. This study reviews publications that used stated preference methods to assess non-market human benefits of NBS and NBS-like strategies. Its aim is to highlight any biases or knowledge gaps in this kind of evaluation. Our results show that the valuation of non-tangible benefits of NBS (e.g. increased recreation and well-being, enhanced biodiversity) still suffers from a lack of common framing. Despite some steps being taken on enabling interconnected benefit assessments, unexploited opportunities concerning the integrated assessment of non-market human and nature benefits predominate. Moreover, the research to-date appears based on a case-to-case approach, and thus a shared holistic method does not emerge from the present literature, potentially delaying the uptake of NBS. We argue that future research could minimize missed opportunities by focusing on and systematically applying holistic benefits assessments. Methods based on stated preference surveys may help to ensure holistic approaches are taken, as well as contributing to their replicability and application when upscaling NBS.