# Sugars in Snow, Their Sources, and Fate Related to Microbial Metabolism: A Review

Francesca Schivalocchi, Kara Sampsell, Christine Piot, Catherine Larose

► To cite this version:

Francesca Schivalocchi, Kara Sampsell, Christine Piot, Catherine Larose. Sugars in Snow, Their Sources, and Fate Related to Microbial Metabolism: A Review. Journal of Geophysical Research: Biogeosciences, 2025, 130 (8), 10.1029/2024JG008720. http://dx.doi.org/10.5194/g2025-130-8-1029-2024

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# JGR Biogeosciences

## REVIEW ARTICLE

10.1029/2024JG008720

**Key Points:**

* Snowpacks receive carbohydrates and organic particles from atmospheric deposition

* Carbohydrates are produced in situ, but this process still needs to be unraveled

* There is a gap in knowledge of the role of microorganisms in sugar cycling in snow

**Correspondence to:**

F. Schivalocchi,
francesca.schivalocchi@univ-smb.fr;
f.schivalocchi97@gmail.com

**Citation:**

Schivalocchi, F., Sampsell, K., Piot, C., & Larose, C. (2025). Sugars in snow, their sources, and fate related to microbial metabolism: A review. *Journal of Geophysical Research: Biogeosciences*, 130, e2024JG008720. https://doi.org/10.1029/2024JG008720

Received 23 DEC 2024

Accepted 28 JUL 2025

**Author Contributions:**

**Conceptualization:**

Francesca Schivalocchi, Kara Sampsell,
Christine Piot, Catherine Larose

**Funding acquisition:** Christine Piot,
Catherine Larose

**Project administration:** Christine Piot,
Catherine Larose

**Supervision:** Christine Piot,
Catherine Larose

**Validation:** Francesca Schivalocchi,
Kara Sampsell, Christine Piot,
Catherine Larose

**Visualization:** Francesca Schivalocchi

**Writing – original draft:**

Francesca Schivalocchi

**Writing – review & editing:**

Francesca Schivalocchi, Kara Sampsell,
Christine Piot, Catherine Larose

## Sugars in Snow, Their Sources, and Fate Related to Microbial Metabolism: A Review

<figure><img src="image_2.png" /></figure>

Francesca Schivalocchi¹,² ID, Kara Sampsell² ID, Christine Piot¹,² ID, and Catherine Larose²

¹EDYTEM—Environnements, Dynamiques et Territoires de Montagne, Université Savoie Mont Blanc, Le Bourget du Lac, France, ²IGE—Institut des Géosciences de l'Environnement, Université Grenoble Alpes, Saint Martin d'Hères, France

**Abstract** Snowpacks play a key role in local and regional biogeochemical cycles and impact surrounding ecosystems during snowmelt. While they do not serve as long-term carbon sinks like glaciers or permafrost, snowpacks temporarily store nutrients, pollutants, and microorganisms that can be released into surrounding ecosystems through meltwater. Active snow microorganisms within temporary snowpacks can contribute to carbon cycling through processes such as carbon fixation, respiration, and carbohydrate metabolism. In addition, snowpacks continuously receive atmospheric inputs, including carbohydrates from plants and microbes. These carbohydrates serve as indicators of biological and human activities. Factors like season, altitude, and location affect the carbohydrate composition, with sugars like glucose, sucrose, and mannitol linked to vegetation and microbial activity, while others, such as levoglucosan, mannosan, and galactosan, trace biomass burning events. Over time, snowpacks transform into firn and eventually ice, trapping airborne particles like carbohydrates. These preserved compounds in ice cores provide insights into past environmental conditions, including vegetation patterns and fire events. However, the current situation of rapid climate change threatens to disrupt these snowpack systems, underscoring the need for urgent investigation into the dynamics of carbohydrates and microbial activity. Thus, further research is crucial to unravel the biochemical processes within snowpacks and their implications for ecosystem dynamics. Field studies and experimental approaches will be fundamental in advancing our understanding of these complex and evolving systems.

**Plain Language Summary** Snowpacks are vital for ecosystems and global elemental cycles, storing nutrients and pollutants prior to their transport during snowmelt. Among these, carbohydrates such as sugars and sugar alcohols, are key components of the carbon pool. Understanding their sources and fates is critical because they serve not only as indicators of environmental conditions, but also as essential nutrients that sustain snow-dwelling organisms. Snowpacks provide a habitat for active microbial communities that influence snow chemistry by breaking down or producing carbohydrates. These interactions are shaped by factors like location and altitude, and they significantly impact the nutrient dynamics within snow. Snow also eventually turns into ice when located on glaciers, locking in these carbohydrates along with other particles. This information can then be analyzed from ice cores to provide clues about past environmental conditions, such as forest cover and fire events. However, climate change is rapidly altering snowpack systems. Understanding how carbohydrates and microorganisms interact within snowpacks is urgent to predict how ecosystems might change. Further research in the field and laboratory is essential to uncover the processes happening in snow and their broader environmental impacts.

