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| Aoki, I; Komatsu, T. |
| This paper examines the use of a neural network to analyse and predict the winter catch, in the Joban-Boso Seas off the Pacific coast of central Japan, of young Japanese sardine (Sardinops melanostictus) representing the index of recruits in the sardine stock. The supervised learning paradigm, a three-layer network and a back-propagation algorithm were employed in constructing the neural net. A number of biological, hydrographic and climatic factors constituted an input vector, the output being the catch of young sardine. The association of sardine abundance with environmental factors was quantified in the form of the trained neural network, which indicated important associations with the Southern Oscillation Index, with patterns of the Kuroshio and the... |
| Tipo: Text |
Palavras-chave: Neural network; Japanese sardine; Recruit; Climatic change; Kuroshio-Oyashio. |
| Ano: 1997 |
URL: http://archimer.ifremer.fr/doc/00093/20436/18103.pdf |
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| Komatsu, T. |
| The Seto Inland Sea is the largest enclosed sea in Japan (22,000 km(2) surface area), and is very shallow (average depth of 37 m). Large Zostera marina L. beds throughout the Sea play an important role in its ecosystems and environments. This study reviews the long-term changes in the area of the Zostera beds, as well as some direct and indirect environmental factors which influence their distribution. In 1924, the area of the beds was 4,137 ha in the waters of the Okayama Prefecture, By 1989, 87 % of these beds had been lost. Industrialization and urbanization around the coasts of the Seto Inland Sea began in the 1950s. In the 1960s, the area of the Zostera beds in this Sea amounted to 22,625 ha. Since 1977, 70 % of these beds has been lost. This decline... |
| Tipo: Text |
Palavras-chave: Zostera bed; Long-term change; Pollution; Reclamation; Transparency. |
| Ano: 1997 |
URL: http://archimer.ifremer.fr/doc/00093/20391/18058.pdf |
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