Through workshops and conference calls, the core team develops a concise influence diagram that represents the key hypothesized relationships between the possible actions, external factors, and ultimate objectives. The coaches use this diagram as a conceptual basis when developing a Bayesian decision network, which allows for assigning stakeholder values and probabilities within the influence diagram. The Bayesian decision network therefore provides a visualization of the quantitative decision model. Within another workshop setting that includes the 8 representative stakeholders and up to 2 experts, the coaches ask each participant to individually provide numerical inputs for the model. There are two types of questions for the elicitation on a scale from 0 to 100%: 1) percent chance that a given external factor or ultimate objective will follow a particular trajectory while accounting other external factors and allocation options; 2) percent satisfaction with each possible combination of outcomes for the three ultimate objectives. During a following discussion, stakeholders agree on set of predictions and satisfaction scores to represent the averages among participants in the decision analysis.

The recommended allocation option is defined as the one with the greater expected stakeholder satisfaction, which is calculated based on inputs and structure of the Bayesian decision network. Recognizing uncertainties about elicited predictions and satisfaction levels, analysts conduct a sensitivity analysis explore whether the recommended allocation changes depending on the set of inputs used for the analysis. In particular, they run the analysis twice: once using the averaged inputs and then a second time based only the input (from the individual) for each variable that is most favorable for the opposing allocation option (i.e., the option with the lower expected satisfaction under the averaged inputs). If the recommendation changes following the second model run, then the analysts use results from both model runs to calculate the expected value of perfect information. This calculation represents the expected percent increase in satisfaction if the uncertainties about the variables and relationships in the model are fully resolved through further research. This provides a way to check the robustness of the recommended allocation to uncertainty and can lead to recommendations for further research to improve decision-making.

Many of the Fin Fighters are non-scientists and do not have backgrounds in biology or conservation. We have therefore created a system of collaboration with scientists to produce a tangible and reasoned method of generating action for species conservation. We established a committee of shark scientists to share skills and bring new technology to shark conservation, and specifically to the Moroccan studies. Working with scientists to collect data for their studies as well as for our own reports, ensures a circular needs based relationship: Scientists come to us with data requirements, we fill these by collecting data, which is then used in their scientific research, and the results are made available for Fin Fighters to use in pushing practical conservation or working to implement enforcement/policy. In this way we are all working collectively to ensure our needs are met and any papers published credit Fin Fighters as an institution for data collection, which adds to our credibility.

During the planning phase extensive formative research informs the Social Marketing, as well as the Technical Assistance components of a campaign. Research sets the baselines that allow the assessment of social and conservation impacts following a campaign. Qualitative research (e.g. focus groups, observation, in-depth interviews) is geared towards understanding target audience opinions, feelings, concerns and perceived benefits of current as well as desired management practices. Qualitative research is about creating a casual conversation with and between participants to establish a comfortable relationship, and to reveal underlying information unobtainable through quantitative research. Quantitative research surveys capture specific answers to specific questions to describe demography, identify media preferences, and assess the current state of knowledge, attitude, communication and readiness of target audiences regarding a certain behavior change. Both components ultimately inform campaign decisions like objectives, respective activities, materials, and messages for both Social Marketing and Technical Assistance.

The results of the project have been shared with Belize’s Ministry of Forest, Fisheries and Sustainable Development (including Coastal Zone Management Authority and Institute and National Climate Change Office) and the Ministry of Tourism to facilitate replication, and uptake of the process and recommendations. The results have also been shared with local communities, local NGOs, land developers and the private tourism sector to build capacity, awareness and implementation of greener landscape practices within the coastal zone.

From the beginning of creation of the ICCA, the local community engaged in the monitoring of quality and quantity of fish catch, socio-economic change and ecosystem health.

Unlike Social Marketing, the Technical Assistance (TA) is based on more personal interactions with the fishers at the fishing group level (cooperatives or associations) or at the individual fisher level. This allows the issues to be addressed with more detail and depth, although larger groups of people are not reached. The overarching goal is to promote fishers´ support for conservation actions (e.g., creation of FRZ, adoption of sustainable fishing practices). Technical assistance tools are targeted towards building capacity in coastal communities and removing technical barriers, emphasizing leadership among fishers to improve the management of fisheries resources. Examples of technical assistance activities include one-on-one conversations, fishing trips, fisher exchanges among sites, formal training in specific fishing methods through workshops and courses, informal training, meetings with the authorities, follow-up with administrative and legal processes (e.g., fishing concession/permit renewal) and providing organizational materials (e.g., file cabinets, blackboards, etc.).

Alternative adaptation options were analyzed via the Marine InVest tool to identify costs and benefits of these approaches. Costs were incorporated directly into the scenarios and InVEST. This included the costs of implementation of adaptation options combined with any associated costs to ecosystem services quantified by our models, and benefits represented by the positive return in ecosystem service values quantified by our models. Local experts helped in reviewing the selected ecosystem services and adaptation options. A technical report was developed on the activities.

We carefully prepared our maps and other data and then wrote a supporting letter to one of the organizers of the IUCN CBD EBSA meeting in Moscow in March 2013. After some back and forth, we managed to get a formal invitation and to raise the funds to send researcher Mikhail Nagaylik. He attended and submitted a strong case for a large EBSA covering most of the east coast of Kamchatka. This EBSA was accepted and supported both by the scientists as well as the Ministry in Moscow.

The Fishermen Association of the Rural Municipality of Mangagoulack (Casamance, Senegal) was informed that— following international CBD decisions and IUCN recommendations— Senegal was promoting and respecting locally established “community conserved areas”. The association thus mobilized the community to create Kawawana ¬ (“our local heritage to be preserved by us all”) in its ancien estuarine territory. In Kawawana, the ancient governance and management rules– renovated and agreed upon also by the municipal and regional governments – are finally again respected.