Nitrogen fixation in the North Pacific Ocean

1974 ◽  
Vol 24 (2) ◽  
pp. 109-119 ◽  
Author(s):  
T. H. Mague ◽  
N. M. Weare ◽  
O. Holm-Hansen
2008 ◽  
Vol 5 (1) ◽  
pp. 95-109 ◽  
Author(s):  
T. Moutin ◽  
D. M. Karl ◽  
S. Duhamel ◽  
P. Rimmelin ◽  
P. Raimbault ◽  
...  

Abstract. Due to the low atmospheric input of phosphate into the open ocean, it is one of the key nutrients that could ultimately control primary production and carbon export into the deep ocean. The observed trend over the last 20 years has shown a decrease in the dissolved inorganic phosphate (DIP) pool in the North Pacific gyre, which has been correlated to the increase in di-nitrogen (N2) fixation rates. Following a NW-SE transect, in the Southeast Pacific during the early austral summer (BIOSOPE cruise), we present data on DIP, dissolved organic phosphate (DOP) and particulate phosphate (PP) pools along with DIP turnover times (TDIP) and N2 fixation rates. We observed a decrease in DIP concentration from the edges to the centre of the gyre. Nevertheless the DIP concentrations remained above 100 nmol L−1 and T DIP was more than 6 months in the centre of the gyre; DIP availability remained largely above the level required for phosphate limitation to occur and the absence of Trichodesmium spp and low nitrogen fixation rates were likely to be controlled by other factors such as temperature or iron availability. This contrasts with recent observations in the North Pacific Ocean at the ALOHA station and in the western Pacific Ocean at the same latitude (DIAPALIS cruises) where lower DIP concentrations (<20 nmol L−1) and T DIP <50 h were measured during the summer season in the upper layer. The South Pacific gyre can be considered a High Phosphate Low Chlorophyll (HPLC) oligotrophic area, which could potentially support high N2 fixation rates and possibly carbon dioxide sequestration, if the primary ecophysiological controls, temperature and/or iron availability, were alleviated.


Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 388
Author(s):  
Hao Cheng ◽  
Liang Sun ◽  
Jiagen Li

The extraction of physical information about the subsurface ocean from surface information obtained from satellite measurements is both important and challenging. We introduce a back-propagation neural network (BPNN) method to determine the subsurface temperature of the North Pacific Ocean by selecting the optimum input combination of sea surface parameters obtained from satellite measurements. In addition to sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS) and sea surface wind (SSW), we also included the sea surface velocity (SSV) as a new component in our study. This allowed us to partially resolve the non-linear subsurface dynamics associated with advection, which improved the estimated results, especially in regions with strong currents. The accuracy of the estimated results was verified with reprocessed observational datasets. Our results show that the BPNN model can accurately estimate the subsurface (upper 1000 m) temperature of the North Pacific Ocean. The corresponding mean square errors were 0.868 and 0.802 using four (SSH, SST, SSS and SSW) and five (SSH, SST, SSS, SSW and SSV) input parameters and the average coefficients of determination were 0.952 and 0.967, respectively. The input of the SSV in addition to the SSH, SST, SSS and SSW therefore has a positive impact on the BPNN model and helps to improve the accuracy of the estimation. This study provides important technical support for retrieving thermal information about the ocean interior from surface satellite remote sensing observations, which will help to expand the scope of satellite measurements of the ocean.


2021 ◽  
Author(s):  
R. J. David Wells ◽  
Veronica A. Quesnell ◽  
Robert L. Humphreys ◽  
Heidi Dewar ◽  
Jay R. Rooker ◽  
...  

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