### 1. Introduction: Snowpacks and Global Carbon Cycle

Snowpacks are defined as seasonally accumulated layers of snow from multiple snowfall events (Oliver, 2008). In regions of high altitude or latitude, snow can persist for much of the year, undergoing compaction, melt-refreeze cycles, and stratification. While some snowpacks persist for several years or transform into firn and ice on glaciers (Berrisford, 1991; T. Schultz et al., 2021), this review focuses on seasonal snowpacks, which are subject to annual melt. These transient layers serve as active interfaces between the atmosphere and terrestrial ecosystems and play a crucial role in short-term biogeochemical exchanges. During the cold season, snowpacks act as temporary reservoirs, accumulating significant amounts of nutrients (Bhatia et al., 2013; Hood & Scott, 2008; Hood et al., 2009; Robinson & Kawecka, 2005; Saros et al., 2010; Vick-Majors et al., 2020), pollutants, and microbes (Cameron et al., 2020). Snow-covered regions, including glaciers, permafrost, and ice sheets, store approximately 20%–30% of the world's organic carbon (Brooks et al., 2011; Jobbágy & Jackson, 2000; Post et al., 1982; Schimel et al., 2001). Snowpacks specifically contribute to short-term carbon

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<figure><img src="image_3.png" /><figcaption>**Figure 1.** Biogeochemical cycle of organic carbon. Carbon is transported through long-range atmospheric transport and deposited in snowpack and soil. Soil and snowpack exchange carbon and humic like substances and volatile organic compounds. Through UV light oxidation, secondary organic aerosols are produced and exchanged. Natural and anthropogenic sources release organic particles. Expolymeric substances are released in aerosol and transported as well.</figcaption></figure>

cycling and redistribution during melt periods, since upon melting, these snowpacks release their stored ma-
terials into adjacent ecosystems, such as soils (Jones, 1999; Moorman, 2005) and aquatic environments,
including streams, lakes, rivers, and oceans (Dyurgerov & Meier, 2004; Jansson et al., 2003; Singer et al., 2012;
Slemmons et al., 2013). However, snowpacks are not merely passive reservoirs; they actively interact with other
ecosystems. For example, they exchange microbially derived reactive nitrogen species, such as nitrite (NO₂⁻)
and nitrate (NO₃⁻) (Amoroso et al., 2010), with the atmosphere, thereby influencing its oxidative capacity and
contributing to the formation of nitrogen oxides (NOₓ), which have a significantly greater warming potential
than CO₂ (Rizwan et al., 2024; Smith, 2010; Song et al., 2023). Additionally, undersnow soil microorganisms
have been shown to respire up to 100 g/m² of CO₂ over a winter season (Mariko et al., 2000; Uchida
et al., 2005), indicating that microbial activity persists even under snow cover. Mast et al. (1998) further re-
ported that CO₂ and CH₄ fluxes in seasonally snow-covered terrains accounted for 8%–23% and 12%–58% of
the annual carbon budget, respectively, highlighting the contribution of snow-covered systems to overall
greenhouse gas fluxes. Snowpacks also mediate the exchange of various carbon-containing compounds,
including organic and volatile organic compounds (Pautler et al., 2011; Xu et al., 2010), microbial exopoly-
meric substances (Nagar et al., 2021), humic and humic-like substances (Guzmán et al., 2007), as well as
secondary organic aerosols formed through the oxidation of volatile organic compounds (Seinfeld & Pan-
kow, 2003). These exchanges occur between the snowpack and soils, the atmosphere, and aquatic ecosystems
(Figure 1), suggesting that snow is an active interface in biogeochemical cycling. Furthermore, atmospheric
deposits—such as black carbon, organic carbon particles, and microbial cells—can accelerate snowmelt by
absorbing solar radiation (Intergovernmental Panel on Climate Change [IPCC], 2022; Qian et al., 2015). This
meltwater mobilizes dissolved organic carbon into pro-glacial rivers, enhancing downstream carbon transport
(IPCC, 2022). Collectively, these findings demonstrate that snow environments function as dynamic regulators
of water, nutrients, pollutants, and greenhouse gases across ecosystems. Microbial activity, even during winter,
appears to be a central driver of these carbon transformations and exchanges.

Snowpack microbial communities contribute to carbon cycling through processes such as carbon fixation, pri-
marily by photosynthetic microalgae and cyanobacteria (Boetius et al., 2015; Cheah et al., 2015; Sciuto &
Moro, 2015; Zhao & Su, 2014), and decomposition of organic matter via respiration, fermentation, and methane
cycling (Blanc-Betes et al., 2016; Uchida et al., 2005). Although the relative magnitude of these processes in the
global carbon budget remains poorly constrained, they may be locally significant, particularly in cryospheric
environments where microbial activity can persist throughout winter. Snow cover plays a critical role in medi-
ating these microbial processes by insulating underlying environments from extreme temperature fluctuations,
influencing trophic interactions within snow ecosystems (Penczykowski et al., 2017), as well as regulating
microbial biomass in underlying soil (Freppaz et al., 2014; Larsen et al., 2007). Snow depth manipulation field experiments have shown that snow removal leads to a significant reduction in the abundance of decomposers in the underlying soil; however, this did not translate to decreased decomposition rates in all treatments, suggesting a potential decoupling between microbial community shifts and organic matter breakdown during winter (Bokhorst et al., 2013). Changes in snowpack persistence and depth could therefore alter microbial community structure and abundance, potentially shifting the balance between carbon accumulation and consumption.

Microbial processes in undersnow soils and permafrost—such as insulation from environmental extremes, shifts in biomass, and altered organic matter decomposition—are relatively well documented. However, the extent to which similar processes occur within the snowpack itself remains poorly understood. For instance, we lack detailed knowledge about how snowpack microbial communities respond to environmental changes or contribute to in situ carbon transformation. This represents a critical research gap, particularly in the context of climate-driven changes to snow cover duration, depth, and quality. Addressing this gap through targeted snowpack studies is essential to fully understand winter carbon cycling across cryospheric ecosystems.

