In Ise Bay, the catch of sand lance has decreased, and fishing has been prohibited since 2016. The main factor behind the decline in sand lance in Ise Bay is thought to be a decline in their water temperature tolerance, which is accompanied by a decrease in condition factor due to food scarcity in the center and mouth of the Ise Bay, from the period of feeding migration to the onset of aggregation around the aestivation ground. In this study, we expressed productive structure of sand lance in Ise Bay using the life cycle model, a Lagrangian model coupled with Eulerian hydrodynamic and lower-trophic ecosystem models, developed in our previous study on the sand lance (Ammodytes japonicus) in the eastern Seto Inland Sea. The model was validated with numerical experiment over the 2-year period from 2014 to 2015. As a result, the growth dynamics of sand lance from hatching through aestivation to spawning and hatching in the following year, as well as ecological features of the lower trophic ecosystem including plankton abundance and nutrient stocks, were reproduced fairly showing a good agreement with the observational data. The model turned out to provide a quantitative evaluation on the interaction between sand lance—the higher trophic organism—, plankton and nutrients—the lower trophic constituents—. In addition, compared to the eastern Seto Inland Sea, Ise Bay showed greater changes in sand lance production due to changes in nutrients and the production of the lower trophic level ecosystem.

We propose a method for estimating high-quality magnetotelluric impedances by evaluating data objectively from long-term seafloor electromagnetic observations. The marine magnetotelluric method, based on natural fluctuations of geomagnetic and electric fields measured on the seafloor, elucidates the distribution of electrical resistivity in the solid Earth. Recently, enormous data are acquired due to increase of observation site and sampling rate, so that the selection and discarding of data are required before analyzing to obtain the target’s EM responses more accurately. However, these processes usually depend on empirical methods. In this study, we addressed this issue by analyzing data acquired at the Kumano-nada area, Japan. We evaluated the quality of the multi-component electric field data using different combinations of electrodes. Then, we divided the time-series data at certain time intervals and evaluated the quality of the observed data for each section. The quality of the observed data was determined based on errors in the impedance phase and the value of multiple coherencies. Using the best combination of electrodes and the better section of the observed data sets, we successfully estimated magnetotelluric impedances of better quality than those obtained by the conventional analysis. Our proposed method enables automatic selection of high-quality observed data effectively, facilitating the high-quality MT response functions required for imaging resistivity structures.

In Ise Bay, the catch of sand lance (Ammodytes japonicus) has decreased, and fishing has been prohibited since 2016. The main factor behind the decline in sand lance standing stock is thought to be a decline in their water temperature tolerance, which is accompanied by a decrease in condition factor due to food scarcity in the center and mouth of Ise Bay, from the period of feeding migration to the onset of aggregation around the aestivation ground. In this study, using a sand lance life cycle model (a Lagrangian model coupled with Eulerian hydrodynamic and lower-trophic ecosystem models) developed in a previous study that can be applied to Ise Bay and Mikawa Bay, we conducted a simulation assuming the nutritional environment of the past (mid-2000s) when sand eel catches were high and nutrients were high, with the aim of analyzing the process of fluctuations in sand eel production in Ise Bay and the mechanism of sand eel recovery. The calculation results showed that, assuming the inflow load in the mid-2000s, the increased nutrients in Mikawa Bay spread to the mouth of Ise Bay, increasing the number and condition factor of sand lance that gather from the mouth of Ise Bay to the area around the aestivation ground in May and June (the aggregation period), and the survival rate during the aestivation period increased, resulting in a rapid increase in the number of stock fish the following year. On the other hand, even when assuming the inflow load amount of the mid-2000s, when the initial population was small, fewer sand lance gathered around the mouth of Ise Bay and the aestivation ground during the aggregation period, and fewer fish reached the only aestivation ground in Ise Bay, so the recovery of the population slowed.

It is widely known that sardine have population cycles, and their population peaks every 60 and 300 years for multiple sardine species in distant ocean regions in the world. Recent studies by Tameishi have suggested (possible) correlation between sardine population cycles and Length of Day (LOD) and Geomagnetic Intensity (GEOM) derived from the fluctuation of earth’s outer liquid core (Holme and Viron, 2005). This study suggests another correlation between the Galactic Cosmic Ray Data (GCRD) and sardine population cycle. More specifically, sardine population and photon energy of galactic cosmic ray are positively correlated. The Index Galactic Cosmic Ray Data (GCRD) and the Index of Sardine Scale Deposition Rate (SSDR) were examined if they have correlations with Sardine Catch Volume (SCV), and followings were found out: (i) a statistically significant correlation between the Index of GCRD and the Index of SSDR: from 1951 to 2004 (R² = 0.877, p = 2.85E-25 < 0.001) and (ii) a statistically significant correlation between the Index of GCRD and the Sardine Catch Volume in Japan (SCV: from 1951 to 2004) (R² = 0.672, p = 3.59E-14 < 0.001). But, (iii) no statistically significant correlation between the Index of NPP and the Index of SSDR: from 1951 to 2004) (R² = 0.073, p = 0.052 > 0.05). It is possibly because photon energy of galactic cosmic ray stimulates atoms in the cells of sardine, then the atoms turn into excited states (so called excitation).