Koichiro Ohgushi

Effects of hypoxia and organic enrichment on estuarine macrofauna in the inner part of Ariake Bay

In the inner part of Ariake Bay, Japan, hypoxia frequently occurs in summer at the organically enriched bottom with salinity stratification caused by flooding after the rainy season. Sediment organic enrichment can work as a stressor for macrobenthos. To investigate the effects of both hypoxia and sediment organic enrichment on macrobenthos, samples were collected at 20 stations by grab sampling in May and August, representing the situation before and after hypoxia, respectively. Although sediment grain size did not change, sediment TOC increased significantly in August. Multivariate analyses showed that the community structure changed significantly in August. The variation in the community structure among stations also increased, which indicated disturbance by stressors during the study period. Similarly, the species richness and total abundance of macrobenthos decreased significantly after hypoxia even after the TOC effect was removed. In addition, the amount of TOC change and the abundance of the main species did not correlate in any case. These results suggest that the community changes during the study period are not caused by stress from the increased sediment TOC but are mainly from the subsequent hypoxic stress.

Retrieving seawater turbidity from Landsat TM data by regressions and an artificial neural network

The radiance reflected at the sea surface (RW (λ)) of the Ariake Sea, Japan, was first estimated by subtracting Lowtran 7 estimated Rayleigh and aerosol scattered radiances from Landsat Thematic Mapper measured radiance. Then RW (λ) was averaged from 4×4 pixel windows centred at 33 sampling sites of the Ariake Sea and the data calibrated against the observed Secchi disk depth (SDD) using linear (LR) and nonlinear (NLR) regressions, and an artificial neural network (ANN) algorithm called the Modified Counter Propagation Network (MCPN). We found that at the validation stage, multi-date RW (λ) data that are mainly based on the visible channels of Landsat Thematic Mapper (TM) predict more accurate and dependable SDDs than single-date RW (λ) data. Furthermore, the NLR describes the SDD/RW (λ) relationship more closely than the LR. As an ANN, MCPN possesses non-linearity, inter-connectivity, and an ability to learn and generalize information from complex or poorly understood systems, which enables it to even better represent the SDD/RW (λ) relationship than the NLR. Our study confirms the feasibility of retrieving SDD (or turbidity) from Landsat TM data, and it seems that the calibrated MCPN and possibly NLR are portable temporally within the Ariake Sea. Lastly, the coefficient of efficiency Ef is a more stringent and probably a more accurate statistical measure than the popular coefficient of determination R 2.

Computational Analysis of Tidal Current and Mass Transport in the Ariake Sea by Using Remote Sensing Technique

ABSTRACT Water quality changes in the Ariake Sea are simulated by numerical calculations of unsteady 2-D depth-averaged equations for fluid motion and mass transport. Landsat-TM images are used to estimate initial distributions of the water quality, such as water transparency and water temperature. Remote sensing technique provides a wide and economical way to monitor water environments. Combinations between the satellite images and the numerical calculations have high potential for estimating water environments in the coastal area.