Integrated Biosphere Management Modeling (iBIOM)ΒΆ

Adequate policy assessment tools will be pivotal to tackle contemporary challenges and assess the impacts of alternative policies towards the achievement of sustainable development goals, by informing policy makers and other stakeholders on long-term policy analyses. This task demands a comprehensive coverage of the ecological-economic systems affecting SDGs and the consideration of the relevant drivers and levers to bring these systems to a safe and just operating space.

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The Integrated Biosphere Management Modeling (iBIOM) is an innovative modelling framework grounded on a nexus approach, designed to integrate multiple sectors, including land use, water and biodiversity, in a cohesive manner. Thereby iBIOM enables a complete analysis of the impacts and interactions within and across sectors in response to biophysical drivers, policies and adaptation alternatives.

iBIOM leverages on a fully-fledged suite of models developed by the BNR program at IIASA. This includes detailed biophysical models able to incorporate the effects of climate and management on agriculture (EPIC), forestry (G4M) and wildfires (FLAM). The biophysical information from this modelling toolbox grounds the productivity estimates employed in the economic land use toolbox composed by the forest management model G4Mm and the economic land use model GLOBIOM. The interface between the two models is mediated via the land use and land cover downscaling model (DownscalR). The latter routine also roots the connection between the land use and the water and biodiversity sectors, where the former provides estimates of water availability and quality to the land use decisions and the latter describes the implications of these decisions to biosphere integrity.

The iBIOM initiative at IIASA serves to integrate models of the Biodiversity and Natural Resources (BNR) research program into a cohesive framework. It leverages the joint hosting of model code, data, runtimes, and services on accessible infrastructure, thereby enabling:

  • Interfacing and data exchange between models.

  • Collaboration on model harmonization and the development of links between models.

  • Knowledge sharing and consolidation.

  • Public access and community building.