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  • 1
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Testor, P., de Young, B., Rudnick, D. L., Glenn, S., Hayes, D., Lee, C. M., Pattiaratchi, C., Hill, K., Heslop, E., Turpin, V., Alenius, P., Barrera, C., Barth, J. A., Beaird, N., Becu, G., Bosse, A., Bourrin, F., Brearley, J. A., Chao, Y., Chen, S., Chiggiato, J., Coppola, L., Crout, R., Cummings, J., Curry, B., Curry, R., Davis, R., Desai, K., DiMarco, S., Edwards, C., Fielding, S., Fer, I., Frajka-Williams, E., Gildor, H., Goni, G., Gutierrez, D., Haugan, P., Hebert, D., Heiderich, J., Henson, S., Heywood, K., Hogan, P., Houpert, L., Huh, S., Inall, M. E., Ishii, M., Ito, S., Itoh, S., Jan, S., Kaiser, J., Karstensen, J., Kirkpatrick, B., Klymak, J., Kohut, J., Krahmann, G., Krug, M., McClatchie, S., Marin, F., Mauri, E., Mehra, A., Meredith, M. P., Meunier, T., Miles, T., Morell, J. M., Mortier, L., Nicholson, S., O'Callaghan, J., O'Conchubhair, D., Oke, P., Pallas-Sanz, E., Palmer, M., Park, J., Perivoliotis, L., Poulain, P., Perry, R., Queste, B., Rainville, L., Rehm, E., Roughan, M., Rome, N., Ross, T., Ruiz, S., Saba, G., Schaeffer, A., Schonau, M., Schroeder, K., Shimizu, Y., Sloyan, B. M., Smeed, D., Snowden, D., Song, Y., Swart, S., Tenreiro, M., Thompson, A., Tintore, J., Todd, R. E., Toro, C., Venables, H., Wagawa, T., Waterman, S., Watlington, R. A., & Wilson, D. OceanGliders: A component of the integrated GOOS. Frontiers in Marine Science, 6, (2019): 422, doi:10.3389/fmars.2019.00422.
    Description: The OceanGliders program started in 2016 to support active coordination and enhancement of global glider activity. OceanGliders contributes to the international efforts of the Global Ocean Observation System (GOOS) for Climate, Ocean Health, and Operational Services. It brings together marine scientists and engineers operating gliders around the world: (1) to observe the long-term physical, biogeochemical, and biological ocean processes and phenomena that are relevant for societal applications; and, (2) to contribute to the GOOS through real-time and delayed mode data dissemination. The OceanGliders program is distributed across national and regional observing systems and significantly contributes to integrated, multi-scale and multi-platform sampling strategies. OceanGliders shares best practices, requirements, and scientific knowledge needed for glider operations, data collection and analysis. It also monitors global glider activity and supports the dissemination of glider data through regional and global databases, in real-time and delayed modes, facilitating data access to the wider community. OceanGliders currently supports national, regional and global initiatives to maintain and expand the capabilities and application of gliders to meet key global challenges such as improved measurement of ocean boundary currents, water transformation and storm forecast.
    Description: The editorial team would like to recognize the support of the global glider community to this paper. Our requests for data and information were met with enthusiasm and welcome contributions from around the globe, clearly demonstrating to us a point made in this paper that there are many active and dedicated teams of glider operators and users. We should also acknowledge the support that OceanGliders has received from the WMO/IOC JCOMM-OCG and JCOMMOPS that have allowed this program to develop, encouraging us to articulate a vision for the role of gliders in the GOOS. We acknowledge support from the EU Horizon 2020 AtlantOS project funded under grant agreement No. 633211 and gratefully acknowledge the many agencies and programs that have supported underwater gliders: AlterEco, ANR, CFI, CIGOM, CLASS Ellet Array, CNES, CNRS/INSU, CONACyT, CSIRO, DEFRA, DFG/SFB-754, DFO, DGA, DSTL, ERC, FCO, FP7, and H2020 Europen Commission, HIMIOFoTS, Ifremer, IMOS, IMS, IOOS, IPEV, IRD, Israel MOST, JSPS, MEOPAR, NASA, NAVOCEANO (Navy), NERC, NFR, NJDEP, NOAA, NRC, NRL, NSF, NSERC, ONR, OSNAP, Taiwan MOST, SANAP-NRF, SENER, SIMS, Shell Exploration and Production Company, Sorbonne Université, SSB, UKRI, UNSW, Vettleson, Wallenberg Academy Fellowship, and WWF.
    Keywords: In situ ocean observing systems ; Gliders ; Boundary currents ; Storms ; Water transformation ; Ocean data management ; Autonomous oceanic platforms ; GOOS
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    ISSN: 0032-8332
    Keywords: Macaca fuscata ; Protein polymorphism ; Genetic distance ; Principal component analysis ; Hennigian cladistics
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract Genetic variability in local populations of the Japanese macaque (Macaca fuscata) was quantified by the proportion of polymorphic loci (Ppoly) and the average heterozygosity per individual ( $$\bar H$$ ) from the starch- and polyacrylamide-gel electrophoreses of blood proteins controlled by 32 independent genetic loci. Ppoly averaged 13.6% and $$\bar H$$ 2.1%, the values being at lower level compared with other mammalian species. Geographical distribution of the genetic variations was not uniform in the whole species but its local differentiation was remarkable. Genetic variability tended to be lower in the southern localities, especially in the southernmost island of Yaku, than in the central and northern localities. The genetic distance and the principal component analyses showed that the most divergent local populations were the population in the Shimokita peninsula at the northernmost distribution area of the species and the populations on the Yaku island at the southernmost. The most contributory loci to the genetic divergence were the PGM-II, Gc, and Hb-β, the variant allele at the first locus being concentrated in the Yaku island, in the Shimokita peninsula, and in the easternmost Boso peninsula, and the variant allele at the latter two loci having high frequencies in the Shimokita and the Izu peninsulas. The Hennigian cladistic analysis, for which the Chinese rhesus macaque (M. mulatta) was used as the outgroup, revealed that the number of presence of derived (apomorphic) alleles was conspicuously smaller in southern islet populations than in central and northern populations, whereas any areal tendency was not recognized in the number of loss of ancestral (plesiomorphic) alleles. The observed distribution pattern that the plesiomorphic variant allele at the PGM-II locus concentrated only in the peripheral (southernmost, northernmost, and easternmost) ranges of the species, would indicate, as a possibility, the occurrence of two or more waves of immigration of ancestors of the present-day Japanese macaque from the Asian continent.
    Type of Medium: Electronic Resource
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