4.7 Article

Combining participatory modelling and citizen science to support volunteer conservation action

Journal

BIOLOGICAL CONSERVATION
Volume 208, Issue -, Pages 76-86

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.biocon.2016.07.037

Keywords

Participatory modelling; Citizen science; Fuzzy cognitive mapping; Public participation in scientific research (PPSR)

Funding

  1. National Science Foundation Award [1233722]
  2. USDA
  3. Direct For Computer & Info Scie & Enginr
  4. Div Of Information & Intelligent Systems [1227550] Funding Source: National Science Foundation
  5. Direct For Computer & Info Scie & Enginr
  6. Office of Advanced Cyberinfrastructure (OAC) [1339707] Funding Source: National Science Foundation
  7. Div Of Information & Intelligent Systems
  8. Direct For Computer & Info Scie & Enginr [1233722] Funding Source: National Science Foundation
  9. Office of Advanced Cyberinfrastructure (OAC)
  10. Direct For Computer & Info Scie & Enginr [1550463] Funding Source: National Science Foundation

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The popularity of both citizen science and participatory modelling has given way to a growing number of case studies that all outline the benefits of more inclusive forms of conservation planning. Citizen science offers volunteers the opportunity to engage in environmental research while participatory modelling engages individuals in community-level environmental decision-making. Although both of these public-science collaborations are often said to lead to improved environmental decision-making, evidence for these outcomes in the peer reviewed literature remains sparse. We suggest that combining these fields has promise for developing community-supported research leading to conservation action. To demonstrate this approach, we present the infrastructure and use of a participatory modelling software called Mental Modeler (http://www.mentalmodeler.org/), used with a citizen science web portal (www.citsci.org) that allows citizen scientists, scientists, and managers to: (1) collaboratively define local conservation issues of shared concern; (2) model and represent assumptions, evidence, and existing information about these issues; (3) run scenarios to discuss potential research or management options; and ultimately (4) co-develop citizen scientific research and conservation plans. Using case study data from two community groups working on locally-defined issues related to land management practices in the US, we demonstrate how coordinated learning through modelling practices can lead to the development of self-organized and co-created conservation action. We conclude that the development of online modelling tools holds strong promise for the fields of both citizen science and conservation biology. Published by Elsevier Ltd.

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