PARENT SESSION
Contributed Oral Session 124: Grassland Ecology: Water Relations; Growth
Thursday, August 11, 8:00 AM - 11:30 AM, Meeting Room 518 C, Level 5, Palais des congrès de Montréal

Spatial and temporal variabilities in biomass allocation in grassland ecosystems: A synthesis of experimental field data.

Hui, Dafeng^*,1, Jackson, Robert^{1, 2}, ¹ Department of Biology, Durham, NC, USA² Nicholas School of the Environment and Earth Sciences, Durham, NC, USA

ABSTRACT- Biomass allocation is an important variable in plant growth and terrestrial ecosystem carbon modeling. However, spatial and temporal variabilities in the fraction of below-ground net primary productivity (BNPP) to total NPP (f_BNPP) and its relationship with climatic variables have not been explored. We addressed these issues by synthesizing 98 site-year field biomass data at 12 grassland sites from a global NPP database and literature. Results showed that f_BNPP varied from 0.40 to 0.86 across 12 sites. In general, savannas and humid savannas had generally smaller f_BNPP but larger interannual variability in f_BNPP, while cold steppe ecosystems had larger f_BNPP and median interannual variability. The observed interannual variabilities in f_BNPP could be attributed to interannual variabilities in both BNPP and above-ground NPP, as well as the interannual variability in mean annual precipitation (MAP). Spatial variability in f_BNPP was relatively larger than interannual variability within sites. While f_BNPP decreased with mean annual temperature (MAT) and MAP across sites, different temporal responses of f_BNPP with MAT and MAP were found within each site. The divergent responses at spatial and temporal scales reflected different mechanistic controls on f_BNPP variation: increased vegetation contributions at the spatial scale and greater environmental controls at the temporal scale. To estimate carbon sequestration and cycling accurately in terrestrial ecosystems, both the spatial variability in f_BNPP and the site-specific responses of f_BNPP with climatic variables should be considered in global carbon modeling.

Key words: biomass allocation, climate, grassland, meta-data synthesis