Plankton Size Spectra in Relation to Ecosystem Productivity, Size, and Perturbation

1986 ◽  
Vol 43 (9) ◽  
pp. 1789-1794 ◽  
Author(s):  
W. Gary Sprules ◽  
M. Munawar

Quantification and comparisons of the structure of open-water plankton communities from 25 inland lakes of Ontario, from the Laurentian Great Lakes Superior, Huron, St. Clair, Ontario, and Erie, and from the Central Gyre in the North Pacific Ocean were made on the basis of the normalized biomass size spectrum. Residual variation around the fitted straight lines (corresponding to a theoretical steady state) was least for the large, oligotrophic Lake Superior and the North Pacific Gyre and greatest for eutrophic Saginaw Bay and shallow Lake Erie, suggesting progressive departure from steady-state conditions with increasing system productivity. The slopes of the normalized spectra decrease with increasing eutrophy, indicating that nannoplankton abundances are similar in all communities studied, but that associated zooplankton abundances vary by 2.5 orders of magnitude. Our results suggest that parameterization of particle-size models for prediction of potential fish production must be adjusted according to the size and productivity of the ecosystem, and that routine monitoring of communities by the normalized biomass spectrum could provide early warning of nutrient or toxic stress in aquatic ecosystems.

2020 ◽  
Author(s):  
Michio Aoyama ◽  
Daisuke Tsumune ◽  
Yayoi Inomata ◽  
Yutaka Tateda

<p>Regarding with amount of movement of 137Cs from domain to domain for several years after the accident, we also evaluated that the amount of 137Cs transported by the rivers might be 40 TBq which is corresponding to less than 1.3 % of deposited 137Cs. For resuspension, the annual deposition of 137Cs at Okuma during the period from 2014 to 2018 means that 4 TBq year-1to 10 TBq year-1should be amount of resuspension from land to atmosphere and this amount correspond to 0.1 % to 0.3 % of total deposition of 137Cs on land in Japan. The 137Cs activity concentration at 56N canal in 2016-2018 correspond to 137Cs discharge of 0.73 TBq year-1to 1.0 TBq year-1from FNPP1 site to open water. The integrated amount of FNPP1 derived 137Cs that entered the Sea of Japan, SOJ, until 2017 was 0.27 ± 0.02 PBq, which is 6.4 % of the estimated total amount of FNPP1-derived 137Cs in the STMW in the North Pacific. The integrated amount of FNPP1-derived 137Cs that returned to the North Pacific Ocean through the Tsugaru Strait from SOJ was 0.11 ± 0.01 PBq, 42 % of the total amount of FNPP1-derived 137Cs transported to the SOJ. As a result of decontamination works, 134 TBq of 137Cs was removed from surface soil until February 2019 which correspond to 4 % of deposited 137Cs on land in Japan. Therefore, the largest transport amount of 137Cs was 270 ± 2 TBq from STMW in the North Pacific to SOJ until 2017, and the second largest was decontamination work by which work about 134 TBq was removed from surface soil on land until Feb. 2019. Fluvial transport by rivers contributed about 40 TBq since June 2011 until 2016.</p>


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 ◽  
...  

2010 ◽  
Vol 37 (2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Robert H. Byrne ◽  
Sabine Mecking ◽  
Richard A. Feely ◽  
Xuewu Liu

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