title: Nonlinear effects of group size on collective action and resource outcomes.
abstract: For decades, scholars have been trying to determine whether small or large groups are more likely to cooperate for collective action and successfully manage common-pool resources. Using data gathered from the Wolong Nature Reserve since 1995, we examined the effects of group size (i.e., number of households monitoring a single forest parcel) on both collective action (forest monitoring) and resource outcomes (changes in forest cover) while controlling for potential confounding factors. Our results demonstrate that group size has nonlinear effects on both collective action and resource outcomes, with intermediate group size contributing the most monitoring effort and leading to the biggest forest cover gain. We also show how opposing effects of group size directly and indirectly affect collective action and resource outcomes, leading to the overall nonlinear relationship. Our findings suggest why previous studies have observed differing and even contradictory group-size effects, and thus help guide further research and governance of the commons. The findings also suggest that it should be possible to improve collective action and resource outcomes by altering factors that lead to the nonlinear group-size effect, including punishing free riding, enhancing overall and within-group enforcement, improving social capital across groups and among group members, and allowing self-selection during the group formation process so members with good social relationships can form groups autonomously.
authors.affiliation: Center for Systems Integration and Sustainability, Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48823, USA. yangwu1201@gmail.com
authors.forename: Wu
authors.initials: W
authors.lastname: Yang
authors.forename: Wei
authors.initials: W
authors.lastname: Liu
authors.forename: Andrés
authors.initials: A
authors.lastname: Viña
authors.forename: Mao-Ning
authors.initials: MN
authors.lastname: Tuanmu
authors.forename: Guangming
authors.initials: G
authors.lastname: He
authors.forename: Thomas
authors.initials: T
authors.lastname: Dietz
authors.forename: Jianguo
authors.initials: J
authors.lastname: Liu
mesh_terms: D000818:Animals; D044822:Biodiversity; D002681:China; D003247:Conservation of Natural Resources / Q000379:methods* / Q000706:statistics & numerical data; D017753:Ecosystem; D006126:Group Processes; D006801:Humans; D017711:Nonlinear Dynamics; D012944:Social Support; D014197:Trees; D001503:Ursidae
keywords: biodiversity conservation; casual inference; commons governance; ecosystem services; sustainability