10月の公開セミナー

Earthworms inhabit almost all ecosystems and are important soil macrofauna moving mainly for foraging. Their biomass is large, and their burrowing and ingestion of soils alters soil physicochemical properties. Furthermore, the mucus excreted from the surface of their skin affects the surrounding soil microbes which in turn have a strong influence on soil material flow dynamics. Also because of their huge biomass the earthworms are regarded as indicator as "soil heath". However, primarily owing to the difficulties involved in quantifying their behavior, the extent of their impact on soil material flow dynamics and "soil health" is poorly known. Image data have proven to be a powerful tool in quantifying the movements of objects, with the aid of image processing tools. Image data sets are often huge and time consuming to analyze especially if the data are continuously recorded and manually proceeded. Thus, the objective of this study was to develop a system to quantify earthworm movement. Our newly developed program successfully tracked the two-dimensional positions of three separate parts of the earthworm along with its change in body length. From the output data, we estimated the velocity. The performance of the program has been verified by comparison with manually estimated data. To date, there are no existing systems to quantify earthworm activity, because they can move and stretch their bodies out of view in continuously recorded image data. The system developed in this study will reduce labor intensity and errors involved in the quantification of huge data sets and provide more reliable estimated values. In combination with other techniques, such as metabolic gas emission from the earthworm bodies, this program will provide continuous observations of earthworm behavior in response to environmental variables under laboratory conditions.

Dijon 研究所のクロルデコン汚染土壌修復研究及び国際会議での研究（主にバイレメ関連）の紹介を行います。

Crop growth and yields in water-limited regions are affected by irrigation management as well as variations in climatic condition, especially precipitation. While many crop models can simulate the impacts of variations in precipitation on given irrigation scenarios, only a few models can simulate variations in crop yields accounting for available agricultural water resources responding to regional climatic and socioeconomic conditions. We developed a coupled model for assessing both crop yields and agricultural water resources and tested its performance, taking Songhua river watershed, Northeast China, where a major semi-arid crop-producing region in China. Results showed that the simulated mean evapotranspiration and surface soil moisture content during the growing season over the area matched with the corresponding observations. The simulated mean river discharge during the growing season fell within the range of the year-to-year variations in the observations during the past years. Also, the simulated the long-term trend and annual variations in crop yield faithfully reproduced the corresponding observations.