## 2. Organic Carbon Deposition and Importance of Studying It in Snow

Snowpacks are closely connected to the atmosphere, forming from snow deposits that include water, dissolved compounds, gases, volatile substances, and atmospheric particulate matter (PM). They continuously accumulate atmospheric particles through both wet and dry deposition (Ibrahim et al., 1983; Kajino & Aikawa, 2015). Atmospheric PM is diverse, consisting of a mix of solid particles and liquid droplets. Its chemical makeup includes organic matter (OM) such as plant debris, pollen, microorganisms, and carbon compounds. The presence of carbohydrates in atmospheric aerosols is well established as a component of the organic fraction of PM (Barbaro et al., 2015, 2017; Simoneit, Elias, et al., 2004; Simoneit, Kobayashi, Mochida, Kawamura, & Huebert, 2004; Simoneit, Kobayashi, Mochida, Kawamura, Lee, et al., 2004; Yttri et al., 2007), but only a few of these compounds have been studied after deposition in snow and ice (Barbaro et al., 2017; Gambaro et al., 2008; Kang et al., 2021; Kehrwald et al., 2012; Pokhrel et al., 2020; You, 2021; You, Song, et al., 2016). More recently, Li et al. (2022) quantified different classes of water-soluble carbon compounds (carbohydrates, lipids, lignin, protein/amino sugar, and hydrocarbons) in different Tibetan glaciers and highlighted their role in glacier melt and its potential impact on the carbon and hydrological cycles. Carbohydrates are categorized into simple and complex sugars, sugar alcohols, and anhydrosugars and their presence in snow and ice cores has been used as tracers of biological activity in some studies (Antony et al., 2014, 2016; Bauer et al., 2008; Nagar et al., 2021). For instance, glucose is the most diffused monosaccharide in living organisms due to its stable structure and low rate of glycosylation (Bunn & Higgins, 1981), and the sugar alcohols, mannitol and arabitol, are contained in fungal spores, lichens, and bacteria (Bauer et al., 2008; Medeiros et al., 2006; Oduber et al., 2021). Sucrose and fructose are common plant-derived sugars, found across a wide range of taxa (Komor, 2000; Lemoine et al., 2013; Martin et al., 1988; Semenzato, 1995), and 2-methyl-D-erythritol is a sugar naturally produced by enzymatic activity in many plants (Jacobsen & Anthonsen, 2015). Other sugars, such as levoglucosan, galactosan, and mannosan, can be used as proxies of nonbiological activities, like biomass burning events (Fabbri et al., 2009; Kehrwald et al., 2012; Massimi et al., 2020; Oduber et al., 2021; Simoneit et al., 1999; You, Yao, et al., 2016).

PM deposition has been shown to vary temporally and regionally depending on particle size (Grantz et al., 2003). Before being deposited in the snow, the particles present in the atmosphere are transported following complex and regionally distinct patterns. For example, in the Mediterranean area, the circulation is characterized by a cold and a warm period, with cyclonic and anticyclonic activity (Maheras et al., 1999). During the cold period, wet deposition (rainout—in-cloud scavenging and washout—below-cloud scavenging) plays a key role for the removal of particles from the air (Kallos et al., 2007). Atmospheric particles, such as PM, biological debris and microbial cells, play a widely recognized role in the formation of cloud condensation nuclei (CCN) and ice nuclei (IN) by recalling water (Mikhailov et al., 2019; Mohler et al., 2007). After condensation, the droplets fall in the form of rain or snow, transporting and depositing the particles that initially formed CCN or IN into snowpacks. This mechanism of particle removal from the air could be a way through which microorganisms and carbon compounds are deposited in snowpacks (Mohler et al., 2007). Differences in circulation patterns, wet deposition, cloud, and ice nucleation processes likely contribute to seasonal, regional, and temporal variations of sugar and microbial content in snow.
Most research on suspended PM primarily emphasizes the impacts on human health, since the smallest particles such as PM<sub>2.5</sub> (particles <2.5 µm) and PM<sub>10</sub> (particles <10 µm) have been classified as carcinogens (Group I) by the International Agency for Research on Cancer (IARC), due to their link to lung cancer development. However, the assessment of PM post-deposition effects on ecosystems, including snowpacks, has received considerably less attention. The components of the organic phase of PM (OM), and carbon compounds like carbohydrates in particular, are still poorly studied in snow. Yet, snowpacks are dynamic biogeochemical systems where deposited PM may alter microbial activity, nutrient availability, albedo, and the fate of carbon compounds (Barbaro et al., 2017; Bergk Pinto et al., 2019; Freppaz et al., 2014; IPCC, 2022; Keuschnig et al., 2023).

### 3. In Situ Sugar Cycling in Snowpacks and Links to Microbial Activity

In addition to the atmospheric input of sugars, microorganisms inhabiting the snow likely influence the in situ carbohydrate content. Not only do their cells contain sugars, microorganisms are also able, if they are active, to produce and metabolize carbon compounds (Bergk Pinto et al., 2019). Since snow hosts a variety of living organisms like microalgae, bacteria, fungi, lichen pieces, protozoa, and rotifers (Hoham, 1989), their activity is likely to modify snow carbohydrates. Although these snow-dwelling microorganisms face low temperatures (almost always below 0°C), usually acidic pH (Greilinger & Kasper-Giebl, 2021), limited nutrient availability, alternating cycles of freezing, thawing, and drying, and high UV light exposure in surface layers of the snow environment (Komárek & Nedbalová, 2007), they have been shown to be active in snow and not only trapped in a vegetative stage waiting for better conditions (Bergk Pinto et al., 2019; Bradley et al., 2023; Elster et al., 2007; Hoham, 1989; Keuschnig et al., 2023; Krug et al., 2020; Larose et al., 2013; Maccario et al., 2014, 2015; C. Zhu et al., 2020). In several studies, bacterial activity was found at temperatures down to -20°C in sea ice (Junge et al., 2003, 2004, 2006) and even down to -39°C in soil (Brooks et al., 1996, 2011; Panikov et al., 2006). Such microbial activity plays a crucial role in carbon cycling within the snowpack, as microbes actively degrade and synthesize essential biomolecules. In particular, sugars can be readily metabolized, transformed, and stored by these microorganisms (Gunina & Kuzyakov, 2015).

