Creating conservation strategies with value-focused thinking

Biodiversity and human well-being strategies are only as good as the set of ideas people think about. We evaluated value-focused thinking (VFT), a framework that emphasizes creating objectives and strategies that are responsive to the objectives. We performed a proof-of-concept study of VFT with 6 conservation planning teams at a global conservation organization. We developed a package of materials related to VFT, including meeting-session agendas, a virtual facilitation template, facilitator's guide, and evaluation questionnaires. We used these materials to test whether VFT applied in a group setting resulted in high-quality conservation strategies and participant satisfaction and whether our materials were scalable, meaning that someone newly trained in VFT could facilitate planning meetings that resulted in high-quality strategies and participant satisfaction, as compared with an experienced VFT facilitator. Net response indicated positive compelling, feasible, creative, and representative ratings for the conservation strategies per team. Participants indicated satisfaction overall, although satisfaction was greater for objectives than for strategies. Among the participants with previous conservation planning experience, all were at least as satisfied with their VFT strategies compared with previously developed strategies, and none were less satisfied (p = 0.001). Changes in participant satisfaction were not related to facilitator type (experienced or inexperienced with VFT) (p > 0.10). Some participants had a preconceived sense of shared understanding of important values and interests before participating in the study, which VFT strengthened. Our results highlight the advantages of structuring the development and evaluation of conservation planning frameworks around VFT.

Using decision science to evaluate global biodiversity indices

Global biodiversity indices are used to measure environmental change and progress toward conservation goals, yet few indices have been evaluated comprehensively for their capacity to detect trends of interest, such as declines in threatened species or ecosystem function. Using a structured approach based on decision science, we qualitatively evaluated 9 indices commonly used to track biodiversity at global and regional scales against 5 criteria relating to objectives, design, behavior, incorporation of uncertainty, and constraints (e.g., costs and data availability). Evaluation was based on reference literature for indices available at the time of assessment. We identified 4 key gaps in indices assessed: pathways to achieving goals (means objectives) were not always clear or relevant to desired outcomes (fundamental objectives); index testing and understanding of expected behavior was often lacking; uncertainty was seldom acknowledged or accounted for; and costs of implementation were seldom considered. These gaps may render indices inadequate in certain decision-making contexts and are problematic for indices linked with biodiversity targets and sustainability goals. Ensuring that index objectives are clear and their design is underpinned by a model of relevant processes are crucial in addressing the gaps identified by our assessment. Uptake and productive use of indices will be improved if index performance is tested rigorously and assumptions and uncertainties are clearly communicated to end users. This will increase index accuracy and value in tracking biodiversity change and supporting national and global policy decisions, such as the post-2020 global biodiversity framework of the Convention on Biological Diversity.

Untapped potential of collective intelligence in conservation and environmental decision making

Environmental decisions are often deferred to groups of experts, committees, or panels to develop climate policy, plan protected areas, or negotiate trade-offs for biodiversity conservation. There is, however, surprisingly little empirical research on the performance of group decision making related to the environment. We examined examples from a range of different disciplines, demonstrating the emergence of collective intelligence (CI) in the elicitation of quantitative estimates, crowdsourcing applications, and small-group problem solving. We explored the extent to which similar tools are used in environmental decision making. This revealed important gaps (e.g., a lack of integration of fundamental research in decision-making practice, absence of systematic evaluation frameworks) that obstruct mainstreaming of CI. By making judicious use of interdisciplinary learning opportunities, CI can be harnessed effectively to improve decision making in conservation and environmental management. To elicit reliable quantitative estimates an understanding of cognitive psychology and to optimize crowdsourcing artificial intelligence tools may need to be incorporated. The business literature offers insights into the importance of soft skills and diversity in team effectiveness. Environmental problems set a challenging and rich testing ground for collective-intelligence tools and frameworks. We argue this creates an opportunity for significant advancement in decision-making research and practice.