積雪量変化が北東シベリアのカラマツタイガ林生態系に及ぼす影響

Changes in winter precipitation (snow) may greatly affect vegetation by altering hydrological and biochemical processes. To understand the effects of changing snow cover depth and melt timing on the taiga forest ecosystem, a snow manipulation experiment was conducted in December 2015 at the Spasskaya Pad experimental larch forest in Eastern Siberia, which is characterized by a continental dry climate with extreme cold winters and hot summers. Variables including soil temperature and moisture, oxygen and hydrogen isotope ratios of soil moisture and stem water, foliar nitrogen and carbon contents and their isotopes, phenology, and soil inorganic nitrogen were observed at snow removal (SNOW−), snow addition (SNOW+), and CONTROL plots. After snow manipulation, the soil temperature at the SNOW− plot decreased significantly compared to the CONTROL and SNOW+ plots. At SNOW− plot, snowmelt was earlier and soil temperature was higher than at other plots during spring because of low soil moisture caused by less snowmelt water. Despite the earlier snowmelt and higher soil temperature in the SNOW− plot in the early growing season, needle elongation was delayed. Leaf chemistry also differed between the CONTROL and SNOW− plots. The needle nitrogen content in the SNOW− plot was lower in the middle of July, whereas no difference was observed among the three plots in August. The soil inorganic nitrogen content of each plot corresponded to these results. The amount of soil ammonium was lower in the SNOW− plot than in the other plots at the end of July, however, once mineralization started at the end of August, the amount of soil ammonium in the three plots was comparable. Extremely low soil temperatures in winter and freeze-thaw cycles in spring and dry soil condition in spring and early summer at the SNOW− plot may have influenced the phenology and mineralization of soil inorganic nitrogen

Photographic records of plant phenology and spring river flush timing in a river lowland ecosystem at the taiga-tundra boundary, northeastern Siberia

Arctic terrestrial ecosystems near the treeline in river lowlands are vulnerable to the changing climate and seasonal extreme events, including flooding. We set up a simple camera monitoring system to record the timings and durations of the leafy period and the spring flush of river water at three observation sites (Boydom [B]: 70.64°N, 148.15°E; Kodac [K]:70.56°N, 148.26°E; Verkhny-Khatistakh [VK]:70.25°N,147.47°E) in the Indigirka lowland, in north-eastern Siberia. Time-lapse digital cameras were located at seven points across the three sites. The time intervals were 1–4 or 24 hours. The minimum and maximum monitoring periods were 2-years (July-2016 to August-2018) at B and 5-years (August-2013 to July-2018) at K. One camera documented the timings of river ice melt and open water periods from the riverbank of the Kryvaya River, one of the small tributaries of the Indigirka River. The other six cameras recorded several types of ground cover typical of the area, including larch trees (Larix cajanderi), shrubs (including Salix spp., and Betula nana), forbs, mosses, and graminoids in an ecosystem of sparsely forested shrublands, wetlands, and riversides. The data consists of 45,617 JPEG-format images. This dataset can be used to detect the onset and offset of the growing season and to capture the ice melt timing and water cover periods in wetlands and riversides. It may be useful in validating satellite data such as the vegetation remote sensing index for remote and little-known areas. These data may contribute to the study of the role of high-latitude ecosystems in global climate changes

Changes in Forest Conditions in a Siberian Larch Forest Induced by an Extreme Wet Event

The taiga forest, a semi-arid and nitrogen-limited ecosystem on permafrost, has changed under extreme wet events. This study aims to understand the changes that occurred in a larch forest in Eastern Siberia after the wet event of 2006–2007. In the summer of 2018, studies were conducted at the Spasskaya Pad Experimental Forest Station near Yakutsk, Russia, where a transect (60 m × 510 m) with 34 plots (30 m × 30 m) was set. It included intact sites and affected sites with different levels of forest damage, owing to the extreme wet event. We observed spatial variations in the normalized difference vegetation index (NDVI) calculated from Landsat satellite-observed data, and the foliar δ13C, δ15N, and C/N (carbon/nitrogen) ratio obtained from the needle samples of 105 mature larch trees. Our results reveal that the affected plots had a lower NDVI than the intact plots, resulting from a difference in tree stand density. In addition, the stand density is suggested to be a controlling factor in the spatial variations in the foliar C/N and δ13C values based on their significant relationships with the NDVI in June. We concluded that the larch trees from the regenerating forests in the affected areas have a higher nitrogen level and light availability (relatively low C/N and high δ13C) because of the slight competition for resources, owing to a low-stand density. This may lead to further succession of the larch forests after the extreme wet event

Changes in Forest Conditions in a Siberian Larch Forest Induced by an Extreme Wet Event

The taiga forest, a semi-arid and nitrogen-limited ecosystem on permafrost, has changed under extreme wet events. This study aims to understand the changes that occurred in a larch forest in Eastern Siberia after the wet event of 2006–2007. In the summer of 2018, studies were conducted at the Spasskaya Pad Experimental Forest Station near Yakutsk, Russia, where a transect (60 m × 510 m) with 34 plots (30 m × 30 m) was set. It included intact sites and affected sites with different levels of forest damage, owing to the extreme wet event. We observed spatial variations in the normalized difference vegetation index (NDVI) calculated from Landsat satellite-observed data, and the foliar δ13C, δ15N, and C/N (carbon/nitrogen) ratio obtained from the needle samples of 105 mature larch trees. Our results reveal that the affected plots had a lower NDVI than the intact plots, resulting from a difference in tree stand density. In addition, the stand density is suggested to be a controlling factor in the spatial variations in the foliar C/N and δ13C values based on their significant relationships with the NDVI in June. We concluded that the larch trees from the regenerating forests in the affected areas have a higher nitrogen level and light availability (relatively low C/N and high δ13C) because of the slight competition for resources, owing to a low-stand density. This may lead to further succession of the larch forests after the extreme wet event

Photographic records of plant phenology and spring river flush timing in a river lowland ecosystem at the taiga–tundra boundary, northeastern Siberia

Arctic terrestrial ecosystems near the treeline in river lowlands are vulnerable to the changing climate and seasonal extreme events, including flooding. We set up a simple camera monitoring system to record the timings and durations of the leafy period and the spring flush of river water at three observation sites (Boydom [B]: 70.64°N, 148.15°E; Kodac [K]:70.56°N, 148.26°E; Verkhny-Khatistakh [VK]:70.25°N,147.47°E) in the Indigirka lowland, in north-eastern Siberia. Time-lapse digital cameras were located at seven points across the three sites. The time intervals were 1–4 or 24 hours. The minimum and maximum monitoring periods were 2-years (July-2016 to August-2018) at B and 5-years (August-2013 to July-2018) at K. One camera documented the timings of river ice melt and open water periods from the riverbank of the Kryvaya River, one of the small tributaries of the Indigirka River. The other six cameras recorded several types of ground cover typical of the area, including larch trees (Larix cajanderi), shrubs (including Salix spp., and Betula nana), forbs, mosses, and graminoids in an ecosystem of sparsely forested shrublands, wetlands, and riversides. The data consists of 45,617 JPEG-format images. This dataset can be used to detect the onset and offset of the growing season and to capture the ice melt timing and water cover periods in wetlands and riversides. It may be useful in validating satellite data such as the vegetation remote sensing index for remote and little-known areas. These data may contribute to the study of the role of high-latitude ecosystems in global climate changes