As mentioned above, some types of sugars (polysaccharides) are part of the structure of all living cells (Darvill et al., 1985; Held et al., 2014; Teeling et al., 2016; Ullah et al., 2021); thus, bacteria, fungi, and microalgae themselves can be sources of sugars. In a study by Tanaka et al. (1990), the percent sugar composition (mainly monosaccharides and polysaccharides) per weight of pure cultures of bacteria, soil-extracted bacteria, and soil-extracted fungi was determined (Table 1). They found that the most abundant sugar present inside microbial cells was glucose, while the most abundant component sugar of extracellular polysaccharide was mannose (polyol from which mannitol derives) in all the investigated cells. These structural sugars can be a source of energy when microbial cells die and are scavenged by the other microorganisms (Bayer et al., 2004; Buchan et al., 2014; Shoham et al., 1999; Teeling et al., 2016). Furthermore, the molecular weight of sugars can also influence the rate of metabolization from microorganisms. As shown by Antony et al. (2012), bacteria preferred high molecular weight (ex: starch) to low molecular weight substrates (e.g., glucose). Thus, these living microorganisms can influence the different inputs, consumption, and production of sugars in snow, potentially changing the carbohydrate pool content and altering snow chemistry.

Not only bacteria and fungi impact sugar cycling in snowpacks, but microalgae and insects as well. The carbohydrate pool in snow can be influenced by the presence of some Chlorophyta (also called green algae), such as the microalgae *Sanguina sp.* (Maréchal & Nedbalová, 2022; Procházková et al., 2019) and *Chlamydomonas sp.* (Remias et al., 2005), which were reported to cause red or orange coloration of snow in the European Alps (Maréchal & Nedbalová, 2022). Green algae store carbohydrates as starch in their plastids (Ball et al., 2011). This polysaccharide can be an important source of energy for microorganisms. In fact, some bacteria have demonstrated high specialization in polysaccharide degradation when algae die, indicating their tendency to take advantage of the new energy source (Teeling et al., 2016). Microorganisms in snowpacks likely also contribute to sugar production and recycling, but these processes have mostly been assessed in soil (Basler et al., 2015a, 2015b; Derrien et al., 2007; Gunina & Kuzyakov, 2015; Tanaka et al., 1990). Some examples of recycled sugars are arabinose and xylose that are known to be de novo synthesized by soil bacteria. Galactose and rhamnose, which are slowly recycled in soil, but result in a very long mean residence time, are also known to be synthesized by bacteria (Basler et al., 2015a). The disaccharide, trehalose, and the polyol sorbitol have also been reported as biosynthesized by bacteria in response to osmotic stress (Loos et al., 1994; Styrvold & Strøm, 1991). It is possible
<table><caption>**Table 1**

Sugar Composition of Microbial Cells, the Results Are Expressed in Percentage per Weight</caption><thead><tr><th>Microorganism and source of sugars</th><th>Glucose</th><th>Galactose</th><th>Mannose</th><th>Arabinose + Fucose + Fructose</th><th>Xylose</th><th>Ribose</th><th>Rhamnose</th></tr></thead><tbody><tr><td colspan="8"><strong>Pure cultures</strong></td></tr><tr><td>Bacillus subtilis</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cell<sup>a</sup></td><td>45.9</td><td>26.2</td><td>8.9</td><td>n.a.</td><td>n.a.</td><td>14.8</td><td>4.3</td></tr><tr><td>EPS<sup>b</sup></td><td>10.1</td><td>n.a.</td><td>89.9</td><td>n.a.</td><td>n.a.</td><td>n.a.</td><td>n.a.</td></tr><tr><td colspan="8"><strong>Pseudomonas fluorescens</strong></td></tr><tr><td>Cell<sup>a</sup></td><td>42.0</td><td>n.a.</td><td>4.6</td><td>n.a.</td><td>n.a.</td><td>16.3</td><td>37.0</td></tr><tr><td>EPS<sup>b</sup></td><td>17.7</td><td>4.5</td><td>58.4</td><td>n.a.</td><td>n.a.</td><td>1.0</td><td>18.4</td></tr><tr><td colspan="8"><strong>Microbial groups extracted from an Ando soil</strong></td></tr><tr><td>Bacteria</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Cell<sup>a</sup></td><td>33.1</td><td>13.5</td><td>5.7</td><td>5.3</td><td>n.a.</td><td>29.1</td><td>13.5</td></tr><tr><td>EPS<sup>b</sup></td><td>6.5</td><td>1.2</td><td>96.6</td><td>0.6</td><td>n.a.</td><td>0.3</td><td>0.2</td></tr><tr><td colspan="8"><strong>Actinomyces</strong></td></tr><tr><td>Cell<sup>a</sup></td><td>13.6</td><td>16.0</td><td>41.4</td><td>10.7</td><td>n.a.</td><td>11.8</td><td>6.5</td></tr><tr><td>EPS<sup>b</sup></td><td>1.3</td><td>0.4</td><td>97.9</td><td>0.1</td><td>n.a.</td><td>0.2</td><td>n.a.</td></tr><tr><td colspan="8"><strong>Fungi</strong></td></tr><tr><td>Hyphae</td><td>97.1</td><td>1.2</td><td>0.7</td><td>1.1</td><td>n.a.</td><td>n.a.</td><td>n.a.</td></tr></tbody></table>

Note. Data from Tanaka et al. (1990). <sup>a</sup>Cell—cell compounds. <sup>b</sup>EPS—extracellular polysaccharides; n.a.—data not available.

that active microorganisms in snowpacks might also be able to carry out these reactions, but the literature is currently sparse.

