Recent research indicates increasing openness among conservation experts toward a set of previously controversial proposals for biodiversity protection. These include actions such as assisted migration, and the application of climate-change-informed triage principles for decision-making (e.g., forgoing attention to target species deemed no longer viable). Little is known however, about the levels of expert agreement across different conservation adaptation actions, or the preferences that may come to shape policy recommendations. In this paper, we report findings from a web-based survey of biodiversity experts that assessed: (1) perceived risks of climate change (and other drivers) to biodiversity, (2) relative importance of different conservation goals, (3) levels of agreement/disagreement with the potential necessity of unconventional-taboo actions and approaches including affective evaluations of these, (4) preferences regarding the most important adaptation action for biodiversity, and (5) perceived barriers and strategic considerations regarding implementing adaptation initiatives. We found widespread agreement with a set of previously contentious approaches and actions, including the need for frameworks for prioritization and decision-making that take expected losses and emerging novel ecosystems into consideration. Simultaneously, this survey found enduring preferences for conventional actions (such as protected areas) as the most important policy action, and negative affective responses toward more interventionist proposals. We argue that expert views are converging on agreement across a set of taboo components in ways that differ from earlier published positions, and that these views are tempered by preferences for existing conventional actions and discomfort toward interventionist options. We discuss these findings in the context of anticipating some of the likely contours of future conservation debates. Lastly, we underscore the critical need for interdisciplinary, comparative, place-based adaptation research.