Community science: A typology and its implications for governance of social-ecological systems. Issue 106 (April 2020)

• Record Type: Journal Article
• Authors: Charles, Anthony; Loucks, Laura; Berkes, Fikret; Armitage, Derek
• Is Part Of: Environmental science & policy. Issue 106(2020)
• Page Start: 77
• Page End: 86
• Publication Date: 2020-04
• Subjects: Community-based environmental monitoring -- Governance fit -- Ecosystem-based management -- Stewardship -- Social learning -- Fisheries and coasts; Environmental policy -- Periodicals; Environmental sciences -- Periodicals; Environnement -- Politique gouvernementale -- Périodiques; Sciences de l'environnement -- Périodiques; Environmental policy; Environmental sciences; Periodicals; Electronic journals; 363.70561
• DOI: 10.1016/j.envsci.2020.01.019
• Languages: English
• ISSNs: 1462-9011

Abstract

Highlights: Community science is community-driven and community-controlled. Community science involves local knowledge, collective action & empowerment. Community science helps to improve conservation, livelihood & governance outcomes. Community science links to ecosystem-based management & environmental sustainability. Community science involves social learning with external, internal or hired expertise. Abstract: There is an increasing recognition globally of the role to be played by community science –scientific research and monitoring driven and controlled by local communities, and characterized by place-based knowledge, social learning, collective action and empowerment. In particular, community science can support social-ecological system transformation, and help in achieving better 'fit' between ecological systems and governance, at local and higher levels of decision making. This paper draws on three examples of communities as central actors in the process of knowledge co-production to present a typology of community science, and to deduce a set of key principles/conditions for success. The typology involves three social learning models in which the community acquires scientific knowledge by (1) engaging with external bodies, (2) drawing on internal volunteer scientific expertise, and/or (3) hiring (or contracting) in-house professional scientific expertise. All of these models share the key characteristic that the local community decides with whom they wish to engage, and in each case, social learning is fundamental. Some conditions that facilitate community science include: community-driven and community-control; flexibility across leadership models; connection to place and collective values; empowerment, agency and collective action; credible trust; local knowledge; and links to governance. Community science is not a panacea for effecting change at the local level, and there is need for critical assessment of how it can help to fill governance gaps. Nevertheless, a considerable body of experience globally illustrates how local communities are drawing effectively on community science for better conservation and livelihood outcomes, in a manner compatible with broader trends toward ecosystem-based management and local stewardship.