In BGC-MAN, daily weather data and site information are needed to calculate the cycles of carbon, nitrogen, water and energy within a given ecosystem. Up to 50 parameters describe the ecophysiology, phenology, growth and allocation structure, as well as intrinsic and externally driven biomass mortality of: (i) single species, (ii) assemblies of species, (iii) plant traits, (iv) plant functional types or (v) biomes. Distinct parameter sets exist for the major species of temporal and boreal forests, temperate and boreal grasslands, as well as for distinct tropical forest ecosystems, tropical savannahs and tropical woodlands.
Differences to other dynamic vegetation models
One of the main advantages of BGC-MAN is the explicit consideration of management and land use, as well as land use change impacts on the biogeochemistry of a given parcel of land.
BGC-MAN differs from other Dynamic Global Vegetation Models by parameter flexibility: parameters are not fixed but may change in response to management interventions, natural disturbances or changes in environmental conditions. As such, it resembles one of the first NGVMs (Next Generation Vegetation Models), by explicitly including the flexible response of plants to changes in growth conditions.
Development of the model started over 15 years ago based on Biome-BGC version 4.2, kindly provided by Peter E. Thornton from the Climate Change Science Institute at Oak Ridge National Laboratory in the USA. Model changes and improvements started at BOKU University of Natural Sciences and Life Sciences, Austria, and continued at IIASA, where it became part of the IIASA modelling framework.
Interaction with the IIASA modeling cluster
BGC-MAN provides estimates on productivity, carbon sequestration, livestock feed and fodder potential, coarse woody debris and litter stocks, etc. to the IIASA/ ESM GLOBIOM-EPIC-G4M-FLAM modelling cluster. In addition, BGC-MAN provides estimates of the stability and resilience of a given management type or land use form under current and changing environmental conditions.
Last edited: 26 August 2016
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Pietsch S, Bednar JE, Mosnier A, & Obersteiner M (2015). Probabilistic Spatial and Temporal Resilience Landscapes for the Congo Basin. In: Systems Analysis 2015 - A Conference in Celebration of Howard Raiffa, 11 -13 November, 2015, Laxenburg, Austria.
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