Global bioenergy scenarios - future forest development, land-use implications, and trade-offs - Kraxner, Florian; Nordstrom, E.M.; Havlík, Petr; Gusti, Mykola; Mosnier, Aline; Frank, S.; Valin, Hugo; Fritz, Steffen; Fuss, S.; Kindermann, Georg; McCallum, Ian; Khabarov, N.; et al. (Elsevier, 2013)
Preservation of biodiversity and reduction of deforestation are considered as key elements when addressing an increased use of bioenergy in the future. This paper presents different combinations of scenarios for global feedstock supply for the production of bioenergy under specified social and environmental safeguard provisions. The objectives of this study were threefold: a) to present a global perspective using an integrated modeling approach; b) to frame the boundaries for lower scale assessments; and c) to identify potential trade-offs to be considered in future research. The aggregate results, achieved through the application of an integrated global modeling cluster, indicate that under a high global demand for bioenergy by mid-century, biomass will to a large extent be sourced from the conversion of unmanaged forest into managed forest, from new fast-growing short-rotation plantations, intensification, and optimization of land use. Depending on the underlying scenario, zero net deforestation by 2020 could be reached and maintained with only a minor conversion of managed forests into other land cover types. Results further indicate that with rising populations and projected consumption levels, there will not be enough land to simultaneously conserve natural areas completely, halt forest loss, and switch to 100% renewable energy. Especially in the tropical regions of the southern hemisphere, it will be important to achieve a controlled conversion from unmanaged to sustainably managed forest as well as increased protection of areas for ecosystems services such as biodiversity. The study concludes with the recommendation to focus on targeted regional policy design and its implementation based on integrated global assessment modeling.