Data collection will enable us to set the base and to see a general socio-economic picture of the area, what ecosystem services are existent on the area and how the local populations perceive them and value them. To achieve this, we carry out a statistical data analysis on basic socio-economic attributes like population, employment and key incomes. We conduct several field surveys and interviews of key stakeholders and we organise participatory workshops.
Data collection includes:
- Statistical data collection and analysis on the three regions and also on some selected settlements analysing population, area, population density, male/female ration, urban/rural ration, age structure in terms of population. Regarding economy, livestock, crops, agriculture related employment and average salary in agriculture as well as additional GDP and sectorial analysis. Besides, education data are also collected along with transport and infrastructure.
- Setting up a Stakeholder Advisory Board where the key stakeholders are brought together to help understanding key ecosystem services. The establishment of the SAB will be preceded by a detailed stakeholder analysis.
- Conducting various field surveys will be carried out in two stages by questionnaires to evaluate economic preferences of the population. The first stage of field work will create opportunity to identify the most relevant ecosystem services, while the second stage will create opportunity to gather specific local data through targeted interviews regarding indicators of those ESs.< /li>
- Organising participatory scenario workshops to develop potential future land use models (scenarios) with the involvement of local stakeholders. Based on the outcome, two participatory scenario and land-use planning workshops will be held at two contrastive settlements. The scenarios will focus on identifying the expected impact of future change on the economic sectors most dependent on ecosystem services (agriculture, forestry, tourism).
- Organising participatory expert workshops to verify the collected data. Expert opinions on the relationships between services and different influencing factors will be mapped and cast into a conceptual model using the QuickScan toolset.