Belowground Carbon Flux and Partitioning: Global Patterns and Response to Temperature

The fraction of gross primary production (GPP) that is total belowground carbon flux (TBCF) and the fraction of TBCF that is belowground net primary production (BNPP) represent globally significant C fluxes that are fundamental in regulating ecosystem C balance. However, global estimates of the partitioning of GPP to TBCF and of TBCF to BNPP, as well as the absolute size of these fluxes, remain highly uncertain. Efforts to model belowground processes are hindered by methodological difficulties for estimating belowground C cycling, the complexity of belowground interactions, and an incomplete understanding of the response of GPP, TBCF and BNPP to climate change. Due to a paucity of available data, many terrestrial ecosystem models and ecosystem-level studies of whole stand C use efficiency rely on assumptions that: 1) C allocation patterns across large geographic, climatic, and taxonomic scales are fixed; and 2) ~50% of TBCF is BNPP. Here, we examine available information on GPP, TBCF, BNPP, TBCF:GPP, and BNPP:TBCF from a diverse global database of forest ecosystems to understand patterns in belowground C flux and partitioning, and their response to mean annual temperature (MAT). GPP, TBCF and BNPP all increased linearly across the global scale range of MAT. TBCF:GPP increased significantly with MAT for temperate and tropical ecosystems (>5°C), but variability was high across the dataset. BNPP:TBCF varied from 0.26 to 0.53 across the entire MAT gradient (-5 to 30°C), with a much narrower range of 0.42 to 0.53 for temperate and tropical ecosystems (5 to 30°C). Variability in the datasets was moderate and clear exceptions to the general patterns exist that likely relate to other factors important for determining belowground carbon flux and partitioning, in particular water availability and nutrient supply. Still, our results highlight global patterns in belowground C flux and partitioning in forests in response to MAT that in part confirm previously held assumptions.