We conducted an investigation assuming that the behavior of meltwater within the snowpack significantly influences the runoff mechanism during the snowmelt period in the heavily snow-covered mountainous region. In the watershed based on the Hida metamorphic rocks, which were the target substrate, the electrical conductivity of stream water during baseflow was high, and its value decreased with an increase in water discharge. In the watersheds of snowy mountainous regions, during the severe winter period, the daily average temperature was generally below 0℃. The water supply to the watershed occurred solely from the snowmelt water at the base of the snowpack. Subsequently, as the daily average temperature rose above 0℃, surface melting occurred, and the snowmelt water began to flow into the streams. During the initial stages of snowmelt, even a slight increase in water discharge led to a significant decrease in the electrical conductivity of stream water. However, as the snowmelt progresses and the outflow increased, the similar decrease in electrical conductivity shifted to occur with more substantial increases in water discharge. The observed changes in the relationship between snowmelt runoff and electrical conductivity (EC) were estimated to be due to some of the surface-melted water not infiltrating vertically to the ground surface. Instead, it was believed to flow laterally within the snowpack and reach the streams through subsurface pathways, contributing to the altered EC levels during the snowmelt period. Therefore, it was considered that snow accumulation plays a significant role in the runoff mechanism during the snowmelt period in snowy mountainous areas.

The purpose of this study is to develop a methodology to extract the potential harvesting areas for tower yarder system at a regional scale. In particular, the method was developed for downhill yarding by means of geographic information system (GIS). Using the digital elevation model, points were created on the road near the valley bottom in the forest assuming that the valley bottoms were the location for setting up the tower yarder. Then, the area within a horizontal distance of 500 m from the tower to a perimeter of 360 °without crossing the ridge was calculated by using the “Skyline tools” of the GIS. By subtracting the elevation from the skyline level, the potential harvesting areas was detected while considering deflection. The areas were then classified into three categories based on the height under the cable: suitable for harvesting with the height of 5 m to 80 m, area requiring intermediate support with height less then 5 m, and area of carriage running only which heights are more than 80 m. Compared to the actual harvested area, almost all of the areas were included in the extracted potential area. However, there were some actual harvested areas outside of the potential areas because harvesting over the ridges, which was out of our scope of this study. Although on-site judgement is required for actual determination of the system introduction, the developed method was considered to be effective to explore the potential harvesting areas for tower yarder system at a regional scale.

Mapping the status of overcrowded mixed private forests is a task in forest management. Recently, Airborne lasers have been used for forest analysis, and three wavelengths (532, 1,064, and 1,550 nm) of laser are available and expected to improve accuracy. Therefore, we examined the usefulness of the three wavelength laser data obtained in March (1,550 nm) and September (532, 1,064 nm) for tree species classification which were Sugi cedar, Hinoki cypress, Japanese red pine, and deciduous broadleaf trees in overcrowded private forests in a steep area in Suzuka mountain. The location of tree tops was mapped using point clouds and point clouds within 0.75 m of the tree tops were sampled to generate parameters for classification. Effective parameters were selected using separability and tree species were classified by the support vector machine classifier after producing segmented images by tree area. Deciduous broadleaf and evergreen conifer trees were classified with an overall accuracy of 95.3％ using 1,550 nm data obtained in the defoliation period. The three evergreen conifer species were best classified with an overall accuracy of 88.6％ using reflectance factor parameters and the accuracy improved by 6.7％ than the classification using 1,064 nm data alone. Thus, reflectance factors in multi-wavelength were more effective than single-wavelength data for the evergreen conifer classification.

This study uses the Kanayagawa campus of Fukushima University, where a campus biodiversity conservation system has been in operation since 2009, as a case study to achieve the 30by30 goal. The study clarified the establishment process and operational status of Fukushima University's biodiversity conservation system and examines the challenges of registering OECMs (Other Effective Area-based Conservation Measures) on university campuses from the perspective of the university's organizational management. The results showed that although there were some institutional deficiencies at Fukushima University, both sides communicated and discussed countermeasures every time a case that needed to be considered arose between the university and faculty members. Therefore, close cooperation between the university and faculty members was important for the operation of the system. Many universities were considered to have potential for registration because the OECMs criteria are not limited to the protection of rare species, but also cover natural environments related to humans. The effectiveness of activities on biodiversity and the implementation of monitoring were seen as the main challenges for registration. The use of the campus for education and research, triggered by the registration, was considered to be a unique use of the OECMs by universities.