Yutaka Tateda

Simulation of radioactive cesium transfer in the southern Fukushima coastal biota using a dynamic food chain transfer model.

The Fukushima Dai-ichi Nuclear Power Plant (1F NPP) accident occurred on 11 March 2011. The accident introduced (137)Cs into the coastal waters which was subsequently transferred to the local coastal biota thereby elevating the concentration of this radionuclide in coastal organisms. In this study, the radioactive cesium levels in coastal biota from the southern Fukushima area were simulated using a dynamic biological compartment model. The simulation derived the possible maximum radioactive cesium levels in organisms, indicating that the maximum (137)Cs concentrations in invertebrates, benthic fish and predator fish occurred during late April, late May and late July, respectively in the studied area where the source was mainly the direct leakage of (137)Cs effluent from the 1F NPP. The delay of a (137)Cs increase in fish was explained by the gradual food chain transfer of (137)Cs introduced to the ecosystem from the initial contamination of the seawater. The model also provided the degree of radionuclide depuration in organisms, and it demonstrated the latest start of the decontamination phase in benthic fish. The ecological half-lives, derived both from model simulation and observation, were 1-4 months in invertebrates, and 2-9 months in plankton feeding fish and coastal predator fish from the studied area. In contrast, it was not possible to similarly calculate these parameters in benthic fish because of an unidentified additional radionuclide source which was deduced from the biological compartment model. To adequately reconstruct the in-situ depuration of radiocesium in benthic fish in the natural ecosystem, a contamination source associated with the bottom sediments is necessary.

Gas Exchange Analysis for Estimating Net CO2 Fixation Capacity of Mangrove (Rhizophora stylosa) Forest in the Mouth of River Fukido, Ishigaki Island, Japan

Abstract Mangrove trees have been considered to possess a higher carbon fixation capacity than terrestrial trees although a reliable method to estimate their CO2 fixation capacity has not been established. In this study, net CO2 fixation in above-ground of Rhizophora stylosa was estimated as the difference between photosynthetic absorption and respiratory emission of CO2. In order to estimate these parameters, photosynthetic rates of single-leaves in response to light and temperature and the respiratory rates of leaves and branches in response to temperature were measured. Furthermore, we established a model of diurnal change in temperature. Monthly averages of the diurnal temperature change were used for correcting the CO2 absorption and emission. The effect of temperature modification on the estimation of net CO2 fixation was examined, and the net CO2 fixation capacity estimated with and without temperature modification was compared. Biomass accumulation estimated without temperature modification (i.e. corrected only for the light intensity) was 6.1 tons ha-1 yr-1, while that estimated with temperature modification (i.e. corrected for both light intensity and temperature) was 13.0 tons ha-1 yr-1. A doubling of the estimated values of net CO2 fixation as observed in this study was caused by the decrease in respiratory CO2 emission by half, which results from temperature modification. These findings suggest that temperature modification in gas exchange analysis could improve the accuracy of estimation of the net CO2 fixation capacity.

Status of 137Cs contamination in marine biota along the Pacific coast of eastern Japan derived from a dynamic biological model two years simulation following the Fukushima accident

Radiocesium ((134)Cs and (137)Cs) released into the Fukushima coastal environment was transferred to marine biota inhabiting the Pacific Ocean coastal waters of eastern Japan. Though the levels in most of the edible marine species decreased overtime, radiocesium concentrations in some fishes were still remained higher than the Japanese regulatory limit for seafood products. In this study, a dynamic food chain transfer model was applied to reconstruct (137)Cs levels in olive flounder by adopting the radiocesium concentrations in small demersal fish which constitute an important fraction of the diet of the olive flounder particularly inhabiting area near Fukushima. In addition, (137)Cs levels in slime flounder were also simulated using reported radiocesium concentrations in some prey organisms. The simulated results from Onahama on the southern border of the Fukushima coastline, and at Choshi the southernmost point where the contaminated water mass was transported by the Oyashio current, were assessed in order to identify what can be explained from present information, and what remains to be clarified three years after the Fukushima Dai-ichi nuclear power plant (1FNPP) accident. As a result, the observed (137)Cs concentrations in planktivorous fish and their predator fish could be explained by the theoretically-derived simulated levels. On the other hand, the slow (137)Cs depuration in slime flounder can be attributed to uptake from unknown sources for which the uptake fluxes were of a similar magnitude as the excretion fluxes. Since the reported (137)Cs concentrations in benthic invertebrates off Onahama were higher than the simulated values, radiocesium transfer from these benthic detritivorous invertebrates to slime flounder via ingestion was suggested as a cause for the observed slow depuration of (137)Cs in demersal fish off southern Fukushima. Furthermore, the slower depuration in the demersal fish likely required an additional source of (137)Cs, i.e. contaminated detritus or sediment which was entrained with the prey during the active sediment feeding of this fish species.

A Method to Recognize and Count Leaves on the Surface of a River Using User's Knowledge about Color of Leaves

This paper proposes a recognition and count method of leaves on the surface of a river to be used in mangrove ecosystem monitoring. Conventionally counting leaves required considerable manual labor for precise monitoring of material flow in the ecosystem. Therefore an efficient counting method was needed. Our method automatically recognizes and counts the number of floating leaves in recorded video using color and motion features. The color feature is represented by 3 dimensional histogram of a color space. We have developed a user interface based on the interactive machine learning model to acquire the color feature from video images. The user can easily produce a huge number of sample data to extract the color feature by the user interface in the same way as coloring a picture. For the motion feature, speed and acceleration of the targets are used. The counting method proposed in this paper has been applied to three videos (total five hours) which recorded about 20,000 leaves, and high recall and precision rates of 96% and 94%, respectively, have been achieved.