Fuzzy Cognitive Mapping: Wildlife Conservation and Bushmeat Hunting in Tanzania
The purpose of this PM was to understand the social and ecological drivers of the zebra and wildebeest bushmeat trade from the perspectives of Tanzanian bushmeat hunters, bushmeat sellers, and bushmeat consumers who reside in communities adjacent to an international protected area, the Serengeti National Park. Although several conservation programs have been initiated by international NGOs and government agencies to decrease illegal hunting in the area (Rentsch 2012), the variable success of these programs prompted park officials and researchers to compare assumptions about the drivers of the bushmeat trade between current conservation policies and community-based perspectives. The purpose of the study was to identify structural characteristics of the issue based on local knowledge, including the identification of specific social and ecological variables comprising the system and networked relationships between these variables. Fuzzy cognitive mapping (FCM) was used because the approach is flexible and can be undertaken with little formalized training and minimal instruction. FCM was also used to standardize community-based models via concept mapping so that the perceived dynamics of the bushmeat trade could be compared across groups and also compared to policy assumptions. The study was largely exploratory and meant to inform conservation policies in the region with park managers and NGO partners.
The process of model-building was led by an independent local facilitator who lived in a nearby community. Nine workshops were held with 127 individuals over a two month period. Attendees at the workshop ranged from 9-27. Workshops lasted from 4-6 hours each. During workshops, the modeling activity began with introducing participants to the method with an unrelated example FCM. Participants then brainstormed about concepts that were related to zebra and wildebeest hunting and the relationships (either positive or negative) and degrees of influence (high, medium, or low) between the variables were defined. Identification of concepts was unstandardized (see Gray et al. 2014), with the exception of the three concepts of hunting, and wildebeest and zebra populations.
Participation in the project was advertised through a local NGO. Participants were domain experts who were nominated by a larger group of community residents. Participants were not paid for their participation–instead, the research team motivated participation by explaining that the effort was designed to capture and communicate the community perspective to protected area managers and NGOs in charge of conservation programs in the region. Stakeholders were enthusiastic about being able to articulate a model that was intended to inform future policies. Furthermore, because the modeling activity included no personal identifying information from any individual who participated, stakeholders freely provided information without fear of retribution for illegal hunting, which has been identified as an issue in household surveys used to collect data on bushmeat hunting (Nuno et al. 2013). After models from each group were collected, workshop participants discussed new bushmeat management policies (Gray et al. 2015), but the research team took ownership over the models to compare them for recurring concepts to be communicated to park officials, NGOs, and academic audiences in a peer-reviewed manuscript (see Nyaki et al. 2014 and Gray et al. 2015) and other reports but the information was not shared back with the stakeholders who constructed the model given funding and travel resource constraints.
Nine FCM-based models of the bushmeat trade were produced in the effort, one from each of the workshops held in the area. These models included, on average, 36 variables and 90 connections, and identified the drivers of the issue and the most central variables using network centrality metrics. In terms of social outputs, individuals that participated reported that they enjoyed the process, and the research team and park officials learned that the drivers and central variables involved in the bushmeat trade are far more complex than the assumptions that underlie current conservation policies in the region (see, for example, Figure 1). Locally relevant results indicated that cultural factors and confusing legal hunting policies contributed significantly to the bushmeat trade, in addition to known factors such as income generation and food security. Other conclusions more generally applicable to PM contexts included the finding that an anonymous knowledge sharing and modeling approach may generate more detailed data about illicit behaviors in sensitive conservation contexts such as the bushmeat trade.
Futher information can be found in:
Nyaki, A., Gray, S., Lepczyk, J. Skibins, D. Rentsch. 2014. Understanding the hidden drivers and local-scale dynamics of the bushmeat trade through participatory modeling Conservation Biology 28(5) 1403-1414.
Gray, S. A., S. Gray, J. L. De Kok, A. E. R. Helfgott, B. O’Dwyer, R. Jordan, and A. Nayki, 2015. Using fuzzy cognitive mapping as a participatory approach to analyze change, preferred states, and perceived resilience of social-ecological systems. Ecology and Society 20(2): 11
Model can be reconstructed with Mental Modeler: http://www.mentalmodeler.org/
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