PARENT SESSION
Poster Session 5: Climate Dynamics
Tuesday, August 9, 5:00 PM - 6:30 PM, Exhibit Hall 220 A-E, Level 2, Palais des congrès de Montréal
A meta-analysis of annual global terrestrial net primary productivity.
Ito, Akihiko1, 1 Frontier Research Center for Global Change-JAMSTEC, Yokohama, Kanagawa, Japan
ABSTRACT- Over 100 estimations of the present annual global terrestrial net primary productivity (NPP), one of the most important flows in the global biogeochemical carbon cycle, were collected from the literature and analyzed. These NPP estimations published during the period 1919 - 2005 span from 10 to 150 Pg C yr-1; they differ in approaches, basic data, models, and constraint conditions. Average NPP estimations since 1980 (70 studies, except values in the NPP-model intercomparison project in 1997, Potsdam) is 57.5 ± 7.5 Pg C yr-1 (mean ± SD). This value is not significantly different from the Potsdam result by 16 models, 54.9 ± 10.6 Pg C yr-1, supporting a conjecture that the difference in model parameterization is primarily responsible for the wide uncertainty in NPP estimation. Apparently, the 1st to 3rd assessment reports of the Intergovermental Panel of Climate Change have presented intermediate estimations of NPP, that is, 50 to 62 Pg C yr-1. The over 100 estimations were classified by approaches (inventory, remote sensing, empirical model, and mechanistic model), climate datasets, biome maps (if used), and state assumptions (static or transient), and compared by means of ANOVA. Although using spatially explicit information, estimations by remote sensing studies dispersed as widely as other relaxed approaches. Uncertainties due to employing different input datasets (biome, climate, and satellite signals) should be underscored. Also, interannual variability of NPP, prevailing environmental factors, and contribution by C4 species were summarized. Through the meta-analyses, requisites to reducing the uncertainties in our understanding of NPP, carbon cycle, and climate change are discussed.
Key words: Biosphere, Carbon cycle, Global change, Uncertainty