Furthermore, trehalose, glycerol, and glucose, which can act as antifreeze compounds (Vanin et al., 2008), are produced by some typical snow insects, such as *Chionea sp.*, *Boreus hiemalis*, and cantharids (Vanin et al., 2008). Sucrose, trehalose, sorbitol, and inositol have been reported as having similar functions in cold-adapted microalgae (Valledor et al., 2013) and higher plants (Iordachescu & Imai, 2008; Uemura & Steponkus, 2003). This means that all the living organisms (such as bacteria, fungi, microalgae, and insects) can influence carbohydrate concentrations in the environment. However, in snowpacks, the specific sources, transformation pathways, and persistence of sugars remain poorly characterized. It is critically important to understand how microorganisms contribute to sugar cycling after deposition because these processes may regulate microbial survival, community assembly, and biogeochemical activity in snow-covered ecosystems, in addition to community functioning (Bergk Pinto et al., 2019). Furthermore, microbial transformation of carbon sources like sugars could influence the timing and composition of carbon release during snowmelt, with downstream impacts on nutrient dynamics in adjacent soils and aquatic systems. Priority areas for investigation include identifying the active microbial taxa involved in sugar metabolism, quantifying the rates of sugar production and degradation, and determining how these processes respond to environmental change.

# 4. Seasonality and Geographical Location Influencing Snow Sugars

Atmospheric deposition and biological activity are not the only factors influencing the sugar content in snow, different factors, such as seasonality and geographical location of snowpacks, might also be important.

## 4.1. Seasonal Production of Sugars

As introduced in Section 2, snowpacks are continuously seeded by atmospheric particles, including airborne sugars whose concentrations and compositions vary seasonally. For instance, during the colder months, aerosols are enriched in biomass-burning tracers such as levoglucosan, galactosan, and mannosan (Fabbri et al., 2009; Kehrwald et al., 2012; Massimi et al., 2020; You & Xu, 2018; You, Song, et al., 2016; You, Yao, et al., 2016; Zangrando, Barbaro, Kirchgeorg, et al., 2016; Zangrando, Barbaro, Vecchiato, et al., 2016). In contrast, as the season progresses, there is an increase in more bioavailable sugars, likely associated with enhanced biological
activity and airborne vegetation input (Barbaro et al., 2015; Feltracco et al., 2020; Fu et al., 2012; Medeiros et al., 2006). These atmospheric inputs are key drivers of the carbohydrate profile found in snowpacks after deposition (Barbaro et al., 2017). Terrestrial biomass, including plant detritus, lichen, fungal spores, and microbial cells, such as bacteria and microalgae, has been identified as a primary source of atmospheric sugars (Medeiros et al., 2006). Because of this, the type and condition of vegetation near snowpacks are critical for shaping the carbohydrate and microbial profiles of the snow. Vegetation undergoes altitudinal and seasonal changes in phenology (i.e., shifts between dormancy, active growth, flowering, and senescence) driven by factors such as daylength, temperature, solar radiation, and snow cover duration (Asam et al., 2018; Thomson, 1995). For example, while temperature correlates most strongly with phenological changes at lower elevations (<1,000 m a. s.l.), snow cover duration is the dominant driver at higher elevations (Asam et al., 2018). These climate-sensitive phenological patterns influence the timing and quantity of sugar emissions into the atmosphere. Consequently, seasonal shifts in vegetation activity may have an impact on the quantity and type of sugars deposited into snowpacks, either through local deposition or long-range transport. Understanding how seasonality shapes sugar inputs is essential for interpreting snowpack microbial dynamics and their biogeochemical roles.

As demonstrated by Medeiros et al. (2006) in a study conducted in a boreal conifer forest, glucose was the dominant monosaccharide in aerosols during the spring plant growing season, reflecting plant metabolic activity. However, its concentration declined as the season progressed. In contrast, during autumn—when vegetation enters the senescence phase—polyols such as mannitol and arabitol became more abundant, also indicating increased activity from fungi, bacteria, and lichens. Similarly, fructose and sucrose, which are primarily associated with flower development (Bieleski, 1995), were elevated only during spring, underscoring the importance of phenological events in shaping sugar composition. These seasonal shifts in airborne sugar composition, driven by the timing of plant and microbial processes, are likely reflected in the snowpack following atmospheric deposition. During spring, elevated concentrations of glucose and other plant-derived sugars would be expected in the snow, while in autumn, the increased presence of microbial tracers such as polyols may become more prominent. Since atmospheric deposition is a key pathway for the incorporation of sugars into snow, the seasonal progression of vegetation activity not only shapes aerosol sugar composition but might also contribute to the evolving carbohydrate profile of the snowpack over time.

