The recruitment process of planktic larvae of the nereidid polychaete Hediste diadroma, which has a catadromous life cycle, was examined in an estuary in Kagoshima Bay, Southern Japan. Our laboratory experiments showed that the phototaxis of the planktic larvae changed drastically from positive to negative during the 3-chaetiger nectochaeta, 3.5-4.0 days after fertilization. During this stage, the prostomial antennae, first peristomial cirri, and anal cirri appeared and the ciliary bands used for swimming were reduced; these results suggest that larvae shifted from pelagic to demersal stage at approximately 4.0 days after fertilization. Field sampling took place in the estuary, where reproductive swarming of mature adults was observed in late February to April; planktic larvae of, mainly, 5-to 8-chaetiger stages were collected in evening high tides during the spring tides of April and May 1989, 2013, and 2015. During the same period, 5-or higher chaetiger benthic juveniles were collected at low tide from intertidal flats from a wide area of the estuary where adults inhabited. The morphology of benthic juveniles of 5-and 6-chaetiger stages differed from that of planktic larvae of the same stages in the following characteristics: (1) the long larva-specific spinigers were lost; (2) the second peristomial cirri, originating from the parapodial lobes of chaetiger 1 of the planktic larvae, appeared; and (3) the anal cirri were elongated. Our results indicate that 5-to 8-chaetiger nectochaeta are critical phases for the successful settlement of planktic larvae, which come back into an estuary with rising tides.

The JPEG statistical models in the lossy mode specify the procedures for converting the Discrete Cosign Transform (DCT) coeficients into binary strings and context modeling in a case where the binary arithmetic coder called QM-coder is employed as entropy coder. The JPEG lossy mode establishes two statistical models, one for prediction residuals of the D C coeficients and the other for the A C coeficients. I n this paper, we redesign these two models by taking account of their distribution. W e confirm that Laplacian distribution is appropriate f o r both the D C coeficients and the A C coeficients through Kolmogorov-Smirnov (KS) test; consequently, we propose the statistical models that fitLaplacian distribution. B y adopting the proposed statistical models in lieu of the conventional models, the number of the states decreases from 294 to 210 and the compression performance on several test images including super high definition images improves by 0.01 to 1.48%.

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