Choosing wisely: using discrete choice experiments with experts to inform conservation action

作者：James T. Erbaugh, Luci Lu, Brian E. Robinson, Charlotte H. Chang, Istvan Molnar, Dávid Papp, Yuta J. Masuda · 发表于：Environmental Research Letters · 年份：2026 · DOI：10.1088/1748-9326/ae5fac · 研究领域：Economic and Environmental Valuation、Species Distribution and Climate Change、Sustainability and Climate Change Governance

Abstract Conservation actions often rely on expert knowledge. Ensuring that expert elicitation is broadly inclusive, analyzed rigorously, and cost effective is challenging. Discrete choice experiments (DCEs) with experts present an opportunity to measure the preferences individuals with technical knowledge hold for the provision of public goods. We present a novel approach that combines machine learning, language models, and an email campaign to reach over two thousand experts with a record of peer-reviewed publication. We apply this approach to understand the preferences experts ( n = 2 731) have for natural climate solutions (NCSs) that focus on ecosystem restoration. We found that experts have a collective preference for distributing funding across a variety of actions rather than concentrating on specific restoration actions. In addition, experts preferred that restoration take place in lower-income contexts, highlighting the important role such NCS can play in promoting human well-being in marginalized regions with lower opportunity costs for land. These preferences were robust to experts’ area and regional expertise, supporting the conclusion that their preferences did not narrowly reflect private interests. Overall, our research demonstrates how DCEs can synthesize expert knowledge to inform complex problems around provisioning public goods for conservation.