The winter monsoon had strengthened after Typhoon 1722 (Saola) passed, and the first wintry winds of the year prevailed in the Kinki and Tokyo areas. Snow clouds intruded in northern Nagano prefecture, and hoarfrost was observed with shallow snowcover on the slopes of Mt. Neko. The hoarfrost developed quickly and spread across the mountain forests, giving the impression of a snow-capped mountain. Snow clouds were stratified with sporadic open blue skies. The autumn leaves were at their peak around the Ueda basin. Late autumn is the most colorful season in the northern Japanese Alps region.

(Photograph and Explanation: Kenichi UENO

Photographed on October 30, 2017)

 Mountainous areas are quite sensitive to global-scale environmental changes, such as warming. Therefore, the effect of global warming on these meteorological elements is a critical issue. However, Mt. Fuji Weather Station, which was once a symbol of meteorological observation in mountainous areas, has remained unmanned since August 2004. Of the other observation sites of the Japan Meteorological Agency, Nobeyama, at 1350 m.a.s.l. elevation, is the highest. When evaluating the effects of a global-scale warming event on regional-scale environmental change in the Japanese Alps at a high elevation of 1350 m.a.s.l., it must be noted that the lack of meteorological observation data at high elevations impedes any evaluations of the effects of warming on the ecological system and water resources in mountainous ranges. A network of 14 meteorological observatories has been developed by Shinshu University in the Japanese Alps, which have already started recording observations. The highest observation site is Mt. Yari, at 3125 m.a.s.l.. Observation data from these sites are sent to a computer at the laboratory via a data communication mobile telephone network or a phone line throughout the year. These meteorological observation data are available on the laboratory website in quasi-real time. The interannual variability of annual mean temperature and snow depth in the Japanese Alps region are discussed.

 Altitude dependence of trends of precipitation has seldom been studied, because insufficient long-term observation data have been collected at various elevations in mountainous areas. In order to clarify the altitude dependences of precipitation and trends, rain gauge data collected at 37 meteorological observation stations by Japan Meteorological Agency in Nagano prefecture in summer (June–September) during the period 1979-2015 are analyzed. Horizontal distributions of summertime precipitation and trends are also investigated, and the influences of relocating observation stations on trends of summertime precipitation are verified. As a result, positive correlations between monthly precipitations and elevation are found, as in previous studies. An analysis of horizontal distributions of summertime precipitation indicates more precipitation in the southwestern part than the northeastern part of Nagano prefecture. A significant difference among trends of precipitation between relocated meteorological stations and others is not recognized. Regarding altitude dependence of trends of precipitation, trends of monthly precipitation in June tend to be small at high-altitude meteorological observation stations rather than at low-altitude stations. However, the negative correlation between annual change rates of monthly precipitation in June and elevation was caused by a decreasing trend of monthly precipitation in June at Ontakesan (Elevation: 2195 m), which is statistically significant with a 5% significance level. No significant relationship between trends of monthly precipitation and elevation was found in July, August, and September. An analysis of horizontal distributions of trends of summertime precipitation indicates that precipitation in June and September tended to decrease in the southern part of Nagano prefecture.

 Gauge-based hourly precipitation data during the 2015-2016 warm seasons in central Japan observed with the Japan Meteorological Agency AMeDAS network and the Japanese Alps Inter-University Cooperation Project (JALPS) mountain observation network are archived. Gauge data are compared to satellite precipitation data (GSMaP_MVK and GPM/DPR) produced by Japan Aerospace Exploration Agency. The distributions of precipitation measured in gauges depend on synoptic scale disturbances showing areas of regional increases/decreases affected by large mountain ranges without year-to-year variability, except for a composite of typhoon cases. Differences in precipitation amounts are less than 2 mm/d depending on satellite product version or timing of passive microwave observations. Larger precipitation amounts of GSMaP_MVK estimated at more than 2 mm/d are distributed over inner mountain areas and northern coastal areas along the Sea of Japan, and larger amounts of gauge-measured precipitation are distributed in central Gifu and Shizuoka Prefectures. The underestimate of local sporadic heavy precipitation in mountainous areas obtained from GSMaP_MVK data was expected depending on shallow convections. Further strategies are discussed for conducting case studies to reveal the causes of discrepancies between gauge-measured and satellite-indicated precipitation.

