Research about ecosystem services (ES) often aims to generate knowledge that influences policies and institutions for conservation and human development. However, we have limited understanding of how decision-makers use ES knowledge or what factors facilitate use. Here we address this gap and report on, to our knowledge, the first quantitative analysis of the factors and conditions that explain the policy impact of ES knowledge. We analyze a global sample of cases where similar ES knowledge was generated and applied to decision-making. We first test whether attributes of ES knowledge themselves predict different measures of impact on decisions. We find that legitimacy of knowledge is more often associated with impact than either the credibility or salience of the knowledge. We also examine whether predictor variables related to the science-to-policy process and the contextual conditions of a case are significant in predicting impact. Our findings indicate that, although many factors are important, attributes of the knowledge and aspects of the science-to-policy process that enhance legitimacy best explain the impact of ES science on decision-making. Our results are consistent with both theory and previous qualitative assessments in suggesting that the attributes and perceptions of scientific knowledge and process within which knowledge is coproduced are important determinants of whether that knowledge leads to action. ecosystem services | science policy interface | conservation | knowledge systems | boundary organizations T he ongoing loss of biological diversity and persistence of poverty have sparked interest in policies that protect, restore, and enhance ecosystem services (ES). In response, there has been a growth in ES research that aims to inform policies, incentives, and institutions on a large scale (1-3). Despite this goal, scientific knowledge about ES continues to have limited impact on policy and decisions (1, 4-7).The fact that most land-and resource-use policy decisions still do not take ES into account stems in part from an ineffective interface between ES science and policy, a need for scientists to better understand decision-making processes, and challenges in clarifying conflicting stakeholder values (8-11). In some cases, the science-policy interface is an important aspect of decisionmaking, but often the ES research and policy communities are disconnected from one another, with limited interactions, infrequent exchanges of information, and different objectives that hinder coordinated science and policy processes (12). Many scientists conduct ES research without fully considering how the knowledge they are producing might be used (5). If we want ES information to be incorporated into decisions, then we need to understand how and why decision-makers use certain kinds of information. We define "information" as a tangible, factual output of scientific research produced through specific ES analyses; "knowledge" as a body of information learned and conveyed through scientific and policy processes; ...