## 4.2. Geographical Location Impacting Carbohydrate Input

In addition to the impact of seasonality, the geographic location likely plays a significant role in atmospheric sugar input to snowpacks. Snowpack composition is largely dependent on atmospheric deposition, and areas with contrasting land usages emit and aerosolize PM and microbial communities that seed the atmosphere differently. The impact of land use, for example, urban (areas with high traffic volume, high human population density, and low vegetation coverage), rural (open areas characterized by agricultural activities), and forest (areas with low population density, low traffic, and high vegetation cover), on aerosol composition has been investigated extensively (Caetano-Silva et al., 2013; Massimi et al., 2020; Tominaga et al., 2011; Yttri et al., 2007; Zangrando, Barbaro, Kirchgeorg, et al., 2016; R.-G. Zhu et al., 2022). To illustrate differences in sugar aerosol concentrations in relation to geographic areas and seasons, the results from studies conducted during spring, fall, and year-round comparing urban, rural, and forest PM<sub>2.5</sub> aerosol sugar composition (primary sugars, sugar alcohols, and anhydrosugars) in Norway by Yttri et al. (2007) and China by R.-G. Zhu et al. (2022) are presented in Table 2. R.-G. Zhu et al. (2022) reported a significant difference in average sugar concentrations among sites during the spring, with a higher concentration of almost all the sugars analyzed, except for glucose, fructose, and sucrose, in the urban area compared to rural and forested areas. In particular, anhydrosugars (such as levoglucosan, mannosan, and galactosan) displayed higher average concentrations in urban areas compared to rural and forested areas—values comparable to those reported by Yttri et al. (2007) for similar environments (see Table 2). The ratio between levoglucosan and mannosan (L/M ratio) enables the identification of specific burning substrates (Fabbri et al., 2009; Fan et al., 2020; C. Zhu et al., 2015). In R.-G. Zhu et al. (2022), L/M ratio values in urban areas ranged from 14 to 30, typically representing hardwood combustion (Krůmal et al., 2010; Schmidl et al., 2008; Wang et al., 2021; R.-G. Zhu et al., 2022), while in rural and forested areas, ratios fell within the range of softwood combustion (between 3 and 10), reflecting the dominance of softwood plant cover.

Beyond anhydrosugar ratios, the distribution of primary sugars also varied across sites. Fructose, glucose, and sucrose were the dominant sugars in all locations, but trehalose concentrations were substantially higher in urban areas than in rural and forested ones (Table 2). Given that trehalose is one of the most abundant sugars in soil
<caption>**Table 2**</caption>

PM<sub>2.5</sub> Aerosol Sugar Comparison Between Urban, Rural, and Forest Areas, From the Studies of Yttri et al. (2007) and Recalculated Values From Supp. Table R.-G. Zhu et al. (2022)

<table><thead><tr><th rowspan="2">Study<br>Area of study</th><th colspan="2">Yttri et al. (2007)</th><th colspan="3">R.-G. Zhu et al. (2022)</th></tr><tr><th>Urban (9 September to 3 October 2002)</th><th>Rural (Entire year 2002)</th><th>Urban (averaged 30 April to 13 May 2019)</th><th>Rural (averaged 30 April to 13 May 2019)</th><th>Forest (averaged 30 April to 13 May 2019)</th></tr></thead><tbody><tr><td><strong>Primary sugar</strong></td><td colspan="2">PM<sub>2.5</sub> ng/m<sup>3</sup> (min-max)</td><td colspan="3">PM<sub>2.5</sub> ng/m<sup>3</sup> (min-max)</td></tr><tr><td>Fructose</td><td>3,3 (n.d.–5.1)</td><td>0,57 (n.d.–3.3)</td><td>16,2 (n.d.–30.3)</td><td>15,6 (5.6–60.5)</td><td>19,6 (3.1–34.4)</td></tr><tr><td>Glucose</td><td>7,2 (4.3–12)</td><td>1,2 (0.36–4.4)</td><td>28,4 (11.2–52.9)</td><td>21,9 (13.6–35.6)</td><td>29,5 (14.7–54.7)</td></tr><tr><td>Sucrose</td><td>15 (0.36–4.4)</td><td>0,8 (0.16–6.4)</td><td>39,8 (n.d.–86.6)</td><td>27,6 (n.d.–123.3)</td><td>51,8 (n.d.–171.7)</td></tr><tr><td>Trehalose</td><td>5,3 (n.d.–11)</td><td>0,8 (0.14–3.9)</td><td>28,3 (n.d.–255.9)</td><td>2,4 (n.d.–15.5)</td><td>7,2 (n.d.–48.3)</td></tr><tr><td><strong>Sugar alcohols</strong></td><td colspan="2"></td><td colspan="3"></td></tr><tr><td>Arabitol</td><td>1 (n.d.–2.6)</td><td>0,4 (n.d.–0.89)</td><td>11,9 (0.5–32.7)</td><td>6,4 (4.1–12.3)</td><td>9,2 (3.7–17.3)</td></tr><tr><td>Mannitol</td><td>1,6 (n.d.–4.2)</td><td>0,3 (n.d.–0.87)</td><td>83,8 (n.d.–161.2)</td><td>47,4 (28.9–103.4)</td><td>66,5 (23.8–134.1)</td></tr><tr><td><strong>Anhydrosugars</strong></td><td colspan="2"></td><td colspan="3"></td></tr><tr><td>Levoglucosan</td><td>193 (n.d.–475)</td><td>7,8 (0.3–25)</td><td>83,4 (2.0–164.6)</td><td>37,6 (19.4–67.2)</td><td>54 (22.2–109.7)</td></tr><tr><td>Mannosan</td><td>52 (n.d.–155)</td><td>1,9 (0.1–6.9)</td><td>4,45 (n.d.–16.8)</td><td>47,5 (2.9–9.4)</td><td>7,9 (3.6–20.3)</td></tr><tr><td>Galactosan</td><td>1,7 (n.d.–6.9)</td><td>0,6 (n.d.–2.3)</td><td>0,2 (n.d.–1.1)</td><td>1,3 (n.d.–5.8)</td><td>n.d.</td></tr></tbody></table>

Note. In order to compare the two studies, the weekly values from R.-G. Zhu et al. (2022) were averaged. Only sugars analyzed in both studies are presented. Values are expressed in ng/m³, with minimum (min) and maximum (max) values detected. n.d.—not detected.

