Tam, J., T. Waring, S. Gelcich, K.M.A. Chan and T. Satterfield (2021). “Measuring behavioral social learning in a conservation context: Chilean fishing communities.” Conservation Science and Practice n/a(n/a): e336. Doi: 10.1111/csp2.336
In the sustainability and conservation sciences, “social learning” is defined as a group process which depends on trust and social capital and tends to boost conservation outcomes. We term this “collaborative social learning.” Meanwhile, the behavioral sciences define social learning as the individual use of socially acquired information and seek to explain how individuals employ social learning as part of adaptive behavior. We term this “behavioral social learning.” However, the influence of behavioral social learning on ecological outcomes is poorly understood. We conducted a study of behavioral social learning among fishers in seven communities in Chile’s Region V to probe its connections with ecological outcomes and collaborative social learning. We develop and employ a novel behavioral measure of individual social learning in a simple fishing game in which fishers may pay a portion of their game earnings to observe and learn from other fishers in the game. We explore the internal and external validity of the instrument. The self-consistency of game play, learning, and participant reflections reveals strong internal validity of the learning game. Additionally, game behavior is correlated with factors such as migration history, and the perceived availability of peers from whom to learn, suggesting the method also holds external validity. We then test whether factors associated with collaborative social learning, such as social capital, are related to social learning behavior as measured by the experiment. Interestingly, many correlates of ‘collaborative social learning’ are not strongly correlated with ‘behavioral social learning’ in our sample. We argue that this disconnect can help improve our understanding of the emergence of community-based conservation and positive ecological outcomes as well as ‘collaborative social learning’ itself. Finally, we provide guidance on how behavioral measures of social learning could benefit community-based natural resource management and conservation.