scholarly journals In situ measurements of capelin (Mallotus villosus) target strength in the North Pacific Ocean

2008 ◽  
Vol 66 (2) ◽  
pp. 258-263 ◽  
Author(s):  
Michael A. Guttormsen ◽  
Christopher D. Wilson
Keyword(s):  
Pacific Ocean ◽  
North Pacific ◽  
North Pacific Ocean ◽  
In Situ Measurements ◽  
Target Strength ◽  
Mallotus Villosus ◽  
The North ◽  
Capelin Mallotus Villosus ◽  
The North Pacific

Abstract Guttormsen, M. A. and Wilson, C. D. 2009. In situ measurements of capelin (Mallotus villosus) target strength in the North Pacific Ocean. – ICES Journal of Marine Science, 66: 258–263. In situ measurements of capelin (Mallotus villosus) target strength (TS) were collected during summer 2001–2003 near Kodiak Island in the Gulf of Alaska, using a calibrated EK500 echosounder with 38 and 120 kHz split-beam transducers. Targets were detected over dispersed, night-time aggregations using standard acoustic methods, then filtered using a quality-control algorithm to reject invalid targets. The 38 kHz-based, fitted model estimate was TS = 20 log10L− 70.3 (r2 = 0.30), where L is total length of fish. Compared with other studies, the TS-fitted model at 38 kHz was similar to that calculated from swimbladder morphology measurements from St Lawrence estuary capelin (TS = 20 log10L− 69.3), but resulted in greater estimates than models based on in situ measurements of capelin TS in the Barents Sea (TS = 19.1 log10L−74.0) and northern Atlantic Ocean (TS = 20 log10L − 73.1). The large intraspecific variability exhibited in the fitted TS – L models for this species suggests the use of TS measurements from the geographic region where the data were collected.

scholarly journals The dynamic trophic architecture of open-ocean protist communities revealed through machine-guided metatranscriptomics

2021 ◽  
Author(s):  
B.S. Lambert ◽  
R.D. Groussman ◽  
M.J. Schatz ◽  
S.N. Coesel ◽  
B.P. Durham ◽  
...  
Keyword(s):  
Machine Learning ◽  
Pacific Ocean ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Open Ocean ◽  
Functional Roles ◽  
The North ◽  
Nutritional Strategies ◽  
The North Pacific

AbstractIntricate networks of single-celled eukaryotes (protists) dominate carbon flow in the ocean. Their growth, demise, and interactions with other microorganisms drive the fluxes of biogeochemical elements through marine ecosystems. Mixotrophic protists are capable of both photosynthesis and ingestion of prey and are dominant components of open-ocean planktonic communities. Yet, the role of mixotrophs in elemental cycling is obscured by their capacity to act as primary producers or heterotrophic consumers depending on factors that remain largely uncharacterized. Here we introduce a machine learning model that can predict the in situ nutritional mode of aquatic protists based on their patterns of gene expression. This approach leverages a public collection of protist transcriptomes as a training set to identify a subset of gene families whose transcriptional profiles predict trophic status. We applied our model to nearly 100 metatranscriptomes obtained during two oceanographic cruises in the North Pacific and found community-level and population-specific evidence that abundant open-ocean mixotrophic populations shift their predominant mode of nutrient and carbon acquisition in response to natural gradients in nutrient supply and sea surface temperature. In addition, metatranscriptomic data from ship-board incubation experiments revealed that abundant mixotrophic prymnesiophytes from the oligotrophic North Pacific subtropical gyre rapidly remodelled their transcriptome to enhance photosynthesis when supplied with limiting nutrients. Coupling the technique introduced here with experiments designed to reveal the mechanisms driving mixotroph physiology is a promising approach for understanding the ecology of mixotrophic populations in the natural environment.Significance statementMixotrophy is a ubiquitous nutritional strategy in marine ecosystems. Although our understanding of the distribution and abundance of mixotrophic plankton has improved significantly, the functional roles of mixotrophs are difficult to pinpoint, as mixotroph nutritional strategies are flexible and form a continuum between heterotrophy and phototrophy. We employ a machine learning-driven metatranscriptomic technique to assess the nutritional strategies of abundant planktonic populations in situ and demonstrate that mixotrophic populations play varying functional roles along physico-chemical gradients in the North Pacific Ocean, revealing a degree of physiological plasticity unique to aquatic mixotrophs. Our results highlight mechanisms that may dictate the flow of biogeochemical elements and the ecology of the North Pacific Ocean, one of the largest biogeographical provinces on Earth.

scholarly journals Anthropogenic Asian aerosols provide Fe to the North Pacific Ocean

2020 ◽  
Vol 117 (45) ◽  
pp. 27862-27868
Author(s):  
Paulina Pinedo-González ◽  
Nicholas J. Hawco ◽  
Randelle M. Bundy ◽  
E. Virginia Armbrust ◽  
Michael J. Follows ◽  
...  
Keyword(s):  
Pacific Ocean ◽  
Atmospheric Aerosols ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Aerosol Deposition ◽  
Anthropogenic Aerosol ◽  
The North ◽  
Isotope Mass Balance ◽  
The North Pacific

Fossil-fuel emissions may impact phytoplankton primary productivity and carbon cycling by supplying bioavailable Fe to remote areas of the ocean via atmospheric aerosols. However, this pathway has not been confirmed by field observations of anthropogenic Fe in seawater. Here we present high-resolution trace-metal concentrations across the North Pacific Ocean (158°W from 25°to 42°N). A dissolved Fe maximum was observed around 35°N, coincident with high dissolved Pb and Pb isotope ratios matching Asian industrial sources and confirming recent aerosol deposition. Iron-stable isotopes reveal in situ evidence of anthropogenic Fe in seawater, with low δ56Fe (−0.23‰ > δ56Fe > −0.65‰) observed in the region that is most influenced by aerosol deposition. An isotope mass balance suggests that anthropogenic Fe contributes 21–59% of dissolved Fe measured between 35° and 40°N. Thus, anthropogenic aerosol Fe is likely to be an important Fe source to the North Pacific Ocean.

scholarly journals Neural Network Approach to Retrieving Ocean Subsurface Temperatures from Surface Parameters Observed by Satellites

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 388
Author(s):  
Hao Cheng ◽  
Liang Sun ◽  
Jiagen Li
Keyword(s):  
Neural Network ◽  
Pacific Ocean ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Sea Surface ◽  
Satellite Measurements ◽  
Surface Parameters ◽  
The North ◽  
The North Pacific ◽  
Bpnn Model

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.

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