The debate about Sustainable Development Goals reveals the difficulty of simultaneously addressing social and economic development challenges and the degradation of Earth’s life support systems.
Land systems in the humid tropics illustrate these challenges prominently: Local people’s land use strategies are facing competition from large-scale land acquisition, logging etc., but also biodiversity conservation.
Remote decision-makers reshape flows of ecosystem services to their benefit, whereas the consequences hardly reach them. Land change scientists have conceptualized this phenomenon under the term “telecoupling”. Our research project pursued the overall goal of devising and testing innovative strategies and institutional arrangements for securing ecosystem service flows and human well-being in and between telecoupled landscapes at study sites in Laos, Myanmar, and Madagascar.
Research
Research activities took place in three Work Packages (WP) and were implemented in the three study countries Laos, Madagascar, and Myanmar with the aim to obtain comparable results.
WP 1: Analysing social-ecological systems (SES) under telecoupling
The first work package led by CDE, University of Bern, analysed how telecoupling influences decisions on land use, and how these in turn modify the flows of ecosystem services and their impact on human well-being. For this purpose, the researchers identified the actors involved and studied their relational patterns by means of social network analysis (SNA). They expanded existing SNA, firstly, by integrating actors’ attributes such as categories of well-being, their demands for ecosystem services, and their agency and, secondly, by tying actor networks to discrete geographical locations.
WP 2: Participatory modelling for learning, prediction, and decision-making
The second work package, under the guidance of the Swiss Federal Institute of Technology in Zurich (ETHZ), developed a generic Bayesian network model, which was parameterized through participatory stakeholder interaction and result in a 3D collaborative virtual platform for understanding land use decision-making. In order to design cross-scale institutional arrangements, the Bayesian networks (BN) are suitable for modelling open, participatory processes that can incorporate several levels of information sophistication. This allows to convert land use decision models into user-oriented tools for negotiating trade-offs across multiple value systems.
WP 3: Social learning and adaptive governance
The third work package led by the University of Antananarivo translated insights of WP1 and WP2 into concrete innovations using a structured multi-stakeholder learning process. Moreover, it examined how interactions with distant stakeholders under telecoupling can be enabled to facilitate social learning and to what extent these learning processes effectively lead to adaptive decision-making and innovative governance schemes.
Study regions
