Broad values as the basis for understanding deliberation about protected area management

The success of protected areas in addressing global environmental change depends on the development of management strategies that are inclusive of broad values held by local community members. Here, we report on results from a longitudinal and quasi-experimental study that engaged community members in deliberation around their visions for the future of protected areas in Interior Alaska. Following a regional household survey, we purposively assembled three groups of residents according to the relative strength of their broad value orientations. Each group was engaged in online discussions over a month-long period time and a thematic analysis of the resulting transcripts was performed to understand: (1) the perceived benefits and threats facing protected areas, and (2) reflections on how public land management agencies should improve decision-making to better incorporate the perspectives of residents. Results showed that the landscape provided a multitude of benefits, such as natural beauty, opportunities for living an Alaskan lifestyle, and sense of community. Conversely, climate variability, ambivalence toward tourism, and large-scale development were the primary perceived threats. Residents also shared recommendations for how to build meaningful public engagement processes rooted in a philosophy of ‘inclusive conservation’ that solves sustainability science problems by balancing the consequences of different visions for nature-based solutions. Text-based patterns of deliberation showed that broad values affected the topics of discussion and social learning that occurred in small but meaningful ways. We suggest that people with similar values can hold distinct visions for the future, and that shared spaces for deliberation are important for enabling collective action. We also contend that protected area management decision-making should be transformed through the adoption of a value-based framework whereby guiding principles and relational learning are actively weighed in the process of developing more sustainable solutions for society’s most pressing natural resource management problems.