Learning pathways for engagement: Understanding drivers of pro-environmental behavior in the context of protected area management

J Environ Manage. 2022 Dec 1:323:116204. doi: 10.1016/j.jenvman.2022.116204. Epub 2022 Sep 15.

Abstract

The participation of local communities in management decisions is critically important to the long-term salience and therefore, success, of protected areas. Engaging community members in meaningful ways requires knowledge of their behavior and its antecedents, particularly values. Understanding how learning influences cooperation in conservation initiatives is also fundamentally important for supporting decisions being made about public lands. However, there is little empirical evidence of how learning from different information sources works in conjunction with values that shape behavior. Using data from a household survey of residents living in the Denali region of Interior Alaska, U.S, we estimated a two-step structural equation model to understand the psychological reasons why stakeholders made decisions to collectively benefit the environment. Results showed that more diverse pathways by which learning occurred were instrumental in explaining why residents performed pro-environmental behaviors over the past year. Additionally, values that reflected the goals of eudaimonia influenced the transfer and negotiation of knowledge exchange among stakeholders as a correlate of behavior. Environmental concern and personal norms were positively associated with reported behaviors operationalized as social environmentalism and living in an environmentally conscientious manner, whereas environmental concern and willingness to pay for protected area management positively influenced civic engagement. We argue that broadening the range of learning spaces and considering a more diverse array of values in communities surrounding protected areas will encourage daily lifestyle changes, social interactions to support environmentalism, and more robust, pluralistic forms of public engagement in natural resource management.

MeSH terms

  • Alaska
  • Conservation of Natural Resources* / methods
  • Data Collection
  • Humans