Biophysical modeling is the simulation of biological systems using mathematical formalizations of the physical properties of the systems. Such models are used to predict and project the influence of biological and physical factors on complex systems and form the basis for any detailed spatially explicit and integrated land use modeling at all scales. Forest and agricultural ecosystems represent a large majority of global land use and hence need particular attention by science which traditionally has been addressed by IIASA’s Ecosystem Services and Management Program (ESM). Over more than a decade, three back-bone models have been developed: a biophysical Global Forestry Model (G4M), a process-based global agricultural model (EPIC), and a techno-economic engineering model for the assessment of renewable energy systems (BeWhere) which is relying to a large extent on information provided by the other two models. ESM’s Center for Landscape Resilience & Management (CLR) is developing and applying this suit of models in a stand-alone or linked cluster to improve risk-resilient and sustainable management of land-based ecosystems by generating impact through policy-relevant research at multiple geographic scales. The center focuses on land-use by forestry, agriculture, the renewable energy sector and the management of other natural ecosystems at landscape level while expanding the
Employing bioenergy with carbon capture and storage (BECCS), would not only retain 40,000 jobs currently held as part of the US coal industry but would create 22,000 new jobs in the forestry and transportation sectors by the middle of this century, according to new IIASA-led research. More
Researchers, scientists and experts from both sides will participate in the joint research project. IIASA will contribute its expertise on modelling while ITB makes their research Indonesia-specific. More
A new report from researchers from IIASA, Luleå University of Technology (LTU), and RISE Research Institutes of Sweden has shown that more biorefineries, which produce biobased fuels and chemicals, will have only a small effect on the availability and pricing of wood products and feedstocks. More
Two years after hosting the kick-off workshop of the RESTORE+ project in April 2017 at IIASA, the RESTORE+ consortium me... More
A high level delegation from the Indonesian Ministry of National Development Planning (Bappenas), will visit IIASA on 19... More
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Last edited: 19 February 2019
CLR at a glance
Xylia M, Leduc S, Laurent A-B, Patrizio P, van der Meer Y, Kraxner F, & Silveira S (2019). Impact of bus electrification on carbon emissions: the case of Stockholm. Journal of Cleaner Production 209: 74-87. DOI:10.1016/j.jclepro.2018.10.085.
Folberth C, Baklanov A, Balkovic J, Skalsky R, Khabarov N, & Obersteiner M (2019). Spatio-temporal downscaling of gridded crop model yield estimates based on machine learning. Agricultural and Forest Meteorology 264: 1-15. DOI:10.1016/j.agrformet.2018.09.021.
Patrizio P, Leduc S, Kraxner F, Fuß S, Kindermann G ORCID: https://orcid.org/0000-0003-4297-1318, Mesfun S ORCID: https://orcid.org/0000-0002-4909-6643, Spokas K, Mendoza Ponce A, et al. (2018). Reducing US coal emissions can boost employment. Joule 2 (12): 2633-2648. DOI:10.1016/j.joule.2018.10.004.
Mesfun S ORCID: https://orcid.org/0000-0002-4909-6643, Leduc S, Patrizio P, Wetterlund E, Mendoza Ponce A, Lammens T, Staritsky I, Elbersen B, et al. (2018). Spatio-temporal assessment of integrating intermittent electricity in the EU and Western Balkans power sector under ambitious CO2 emission policies. Energy 164: 676-693. DOI:10.1016/j.energy.2018.09.034.
Mendoza Ponce A, Corona-Núñez RO, Galicia L, & Kraxner F (2018). Identifying hotspots of land use cover change under socioeconomic and climate change scenarios in Mexico. Ambio DOI:10.1007/s13280-018-1085-0. (In Press)
Bruckman V, Haruthaithanasan M, Miller R, Terada T, Brenner A-K, Kraxner F, & Flaspohler D (2018). Sustainable Forest Bioenergy Development Strategies in Indochina: Collaborative Effort to Establish Regional Policies. Forests 9 (4): e223. DOI:10.3390/f9040223.
International Institute for Applied Systems Analysis (IIASA)
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