Social network analysis of sustainable forest management actors in Zagros Region

In natural resource management, different stakeholders and actors can be involved as major components. These can include the social network of users benefiting from natural resources. Therefore, the need for an evaluation of the human community that comes into relation with natural resources and social relations is inevitable. The present study aimed to portray current scopes of management in the Zagros forests based on social monitoring and estimations of relationships between local actors. The research uses a method of social network analysis as an efficient tool for evaluating these relationships. Links were found between information exchange and participation in the social network of local actors, and, accordingly, the quantitative and mathematical indicators of network analysis were evaluated among all actors in the Zagros forests. The level of cohesion and social capital in the social network of local stakeholders in this region were estimated as “weak” to “moderate,” and the sustainability of the network was “moderate.” Based on the Quadratic Assignment Procedure (QAP index), a high coefficient was obtained in describing the level of correlation between the two networks of information exchange and participation among the actors in the region. The results can be used in line with principled policies in managing forest resources of the Zagros region for planning, decision-making, and sustainability. Based on the results, there is potential for an increase in social control in the target groups and adherence to local traditions in the sustainable management of forest resources among actors. This can be achieved by strengthening social trust. The scientific contribution of this research mainly fills gaps in the current knowledge of Iran’s administrative bodies which are responsible for sending and receiving information about forest management. The focus is largely descriptive and each organization is given attributes to its values of in-degree and out-degree centrality.