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- Luo, Y. -W, et al.
(författare)
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Database of diazotrophs in global ocean : abundance, biomass and nitrogen fixation rates
- 2012
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Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3508 .- 1866-3516. ; 4:1, s. 47-73
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Tidskriftsartikel (refereegranskat)abstract
- Marine N-2 fixing microorganisms, termed di-azotrophs, are a key functional group in marine pelagic ecosystems. The biological fixation of dinitrogen ( N-2) to bioavailable nitrogen provides an important new source of nitrogen for pelagic marine ecosystems and influences primary productivity and organic matter export to the deep ocean. As one of a series of efforts to collect biomass and rates specific to different phytoplankton functional groups, we have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling about 12 000 direct field measurements of cyanobacterial diazotroph abundances (based on microscopic cell counts or qPCR assays targeting the nifH genes) and N-2 fixation rates. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. The database is limited spatially, lacking large regions of the ocean especially in the Indian Ocean. The data are approximately log-normal distributed, and large variances exist in most sub-databases with non-zero values differing 5 to 8 orders of magnitude. Reporting the geometric mean and the range of one geometric standard error below and above the geometric mean, the pelagic N-2 fixation rate in the global ocean is estimated to be 62 (52-73) Tg Nyr(-1) and the pelagic diazotrophic biomass in the global ocean is estimated to be 2.1 (1.4-3.1) Tg C from cell counts and to 89 (43-150) Tg C from nifH- based abundances. Reporting the arithmetic mean and one standard error instead, these three global estimates are 140 +/- 9.2 Tg Nyr(-1), 18 +/- 1.8 Tg C and 590 +/- 70 Tg C, respectively. Uncertainties related to biomass conversion factors can change the estimate of geometric mean pelagic diazotrophic biomass in the global ocean by about +/- 70 %. It was recently established that the most commonly applied method used to measure N-2 fixation has underestimated the true rates. As a result, one can expect that future rate measurements will shift the mean N-2 fixation rate upward and may result in significantly higher estimates for the global N-2 fixation. The evolving database can nevertheless be used to study spatial and temporal distributions and variations of marine N-2 fixation, to validate geochemical estimates and to parameterize and validate biogeochemical models, keeping in mind that future rate measurements may rise in the future.
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| 2. |
- Jethava, Vinay, 1982, et al.
(författare)
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Scalable multi-dimensional user intent identification using tree structured distributions
- 2011
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Ingår i: SIGIR'11 - Proceedings of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval. - New York, NY, USA : ACM. - 9781450309349 ; , s. 395-404
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Konferensbidrag (refereegranskat)abstract
- The problem of identifying user intent has received considerable attention in recent years, particularly in the context of improving the search experience via query contextualization. Intent can be characterized by multiple dimensions, which are often not observed from query words alone. Accurate identification of Intent from query words remains a challenging problem primarily because it is extremely difficult to discover these dimensions. The problem is often significantly compounded due to lack of representative training sample. We present a generic, extensible framework for learning the multi-dimensional representation of user intent from the query words. The approach models the latent relationships between facets using tree structured distribution which leads to an efficient and convergent algorithm, FastQ, for identifying the multi-faceted intent of users based on just the query words. We also incorporated WordNet to extend the system capabilities to queries which contain words that do not appear in the training data. Empirical results show that FastQ yields accurate identification of intent when compared to a gold standard.
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