(Simoneit, Elias, et al., 2004), R.-G. Zhu et al. (2022) hypothesized that this pattern reflects a stronger influence of soil and road dust resuspension in urban settings. These findings suggest that snowpacks located near urban, rural, or forested areas are exposed to distinct atmospheric deposition fluxes of sugars, shaped by regional combustion sources and resuspension of terrestrial material.

Snowpacks located in remote areas, like alpine, polar, or subpolar environments, can also receive sugars from urban areas through long range transport. Barbaro et al. (2015) studied different sugars in Antarctic aerosols and found that the major component of the total PM<sub>10</sub> concentration was glucose, making up 60% of the sugar biomass. In order to attribute a source to this glucose, Barbaro et al. (2015) analyzed the ratio between glucose and levoglucosan, with values higher than 4.5 being attributed to smoke-free samples (Medeiros et al., 2006). The ratios reported by Barbaro et al. (2015) were >9, leading the researchers to hypothesize that the source of sugars in Antarctic aerosols was mainly of local biological origin, such as microbial decomposition processes (Jia & Andy Fraser, 2011) or bubble bursting from the sea that contribute to spraying particles into aerosol (Crahan et al., 2004; Hawkins & Russell, 2010; Russell et al., 2010). In contrast to locally derived sugars, levoglucosan is often used as a tracer for the long-range transport of aerosols because it is a specific byproduct of cellulose combustion and it is stable in the atmosphere (Locke, 1988). Levoglucosan presence is therefore strongly indicative of biomass burning events occurring at a distance from the deposition site. In Kehrwald et al. (2012), the post-deposition traces of levoglucosan were investigated in snowpacks at the North Greenland Eemian Ice Drilling (NEEM) site (77°26′N, 51°30′W), a remote point located at 2,461 m a.s.l in Greenland. The study elucidated how levoglucosan can be used as a tracer for natural fire events and the air mass trajectory analysis identified North American boreal forest fires as the source.

In conclusion, snowpacks can form in different zones of Earth that can be more or less in proximity to urban inputs. Based on the literature available for aerosol studies, the atmospheric sugar composition varies depending on the surrounding landscapes. Since snow is connected to the atmosphere, this would suggest that different atmospheric sugar depositions can lead to a snow carbohydrate composition that varies as a result of geographic location, but this is still a relatively underexplored field of research.
**5. Biological Variables**

Microorganisms are deposited in snowpack through wet and dry deposition processes (Aikawa et al., 2014; Ibrahim et al., 1983; Kajino & Aikawa, 2015; Mikhailov et al., 2019; Mohler et al., 2007). After deposition, they can undergo selective processes (Keuschnig et al., 2023; Sanchez-Cid et al., 2023), leading to the establishment of snow-specific microbial communities (Els et al., 2019; Maccario et al., 2019). Since not all deposited microbes can survive in their new environment, some may enter dormancy (Bradley et al., 2023), while others remain active under subzero temperatures, potentially metabolizing available organic carbon compounds (Bergk Pinto et al., 2019; Keuschnig et al., 2023), including sugars.

**5.1. Seasonality Influencing Biological Activity and Community Composition**

Seasonality influences not only sugar and particle inputs to snowpacks that act as substrates for microbial activity but also the habitat constraints of the snowpack itself. Season drives differences in UV light radiation, freezing cycles, and precipitation that can impact microbial community activity and functioning within snow-packs (Kallos et al., 2007; Keuschnig et al., 2023; Komárek & Nedbalová, 2007; Maccario et al., 2015; Sanchez-Cid et al., 2023). Several studies (Bergk Pinto et al., 2019; Els et al., 2019; Larose et al., 2013; Y. Liu et al., 2006; Winkel et al., 2022) on snow microbial communities identified seasonal variations of the community structure. In all of the areas investigated during these studies (Austria, Arctic Archipelago of Svalbard, Iceland, and Mt. Everest), the ecosystem of microinhabitants showed a clear shift from the summer to winter season. In particular, the study of Els et al. (2019) reported that the snow community structure changed seasonally for both bacterial and fungal communities. These shifts suggest that not only are microbial communities seasonally distinct but their metabolic potential in processing sugars and other organic compounds may vary as well. This was shown in a field experiment where increases in organic carbon concentration shifted community functioning and microbial interactions (Bergk Pinto et al., 2019). Thus, microbial consumption and transformation of deposited sugars could influence the longevity and bioavailability of these compounds within the snowpack, impacting carbon cycling processes at seasonal scales.

To conclude, microbial communities vary seasonally in composition, but also between the atmosphere and snowpacks. As pointed out in the previous sections, microbial presence and activity plays a fundamental role in sugar content in all ecosystems. Understanding how seasonal microbial succession influences sugar degradation and transformation in snowpacks remains a critical knowledge gap. Investigating which taxa contribute to sugar metabolism in different seasonal phases could improve our understanding of microbial roles in snowpack organic carbon dynamics and their implications for carbon cycling.

