Uncertainties in ecosystem services assessments and their implications for decision support – A semi-systematic literature review

Abstract

Ecosystem services (ES) assessments are rarely integrated into decision-making processes, with uncertainties often cited as a major barrier. While various uncertainties, such as modelling and data uncertainties, are inherent in ES assessments, their role in uptake of ES assessment results in decision-making remains unclear. We conducted a semi-systematic literature review of scientific papers assessing ES to reveal how uncertainties in ES assessments relate to ES uptake, i.e., the potential use of ES assessment results by decision makers. We performed logistic regressions to analyse the influence of three main sources of uncertainty on ES uptake, i.e., (i) modelling uncertainties, (ii) uncertainties related to qualitative and quantitative descriptions of scenarios, and (iii) uncertainties related to the transfer of ES assessment results into decision-making. Furthermore, we investigated if stakeholder involvement plays a role in ES uptake. First, and most importantly, the results indicate that clarifying the policy context can decrease decision uncertainty and thus improve ES uptake. Referring to a specific policy, following a decisive study purpose and documenting the intended policy entry point are factors that significantly enhance ES uptake. Second, the way how ES are modelled is related to ES uptake. Our results show that using multiple models to assess ES significantly promotes ES uptake. Third, involving stakeholders in ES assessments is significantly associated with increased documented uptake. We discuss that explicitly anchoring the assessment in a policy context increases the salience and timeliness of an ES study, assessing model uncertainties can lead to more credible results, and involving stakeholders can provide more legitimacy, which together increase the potential for ES assessments and their results to be used in decision-making. This study encourages future ES assessments to integrate uncertainties in order to support informed decision-making and promote the conservation and sustainable management of ecosystems and their services.