Snow plays an important role in the ecosystems of the Northern Hemisphere (Chapin et al., 2000; Vavrus, 2007). Snow cover acts as an insulator in winter and regulates the water and nutrient balance, thereby influencing material cycling in summer (Aerts et al., 2004; Kreyling et al., 2012; Freppaz et al., 2018). As stated in the IPCC Fifth Assessment Report, the snow-covered area is declining as the southern boundary turns into a snow-free area (Vaughan et al., 2013). Because of global warming, snow-covered areas are expected to decrease and precipitation events are expected to become less frequent and intense (Huntington, 2006; Deser et al., 2010; Callaghan et al., 2011).
Although a general decrease in the depth of snow cover is expected, snow depth may increase in cold permafrost regions. According to simulation models by Park et al. (2014), snow depth is expected to increase in Siberia by 0.99 mm per year. This modeled trend is in accordance with observations from the central and western Siberia regions of Russia (Bulygina et al., 2009; Bulygina et al., 2011). Snow cover depth and duration have a major effect on ecosystems through their influence on the soil water balance and thermal regimes, nutrient availability, and duration of the growing season (Schimel et al., 2004; Grippa et al., 2005; Loranty et al., 2018). Additionally, changes in snow depth and density have a significant influence on the soil temperature (Zhang, 2005; Callaghan et al., 2011). In continuous permafrost regions, deeper snow cover can lead to a significant increase in mean annual ground temperatures, a reduction in the winter freezing depth, and an increase in soil moisture in spring and summer (Morse et al., 2012; Johansson et al., 2013; Park et al., 2015; Karjalainen et al., 2019). Such phenomena were observed in Eastern Siberia in 2004–2007 with heavy summer rainfall and winter snowfall (Iijima et al., 2010). Interannual variations in snow cover conditions (timing, duration, density, and thickness) also have a strong influence on long-term ground temperatures in cold regions (Aerts et al., 2004). During winter and early spring, arctic soil temperatures mainly depend on the properties of snow cover and regional climate, and even small changes in snow cover can have a strong impact on soil frost frequency and intensity (Walker et al., 1999). In addition to the soil temperature, an increase in snow cover may cause soil subsidence and waterlogging in permafrost regions with a high ice content (Nauta et al., 2015). In high-latitude ecosystems, snowmelt timing controls not only hydrometeorological processes, but also many biological processes such as plant phenology and productivity. There are many case studies of snow manipulation experiments with changing a depth of snow cover (e.g., Wipf and Rixen, 2010).
Snow cover affects soil moisture in the early growing season because approximately half of the snow water equivalent (SWE) infiltrates into the soil after snow melt (Sugimoto et al., 2003). Increased water availability, especially during the early growing season, can positively affect boreal tree growth (Zhang et al., 2019), whereas large amounts of soil moisture may lead to overwetting conditions, resulting in reduced gross primary production (Kotani et al., 2019). In subarctic bogs, phenology observed by earlier flowering dates was reported in an experiment with an open top chamber (Aerts et al., 2004). On the other hand, earlier snow melt, followed by cold air temperatures, reduced productivity in Arctic Alaskan tundra (Stow et al., 2004) and boreal forests in northeastern Siberia (Kirdyanov et al., 2003). Models with coupled hydrological and biogeochemical processes (such as CHANGE) have also shown that deeper snow cover causes larger net ecosystem exchange because of higher soil moisture, especially during dry years (Park et al., 2011).
Snow plays an important role in controlling soil moisture and the nutrient balance because higher soil temperatures can activate the decomposition of soil organic matter, resulting in ecosystem changes (Schimel and Clein, 1996; Hardy et al., 2001; Robinson, 2002; Aerts, 2006). There have been many reports on the relationship between snow cover depth and soil nitrogen (e.g. Wipf and Rixen, 2010); however, these effects are vastly different and depend on ecosystem types, which is likely caused by differences in litter quality and quantity, microbial composition, plant N demand, or the response of soil moisture and soil temperature (Li et al., 2016). Although nitrogen production and uptake by plants during winter are relatively well studied in temperate forests (Andresen and Michelsen, 2005; Ueda and Tokuchi, 2013), the number of studies in boreal and tundra ecosystems is still limited (Cooper, 2014; Koyama and Kielland, 2019). Kielland et al. (2006) described how earlier and deeper snowpacks in forest ecosystems allow microbial activity to continue during winter in Alaska, which was previously presumed to be biologically inactive due to a negative soil temperature. They also observed that winter (non-growing season) nitrogen mineralization accounted for approximately 40% of the annual flux, which was significantly higher than previously reported. Moreover, deeper snow cover causes higher soil nitrogen availability, which leads to increased plant N uptake, foliar nitrogen content, photosynthesis rates (Leffler and Welker, 2013), leaf area index (Pattison and Welker, 2014), and plant production (Wahren et al., 2005).
Frost damage is another factor associated with a decrease in snow cover depth. Thin snow cover may cause freeze-thaw cycles in winter and have a negative effect on plant production. The experimental removal of snow cover has previously produced direct frost damage, followed by a 50% reduction in understory vegetation coverage (Kreyling et al., 2012). Indirectly, soil frost and frequent freeze-thaw cycles in the absence of snow cover during winter and spring can cause a decrease in nitrogen availability (Feng et al., 2007, Frechette et al., 2011), an increase in nitrogen and phosphorus leaching (Fitzhugh et al., 2001), and root damage, which disrupts nutrient uptake (Cleavitt et al., 2008). Forests with deeper organic layers have a lower possibility of soil frost damage during winter, even if the snow cover is less deep (Hardy et al., 2001).
