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A historical meta‐analysis of global terrestrial net primary productivity: are estimates converging?
Author(s) -
ITO AKIHIKO
Publication year - 2011
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/j.1365-2486.2011.02450.x
Subject(s) - primary production , biogeochemical cycle , environmental science , context (archaeology) , carbon cycle , productivity , vegetation (pathology) , global change , ecosystem , terrestrial ecosystem , physical geography , climatology , climate change , ecology , geography , medicine , macroeconomics , archaeology , pathology , geology , economics , biology
Net primary productivity (NPP) is one of the most important ecosystem parameters, representing vegetation activity, biogeochemical cycling, and ecosystem services. To assess how well the scientific community understands the biospheric function, a historical meta‐analysis was conducted. By surveying the literature from 1862 to 2011, I extracted 251 estimates of total terrestrial NPP at the present time (NPP T ) and calculated their statistical metrics. For all the data, the mean±standard deviation and median were 56.2±14.3 and 56.4 Pg C yr –1 , respectively. Even for estimates published after 2000, a substantial level of uncertainty (coefficient of variation by ±15%) was inevitable. The estimates were categorized on the basis of methodology (i.e., inventory analysis, empirical model, biogeochemical model, dynamic global vegetation model, and remote sensing) to examine the consistency among the statistical metrics of each category. Chronological analysis revealed that the present NPP T estimates were directed by extensive field surveys in the 1960s and 1970s (e.g., the International Biological Programme). A wide range of uncertainty remains in modern estimates based on advanced biogeochemical and dynamic vegetation models and remote‐sensing techniques. Several critical factors accounting for the estimation uncertainty are discussed. Ancillary analyses were performed to derive additional ecological and human‐related parameters related to NPP. For example, interannual variability, carbon‐use efficiency (a ratio of NPP to gross photosynthesis), human appropriation, and preindustrial NPP T were assessed. Finally, I discuss the importance of improving NPP T estimates in the context of current global change studies and integrated carbon cycle research.