Vietnam's forest transition in retrospect: demonstrating weaknesses in business-as-usual scenarios for REDD.

One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.

Assessing the role of learning devices and geovisualisation tools for collective action in natural resource management: Experiences from Vietnam.

In northern Vietnam uplands the successive policy reforms that accompanied agricultural decollectivisation triggered very rapid changes in land use in the 1990s. From a centralized system of natural resource management, a multitude of individual strategies emerged which contributed to new production interactions among farming households, changes in landscape structures, and conflicting strategies among local stakeholders. Within this context of agrarian transition, learning devices can help local communities to collectively design their own course of action towards sustainable natural resource management. This paper presents a collaborative approach combining a number of participatory methods and geovisualisation tools (e.g., spatially explicit multi-agent models and role-playing games) with the shared goal to analyse and represent the interactions between: (i) decision-making processes by individual farmers based on the resource profiles of their farms; (ii) the institutions which regulate resource access and usage; and (iii) the biophysical and socioeconomic environment. This methodological pathway is illustrated by a case study in Bac Kan Province where it successfully led to a communication platform on natural resource management. In a context of rapid socioeconomic changes, learning devices and geovisualisation tools helped embed the participatory approach within a process of community development. The combination of different tools, each with its own advantages and constraints, proved highly relevant for supporting collective natural resource management.