Although there have been many reports on snow manipulation experiments on tundra ecosystems, few reports have been published on forest ecosystems. This is because snow cover manipulation in forests is complicated by snow shoveling, unlike in tundra, where snow fences can be easily used to manipulate snow cover. In temperate and boreal forests, most snow manipulation experiments have been conducted in regions with expected reductions in snow, for example, North America and Scandinavia, and were mainly focused on the snow removal treatment (e.g. Groffman et al., 2001). Snow removal experiments in forested areas have shown a strong effect of snow cover on ecosystem processes, such as heat and moisture fluxes, nutrient dynamics, and changes in phenology and diversity (Groffman et al., 2001; Frechette et al., 2011; Kreyling et al., 2012; Comerford et al., 2013; Drescher and Thomas, 2013; Martz et al., 2016). Because of direct frost damage to the root system, there have been many reports on the reduced ability of plants to uptake water and nutrients (Pilon et al., 1994; Cleavitt et al., 2008; Blume-Werry et al., 2016). A decrease in nutrient availability from shallower snow cover due to leaching or impaired microbial activity has also been reported (Fitzhugh et al., 2001). Moreover, Frechette et al. (2011) observed decreases in foliar N and photosynthetic activity through spring snow removal in a Canadian boreal forest ecosystem. Other effects have also been observed, such as reductions in the terminal shoot length of sugar maple trees in the U.S. (Comerford et al., 2013), a decrease in the coverage of understory plants in Swedish boreal forests (Kreyling et al., 2012), and reductions in sapling survival in forests in Canada and northern Finland (Drescher and Thomas, 2013; Martz et al., 2016). These effects have negative implications for biomass production. As described above, there are many publications on Alaska and European boreal and temperate forest ecosystems; however, no snow manipulation experiments have been conducted for taiga (deciduous conifer larch forests) in northeastern Siberia, which is a globally typical forest ecosystem because of its extremely large area.
Eastern Siberia is a vast territory covered by taiga, which is characterized by deciduous conifer larch trees (Larix gmelinii and L. cajanderi) that grow on permafrost (Archibold, 1995). This region experiences extreme cold winters, short and hot summers, and an extremely dry climate. Because of the vast coverage area of larch forests worldwide (approximately 40% of boreal forests), the response of larch forests is extremely important. Changes in the snow cover depth and snow water equivalent (SWE) in this region affect soil moisture considerably. For larch trees, soil moisture derived from snowmelt water is extremely important in the early summer season when photosynthesis activity is highest (Sugimoto et al., 2002, 2003). It is also expected that larch trees will be affected by changing snow cover and the related processes described above. Nevertheless, there have been no reports of snow manipulation experiments for larch forests in northeastern Siberia. Therefore, the objective of this research is to observe the responses of larch trees to changes in snow cover using snow manipulation experiments.
In this study, we employ two types of treatments: snow addition (SNOW+) and snow removal (SNOW−), and hypothesize that these treatments will have opposing effects (Fig. 1). Specifically, when the depth of “snow cover increases (decreases)”, snowmelt is delayed (advanced), which causes a “shorter (longer) growing season”, resulting in a “decrease (increase) in production”. If the soil moisture is unusually high after snowmelt, this situation may cause “overwetting in early summer (dry condition)” due to a large (small) amount of snowmelt water, which may consequently lead to “forest dieback (drought) “ and resulting in decrease in production. Indeed, an extreme wetting events occurred in 2006–2007 in the taiga forest ecosystem near Yakutsk, which is usually a very dry forest (Iwasaki et al., 2010; Tei and Sugimoto, 2018; Tei et al., 2013, 2017). Moreover, we hypothesize that “snow cover increase (decrease)” also affect nutrient and water availability (Fig. 1). First, an “increase (decrease) in the depth of snow cover” causes “higher (lower) soil temperature during winter”, leading to “higher (lower) microbial activity” and “higher (lower) nitrogen availability”. This may cause an “increase (decrease) in production”. Second, an “increase (decrease) in snow cover” will induce “larger (smaller) infiltration of snow meltwater”, resulting in “higher (lower) water availability” and an “higher (lower) photosynthesis rate”. This may cuase finally an “increase (decrease) in forest production”. Both soil moisture and soil nutrients are limiting factors for forest photosynthetic activity at the study site (Popova et al., 2013; Tei et al. 2013).
To determine the effect of snow cover changes on the Eastern Siberia larch forest ecosystem, a snow manipulation experiment was conducted in December 2015 by manually removing snow from the snow removal plot (SNOW−) by shovels and adding the removed snow to the snow addition plot (SNOW+) by transporting it in heavy duty bags. The aim of this study is to examine whether the manipulated snow cover affects soil temperature and soil moisture via changes in insulation properties and melt timing, which in turn could affect soil nutrients and soil water availability, thereby affecting the timing of needle opening and leaf chemistry. We expect that these effects will cause a change in tree production. As no direct measurements of production change are conducted in this study, we instead employ the following measurements: 1) needle elongation measurements as a proxy for the growing season length, which can be used as a proxy for production change; 2) soil nutrient availability and foliar N%, which can also be used as a proxy for the photosynthesis rate, which has an effect on production; and 3) soil moisture measurements. As soil moisture is an important limiting factor for production in very dry regions, the inclusion of such measurements in snow manipulation experiments should be considered in future research.