 Ring width, maximum density, and δ¹⁸O chronologies of Tsuga diversifolia and Picea jezoensis var. hondoensis growing in a sub-alpine forest at Mt. Senjo in the Akaishi Mountains were developed. Ring width and maximum density were measured with X-ray densitometry. Tree-ring δ¹⁸O was measured using a mass spectrometer after cellulose extraction. The chronologies developed have significant positive correlations with monthly temperatures in July, August, and September, with the exception of the ring width of T. diversifolia. The transfer functions for July-September temperature were developed using the four chronologies and were verified statistically. The transfer functions reveal a high coefficient of determination, whereas statistical verifications were not successful with rather low RE, CE, and sign test. The estimated temperatures since 1774 partially agreed with reported climate changes based on historical records. The results indicate that estimated temperature is weak for reconstructing increasing trends and low-frequency variations of temperature, although it is potentially useful for higher frequency temperature changes in local areas.

 The effects of climate change on the snow cover and glaciers, such as an acceleration of their ablation in an alpine region (where these effects are more notable), have received increased attention in recent years. However, the meteorological observation network in the Japanese alpine region is relatively undeveloped, so snow accumulation and exhaustion processes as they relate to climate change in this region are not well understood. Therefore, meteorological observations were conducted in the region from November 2002 to October 2017 and an energy balance analysis for the snow cover periods of 2011/2012 to 2016/2017 was performed. In addition, regression models were applied to model the snowmelt process and simulate the sensitivity of the snowmelt rate to increased air temperature due to climate change. Fluctuations in annual mean air temperature, vapor pressure, and wind speed were not observed during the study period. Consequently, the adjusted ablation model was used to model the snowmelt process. The sensitivity of snowmelt to increased air temperature was evident and indicated the possibility that climate change would restrain snow accumulation and thus the amount of snowmelt. These results imply that it is necessary to discuss the effects of increasing snowmelt on the natural environment, and especially to consider the mechanism by which snowmelt occurs if climate change effects become explicit.

 The Japanese Northern Alps, facing the Sea of Japan and composed of several high mountains with peaks over 3,000 m above sea level, are known to form one of the heaviest snowfall areas in the world. However, the horizontal distribution of snow cover and inter-annual and seasonal variations of snow cover have not been understood completely because of a lack of observations. Therefore, numerical simulations are conducted using the Nonhydrostatic Regional Climate Model (NHRCM) with 2-km and 5-km grid spacings (hereafter, NHRCM02 and NHRCM05, respectively), and the simulations are compared to snow cover observations at Murododaira and along the Tateyama-Kurobe Alpine Route. Both NHRCM02 and NHRCM05 simulate interannual variations of snow depth observed at Murododaira in mid-March and late April well, although the snow depth is slightly overestimated. Compared to snow cover observations in the winter of 2014/15, NHRCM05 has remarkably large biases of snow depth at Midagahara and Daikandai. The overestimations of snow depth are improved by NHRCM02 at these stations. The 17-year-mean maximum snow depth shows that NHRCM05 calculates a greater snow depth at the windward side of the Japanese Northern Alps than does NHRCM02, which also influences the altitudinal dependence of snow depth. The horizontal resolution of NHRCM05 is not high enough to resolve convective precipitation over the Sea of Japan in winter. Therefore, NHRCM05 simulates less precipitation over the Sea of Japan and more over mountainous areas than NHRCM02, which results in large snow cover biases at the windward side of the Japanese Northern Alps.

 The vulnerability of alpine ecosystems to climate change, as pointed out by the Intergovernmental Panel on Climate Change (IPCC), and the necessity to monitor alpine zones have been recognized globally. The Japanese alpine zone is characterized by extreme snowfall, and snowmelt time is a key factor in the growth of alpine vegetation. Therefore, in 2011, the National Institute for Environmental Studies (NIES), Japan, initiated long-term monitoring of snowmelt time and ecosystems in the Japanese alpine zone using automated digital time-lapse cameras. Twenty-nine monitoring sites are currently in operation. In this study, images from the cameras installed at mountain lodges in Nagano Prefecture and around Mt. Rishiri in Hokkaido are used. In addition, live camera images are obtained from cameras already operated by local governments in the Tohoku area and near Mt. Fuji. Red, green, and blue (RGB) digital numbers are derived from each pixel within the images. Snow-cover and snow-free pixels are classified automatically using a statistical discriminate analysis. Snowmelt time shows site-specific characteristics and yearly variations. It also reflects the local microtopography and differs among the habitats of various functional types of vegetation. The vegetation phenology is quantified using a vegetation index (green ratio) calculated from the RGB digital numbers. By analyzing temporal variations of the green ratio, local distributions of start and end dates and length of growing period are illustrated on a pixel base. The start of the green leaf period corresponds strongly to the snowmelt gradient, and the end of the green leaf period to vegetation type and elevation. The results suggest that the length of the green leaf period mainly corresponds to the snowmelt gradient in relation to local microtopography.

