Analysing Changes in Climate and Forestry Policy Networks Over Time: Evidence from the Global South

This paper investigates changes in climate change policy networks around forest mitigation in the Global South. Programmes on Reducing Deforestation and forest Degradation (REDD+) has been active for around a decade now, focusing of developing governance structures, various policies and implementing pilot projects in several host countries. National REDD+ policy arenas are characterized by complex, multi-actor, multi-sector interactions that evolve over time. Multi-actor policy networks integrate societal actors beyond the state aiming at influencing ongoing REDD+ policy processes and outcomes. These policy domains include diverse interests around climate and forests. Whose interests dominate and are reflected in the outcomes depends largely on the level of influence of policy actors in decision making processes. In policy networks, power takes different forms, including relational forms of power expressed through different patterns of interaction (e.g. the exchange of information, collaboration, exchanges of material resources, and the formation of coalitions) (Carrington et al. 2005). This study utilize a comparative design to investigate how REDD+ national policy networks have evolved over time. The paper compares policy network structures across countries to assess how power structures have enabled or hindered policy change. It is based on a longitudinal analysis of networking data (Leifeld and Cranmer 2015, Desmarias & Cranmer 2017) on communication, collaboration and resource exchanges collected in 2012 and 2016 in Brazil, Indonesia and Vietnam. Carrington, P.J., Scott, J., Wasserman, S. (2005) Models and methods in social network analysis. Cambridge university press. Desmarais, B.A., Cranmer, S.J. (2017) Statistical Inference in Political Networks Research. The Oxford Handbook of Political Networks, 203. Leifeld, P., Cranmer, S.J. (2015) A theoretical and empirical comparison of the temporal exponential random graph model and the stochastic actor-oriented model. arXiv preprint arXiv:1506.06696.