Existing assessments of biomass supply and demand and their impacts face various types of limitations and uncertainties, partly due to the type of tools and methods applied (e.g., partial representation of sectors, lack of geographical details, and aggregated representation of technologies involved). Improved collaboration between existing modeling approaches may provide new, more comprehensive insights, especially into issues that involve multiple economic sectors, different temporal and spatial scales, or various impact categories. Model collaboration consists of aligning and harmonizing input data and scenarios, model comparison and/or model linkage. Improved collaboration between existing modeling approaches can help assess (i) the causes of differences and similarities in model output, which is important for interpreting the results for policy-making and (ii) the linkages, feedbacks, and trade-offs between different systems and impacts (e.g., economic and natural), which is key to a more comprehensive understanding of the impacts of biomass supply and demand. But, full consistency or integration in assumptions, structure, solution algorithms, dynamics and feedbacks can be difficult to achieve. And, if it is done, it frequently implies a trade-off in terms of resolution (spatial, temporal, and structural) and/or computation. Three key research areas are selected to illustrate how model collaboration can provide additional ways for tackling some of the shortcomings and uncertainties in the assessment of biomass supply and demand and their impacts. These research areas are livestock production, agricultural residues, and greenhouse gas emissions from land-use change. Describing how model collaboration might look like in these examples, we show how improved model collaboration can strengthen our ability to project biomass supply, demand, and impacts. This in turn can aid in improving the information for policy-makers and in taking better-informed decisions.

This paper presents results from comprehensive field surveys of jatropha projects in Mozambique, Tanzania and Mali in 2012. The article singles out the salient economic and social impact results and derives lessons. The results clearly demonstrate the weak business case for jatropha biofuel production at this time. Plantations were found to be unviable because of insurmountable up-front capital requirements in combination with slow and unreliable crop maturation, inefficient oil pressing owing to a lack of scale and experience, inadequate utilization of by-products, and competitively-priced fossil diesel and palm oil. For smallholders, jatropha only has limited value as a hedge crop in environmentally and economically disadvantaged areas. Better prospects have to wait for the advent of improved jatropha varieties. Social impacts from the perspective of project managers were rather mixed: overall, food security perceptions were positive and no massive forced human displacements were noted so far, though some disputes over land access and compensation were reported. Labor legislation was apparently respected on plantations, and positive gender effects, regional income/employment effects and better public facilities were also reported. The projects generated considerable employment, albeit mostly of a temporary nature, as lack of economic viability had caused many projects to close down again. When introducing next-generation biofuel projects, better OPEN ACCESS Sustainability 2014, 6 6204 monitoring by various actor groups is recommended, as well as long-term investment plans that include integral exit strategies.

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