scholarly journals Population genetic diversity and historical dynamics of Fraser’s dolphins Lagenodelphis hosei

2020 ◽  
Vol 643 ◽  
pp. 183-195
Author(s):  
I Chen ◽  
S Nishida ◽  
LS Chou ◽  
T Isobe ◽  
AA Mignucci-Giannoni ◽  
...  

Marine organisms face relatively few barriers to gene flow, and yet even highly mobile species such as dolphins often show population structure over regional geographic scales. Understanding the processes that promote this pattern of differentiation helps us understand the evolutionary radiation of this group, and to promote more effective measures for conservation. Here we report the first population genetic study of Fraser’s dolphin Lagenodelphis hosei (Fraser, 1956), a species that was not recognized by the scientific communities until the early 1970s. We use 18 microsatellite DNA loci and 1 mitochondrial DNA (mtDNA) locus to compare 112 Fraser’s dolphins collected in various locations, mainly from the waters off Japan, Taiwan, and the Philippines, but also including samples from the Gulf of Mexico and Caribbean Sea. Our results indicate differentiation between populations in waters off Japan, Taiwan, and the Philippines, and support the findings from earlier morphological assessments for differentiation between Japanese and Philippine waters. Small sample sets also show likely differentiation between other regions in the North Pacific and North Atlantic Oceans. Moreover, neutrality tests and mismatch analysis based on mtDNA data indicate that the populations in the western North Pacific Ocean have expanded demographically and spatially, possibly since the latest global deglaciation, when sea levels and global temperatures started to rise.

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

Sign in / Sign up

Export Citation Format

Share Document