Bai, Yongfei

Campioli, Matteo

Chang, Jinfeng

Ciais, Philippe

Hauglustaine, Didier A.

Havlik, Petr

Herrero, Mario

Joiner, Joanna

Kosykh, Natalya

Mironycheva-Tokareva, Nina

Peng, Shushi

Peregon, Anna

Piao, Shilong

Soussana, Jean-Francois

Viovy, Nicolas

Wang, Tao

Wang, Xuhui

Yue, Chao

Zhang, Xianzhou

Abstract: Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5\ub0 by 0.5\ub0. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 19012012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, rising\u202fCO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1\u202f\u2009
7\u2009\u202f106\u202fkm2 in 1901 to 12.3\u202f\u2009
7\u2009\u202f106\u202fkm2 in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and interannual variability of grassland productivity at global scale well and thus is appropriate for global applications presented here

Institutional Repository Universiteit Antwerpen

Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management

Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management

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Institutional Repository Universiteit Antwerpen