 Alpine vegetation is considered to be sensitive to climate change. This assumption is supported by an increasing number of observational studies. Vegetation changes during the last decade at Mt. Komagatake in central Japan are reported. Four permanent quadrats of 1 m × 1 m at each of four plots (total 16 quadrats) are set and each quadrat is divided into 100 small grids (0.1 m × 0.1 m). All vascular plant species are recorded in each grid. Soil surface temperature (at depth of 1 cm) is automatically recorded with data loggers at 1-h intervals to determine the start day of the growing season and to calculate the effective cumulative soil temperature. Species numbers did not differ significantly between 2008 and 2017. However, total plant numbers did increase significantly in 2017 from those in 2008. At the study sites, effective cumulative soil temperatures partly explain the increase in total plant numbers. Dwarf shrubs had a tendency to increase compared to graminoids and forbs.

 Long-term geo-environmental changes on a post-fire alpine slope of Mt. Shirouma-dake in the northern Japanese Alps are examined. The fire event occurred on May 9, 2009 on an alpine slope of Mt. Shirouma-dake and spread to Pinus pumila communities and grasslands. The fire resulted in significant damage to P. pumila communities, while that to grassland was minimal. The burning of needles of P. pumila communities exposed the forest floor to atmospheric conditions such as rain, wind, and snow. A map of micro-landforms based on geomorphological field observations was prepared. These micro-landforms were observed for a period of seven years after the fire event. The results do not indicate significant changes to the micro-landforms; however, litter from the forest-floor of burned P. pumila communities was flushed out to surrounding areas. The average thickness of the litter layer of the forest-floor of burned P. pumila communities was 3.5 cm in September 2011, which had decreased to less than 0.5 cm by September 2015. The P. pumila communities on the slope were established on angular and sub-angular gravel having an openwork texture covered with a thin soil layer. It is necessary to pay attention to soil erosion following the outflow of litter because the soil layer can be easily eroded. In addition, ground temperatures of burned and unburned P. pumila communities were measured from 2009 to determine the influence of fire. Ground temperature sensors were installed in the soil at depths of 1 cm, 10 cm, and 40 cm. Diurnal freeze-thaw cycles occurred at a soil depth of 1 cm on the post-fire slope in October and November from 2011 to 2016. However, these cycles did not occur in 2009 and 2010. In addition, the periods of seasonal frost at depths of 10 cm and 40 cm on the post-fire slope were extended by a period of two weeks in comparison to the unburned P. pumilla community. These thermal changes were triggered by a decrease in the thickness of the litter layer in the burned P. pumila community.

 Forest ecosystems play important functional roles over a broad spatial scale in our environment ranging from biodiversity sustainability and ecosystem services at local scales to carbon and water cycles at local, regional and global scales. Micrometeorological observations, ecological research, remote sensing, and simulation models have been used to reveal the dynamics of CO₂ exchange between the atmosphere and forest ecosystems, as well as ecological and biogeochemical processes of the carbon cycle in such ecosystems in a changing environment. However, as the structure and functions of forest ecosystems in a mountainous landscape are characterized by their spatial heterogeneity due to the topographic and climatic conditions, ecosystem science needs to develop a multidisciplinary approach. In addition to these carbon cycle between the atmosphere and ecosystems, biogeochemical and hydrological cycles at forested catchments (basin ecosystems particularly in a mountainous landscape) should be explored to clarify and evaluate the ecosystem functions and services under climate change and human impacts. The following are reviewed: (1) long-term and multidisciplinary researches on forest ecosystem structure and functions in a cool-temperate deciduous forest by applying micrometeorological observations, ecological research, plant photosynthesis modeling, and in-situ and satellite remote sensing, (2) challenges of research topics and opportunities involving forest and catchment ecosystems in a mountainous landscape for revealing the dynamics of biogeochemical cycles in changing environments, and (3) our expectations to addressing these scientific challenges by networking research networks from different disciplines.

 To obtain insights into the relevance of climate and environment for life-history evolution, the following are reviewed: 1) life-history classification derived from r–K selection theory and C–S–R triangle theory, 2) theoretical studies of life-history evolution based on population growth and resource allocation, 3) experimental studies to test life-history theories, and 4) empirical comparison studies between and within species, followed by 5) a brief discussion on how the global climate affects the life-history evolution of plants.