A new species of free-living marine nematode, Diplolaimella ariakensis n. sp. (Nematoda: Monhysteridae) from the Ariake Sea, Japan

Summary A new species of free-living marine nematode, Diplolaimella ariakensis n. sp., is described from a muddy tidal flat of the Ariake Sea, southern Japan. Diplolaimella ariakensis n. sp. differs from its congeners by the following: presence of ocelli, absence of denticles in the buccal cavity, a long tail (11-14 cloacal body diam., c = 3.2-4.0 in male, 17-21 anal body diam., c = 2.9-3.4 in female), spicules as long as 1.4-1.8 cloacal body diam., gubernaculum 0.4-0.5 cloacal body diam. long with a dorsocaudal apophysis 0.5-0.7 cloacal body diam. long, presence of a precloacal supplement, absence of postcloacal papillae, presence of seven pairs of body pores in male, and the anterior position of the vulva (V = 43-46). A dichotomous key to Diplolaimella species is provided. Almost full-length 18S rRNA and partial cytochrome c oxidase subunit I gene sequences were determined for D. ariakensis n. sp. A maximum likelihood tree of 18S sequences supported a close relationship between D. ariakensis n. sp. and D. dievengatensis.

Analysis of the Monthly and Spring-Neap Tidal Variability of Satellite Chlorophyll-a and Total Suspended Matter in a Turbid Coastal Ocean Using the DINEOF Method

Missing spatial data is one of the major concerns associated with the application of satellite data. The Data INterpolating Empirical Orthogonal Functions (DINEOF) method has been proven to be an effective tool for filling spatial gaps in various satellite data products. The Ariake Sea, which is a turbid coastal sea, shows the large spatial and temporal variability of chlorophyll-a (Chl-a) and total suspended matter (TSM). However, ocean color satellite data for this region usually have large gaps, which affects the accurate analysis of Chl-a and TSM variability. In this study, we applied the DINEOF method to fill the missing pixels from the regionally tuned Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua (hereafter, MODIS) Chl-a and MODIS-derived TSM datasets for the period 2002–2017. The validation results showed that the DINEOF reconstructed data were accurate and reliable. Furthermore, the Empirical Orthogonal Functions (EOF) analysis based on the reconstructed data was used to quantitatively analyze the spatial and temporal variability of Chl-a and TSM at both monthly and individual events of spring-neap tidal scales. The first three EOF modes of Chl-a showed seasonal variability mainly caused by precipitation, the sea surface temperature (SST), and river discharge for the first EOF mode and the sea level amplitude for the second. The first three EOF modes of TSM exhibited both seasonal and spring-neap tidal variability. The first and second EOF modes of TSM displayed spring-neap tidal variability caused by the sea level amplitude. The second EOF mode of TSM also showed seasonal variability caused by the sea level amplitude. In this study, we first applied the DINEOF method to reconstruct the satellite data and to capture the major spatial and temporal variability of Chl-a and TSM for the Ariake Sea. Our results demonstrate that the DINEOF method can reconstruct patchy oceanic color datasets and improve spatio-temporal variability analysis.