Courts have determined that adaptive management does not satisfy the Endangered Species Act's requirement to use the 'best available science'. This is due, in part, to the failure to recognise the role of non-epistemic values in science. We examine the role of values in the legal controversy over the scientific reports and adaptive management plans for endangered salmon in the Columbia River Basin. To do this, we employ philosophical concepts related to risk and uncertainty that demonstrate how non-epistemic values are (...) internal to science. We describe how, because adaptive management is a method for dealing with inductive risk, by remaining flexible, responsive and adaptive in those circumstances where the costs of making a mistake are very high, it requires special attention to ensure that it remains useful. We conclude that, because non-epistemic values will inevitably influence the 'best available science', it is critical that they are clarified in any adaptive management planning so that we can ensure the salmon conservation that the ESA mandates. Fortunately, because adaptive management is iterative in nature and includes opportunities for engagement between policymakers and scientists, it enables clarification of non-epistemic values through making standards of evidence transparent, acknowledging aims and goals and dealing with uncertainty at the institutional level. (shrink)

This article explores how scientists adapt to a changing climate. To do this, we bring examples from a case study of salmon habitat restorationists in the Columbia River Basin into conversation with concepts from previous work on change and stability in knowledge infrastructures and scientific practice. In order to adapt, ecological restorationists are increasingly relying on predictive modeling tools, as well as initiating broader changes in the interdisciplinary nature of the field of ecological restoration itself. We explore how the field (...) of ecological restoration is shifting its conceptual gaze from restoring to past, historic baselines to anticipating a no-analog future and consider what this means in terms of understanding the adaptive capacity of knowledge infrastructures and epistemic communities more broadly. We argue that identifying how scientists themselves conceptualize drivers of change and respond to these changes is an important step in understanding what adaptive capacity in science might entail. We offer these examples as a provocation for thinking about “adaptive epistemologies” and how adaptation by scientists themselves can facilitate or hinder particular environmental or sociotechnical futures. (shrink)