The aim of developing joint guidelines and working group for sustainable nature tourism is to protect natural diversity while allowing for recreational use of the protected areas. The Finnish coordinator began by collecting two sets of principles regarding sustainable nature tourism in Norway and Finland, i.e. the principles of Metsähallitus (Agency responsible for managing most protected areas in Finland) and the Sustainable Model of Arctic Regional Tourism (SMART). Joint guidelines combining these sets of principles were prepared, which incorporated input from entrepreneurs, nature tourism working group and the project Steering Committee. The guidelines were added to the Action Plan for nature protection and sustainable nature tourism in Pasvik-Inari Area, and they were published on the project web page.

One aim of joint nature-focused research and monitoring (years 2007, 2011 and 2015) was to harmonize contrasting national methods. Harmonised methodology facilitates data exchange, management, and interpretation to inform park management strategies to protect these populations. The target species/groups included those that are of management concern in the parks: brown bear, Golden Eagle, waterfowl, butterflies, and ants. Brown bear is highlighted here as an important example. Bears affect livelihoods of reindeer herders, which are important stakeholders in the Pasvik-Inari area. Bears are hunted in all the three countries, and estimated bear population size is used when determining numbers of hunting licenses. Modern DNA-sampling methodologies give the best estimate of the number of bears in the cross-border bear population. Hair was collected for DNA-analysis using hair snagging stations scattered around the area. In addition, local residents, in particular hunters and co-workers in the field were encouraged to collect fecal samples. Results can be compared between years, as identical methodology is being used throughout.

Invasive plants occurred on both sides of the Thaya River, which serves as the international boundary and the border between the two national parks. Plants were removed from both sides of the river by staff from the respective parks, and removal of plants took place following their detection by the monitoring effort. When the joint eradication project was originally proposed by Podyjí National Park, staff of Thayatal National Park were sceptical of the efficiency of the efforts to remove the invasive plant based on their knowledge of many unsuccessful eradication attempts in other areas. Thayatal National Park was therefore only willing to invest a small amount of resources initially to test whether the eradication efforts would work. After initial successes, Thayatal National Park contributed resources to conduct more substantial removal measures jointly with Podyjí National Park. As both parks are opposed to the use of pesticides, individual plants needed to be removed by hand and preferably during the adolescent life stages before seeds emerged. Otherwise, seeds could be spread during removal of the adult plants. Nevertheless, mowing measures proved very effective in places of larger stocks.  

The two national park directors met 4-5 times per year to discuss among other issues the status of the invasive plant monitoring and removal. Jointly, they allowed the project to be funded and enabled the necessary actions. Furthermore, other staff from both parks met each other whenever needed to share information regarding the monitoring and removal efforts.

Podyjí National Park took sole responsibility for monitoring the river valley for infestations of the Himalayan Balsam and other invasive plants. The National Park staff used a boat to monitor the occurrence of the plant along the river banks, especially in areas that are hard to reach overland. Today, staff from Thayatal National Park is also part of the boat crew, and monitoring from the river is conducted once a year. The measures to eliminate invasive species are implemented several times during the year (2 to 6 times). The Himalayan Balsam occurs on both sides of the border, but Podyji National Park has greater capacity in implementing the measures. The participation on monitoring and management has thus been divided in accordance of capabilities of both national parks.

The first step is to form a core team composed of two structured-decision-making (SDM) coaches with skills in decision analysis and workshop facilitation along with one authority representing each protected area in the transboundary region. In consultation with park directors, one primary contact person is identified as having the necessary knowledge and time availability to participate in the entire decision process. The core team then holds a series of conference calls or meetings to identify a joint transboundary management question. Between calls, the core team reviews any available management plans from the two respective protected areas and a guidance document on transboundary cooperation between the parks to identify shared management topics. The core team then formulates a concise 1-sentence transboundary conservation question, which summarizes the focal decision, associated objectives, and time-horizon: “Over the next 10 years, how can the managers of Triglav National Park and Julian Prealps Nature Park allocate their resources to best satisfy all stakeholders concerned about brown bears in the Julian Alps?”

The first step is to identify stakeholder groups that should be considered when addressing the transboundary management question, including but not limited to the protected area staffs themselves. Six stakeholder groups were identified: nature conservation, agriculture, forestry, tourism, research, and local communities and municipalities. The core team then identifies up to 8 stakeholder representatives to include in the decision-analytic process. Each participating park authority then independently identifies 2-5 concerns and/or wishes from the perspective of each stakeholder group. Next, each core team converts the wishes and concerns into statements of objectives, and ultimate objectives are then distinguished from intermediate objectives that are only means to achieve ultimate objectives. A reduced set of three ultimate, quantifiable objectives are then identified to represent the main trade-offs and concerns across stakeholder groups while serving as measures of success for the focal transboundary conservation efforts. Focusing on a smaller number of ultimate objectives ensures feasibility and understandability for conducting the participatory decision analysis.

Working with the coaches, the park authorities identify a list of factors that have strong potential influence on the ultimate objectives and that are at least partly beyond the control of park staff. They then narrow down the external factors to a focal set that has a high degree uncertainty about their magnitude and effects on the ultimate objectives. Next, park authorities develop two alternative scenarios representing possible future trajectories for the external factors. A status quo scenario assumes that system dynamics (i.e., external factors along with their impacts and effectiveness of management activities for achieving objectives) will follow the most likely future trajectory. An optimistic scenario assumes that system dynamics are more favorable than expected for achieving the objectives. To keep the participatory decision analysis feasible, additional scenarios (e.g., pessimistic) may be documented for future analyses. After listing possible management activities, park authorities independently assign a percent allocation toward each activity in a way they believe will most likely achieve the objectives under each scenario for external factors.

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.