**5.2. Geographic Location Influencing Microbial Communities**

Snowpack microbial communities are predominantly seeded by the atmosphere, and the composition of airborne microorganisms can vary substantially across geographic regions (Tignat-Perrier et al., 2019). Studies on atmospheric microbial communities showed that airborne microbial communities differ between urban and rural environments (Huttunen et al., 2010; Kaarakainen et al., 2008; H. Liu et al., 2019). For instance, H. Liu et al. (2019) found that urban aerosols in Hangzhou, China were dominated by Proteobacteria and Actinobacteria, while rural air was enriched in fungal taxa such as Ascomycota and Basidiomycota. These findings suggest that snowpacks, which accumulate atmospheric deposits over time, may host distinct microbial communities depending on location and surrounding land use. Azzoni et al. (2018) similarly demonstrated significant differences in snow bacterial communities across glaciers located near urban centers (Forni Glacier, Italy) versus more remote mountain environments (e.g., Ararat in Turkey, Baltoro in Pakistan, and Khumbu in Nepal). Differences were evident in both alpha and beta diversity and taxonomic composition, highlighting that geographic location plays a key role in shaping snow microbiomes. However, while compositional differences are well-documented, less is known about how these microbial shifts translate into functional consequences, particularly in the degradation and transformation of carbon compounds such as sugars. Since microbial communities mediate sugar breakdown and recycling, geographic differences in community composition may lead to region-specific metabolic pathways and carbon turnover rates in snowpacks. This represents a critical knowledge gap in our understanding of how microbial biogeography impacts snow carbon cycling. Future work should aim to link atmospheric seeding patterns, snowpack microbial composition, and in situ metabolic activity to fully understand the ecological role of snow microbiomes across diverse environments.
## 6. Sugar Transition: From Snow to Ice

Sugars deposited in snowpacks can serve as valuable tracers of atmospheric processes, biological activity, and environmental change occurring in terrestrial habitats. Understanding how these carbohydrates transition from snow to ice is crucial, particularly for interpreting their preservation in ice cores and assessing their reliability as historical proxies for land use and vegetation. As stated in Section 1, snowpacks are defined as the layered accumulation of snow, derived from various snowfall events (Oliver, 2008). At high latitudes and altitudes, where the temperature remains below the melting point, the amount of annually deposited snow is greater than the amount of snow that melts (T. Schultz et al., 2021) and this results in a stable, but evolving accumulation. Snow older than 1 year old is called “firn” and it can undergo transformation into ice through a sintering process, increasing the density gradually until ice density (ice = 917 kg/m³) is reached (T. Schultz et al., 2021; Schüpbach et al., 2016). The amount of air trapped in the pores between snow and firn grains decrease significantly until the pores are closed off completely, trapping air in the ice (T. Schultz et al., 2021; Schüpbach et al., 2016). Air bubbles in ice are especially valuable for studying atmospheric parameters, as direct measurements are unavailable prior to the 1970s (M. G. Schultz et al., 2015). Air bubbles in ice trap atmospheric gases such as CO₂ and CH₄, whose connection to climate and temperature increases has been validated by the International Panel on Climate Change (IPCC, 2023). Additionally, the ice contains water isotopes, like δ¹⁸O, essential for estimating snow accumulation rates, and other geochemical tracers, like δ¹⁵N, which aids in reconstructing past firn depth (Capron et al., 2013). A variety of different particles can also be found stored in ice. For example, pollen grains are commonly studied in ice cores from mountain glaciers at low to midlatitudes to identify annual or seasonal layers and reveal past vegetation near the glacier due to their seasonal release patterns (Takeuchi et al., 2019).

Carbohydrates have also been quantified in snow and ice to trace past natural events, like forest fires, or biomass combustion. For example, the anhydrosugars (levoglucosan, mannosan, and galactosan) were quantified in Antarctic (Gambaro et al., 2008) and Alaskan (Pokhrel et al., 2020) ice cores, as well as snow from Greenland (Kang et al., 2021; Kehrwald et al., 2012) and snow and ice from a Tibetan glacier (You, 2021; You, Song, et al., 2016). As anhydrosugars are considered atmospheric tracers of biomass burning and fire events (Barbaro et al., 2019, 2020; Kang et al., 2021; Kehrwald et al., 2012; Pokhrel et al., 2020; Simoneit et al., 1999; You & Xu, 2018; Zangrando, Barbaro, Vecchiato, et al., 2016), their presence and quantification in ice cores can provide valuable information concerning the occurrence of these episodes. Since sugars like glucose, sucrose, 2methyl-erithritol, mannitol, arabitol, and inositol are significantly correlated with airborne bacteria, fungal spores, and pollen concentrations (Bauer et al., 2008; Medeiros et al., 2006; Oduber et al., 2021), they are potentially good tracers of past biological activity and changes. However, as discussed in previous chapters, microbial activity can significantly influence carbohydrate degradation and production in snowpacks, potentially modifying carbohydrate content in snow before it transitions and stabilizes into ice. Thus, carbohydrate measurements obtained from ice cores may not accurately reflect past atmospheric content due to post-depositional microbial activity altering sugar concentrations over time. To improve reconstructions of past atmospheric sugar deposition, future studies should integrate microbial community analysis or compound-specific degradation assessments—such as stable isotope labeling, molecular-level degradation markers, or enzymatic activity profiling—to distinguish atmospheric inputs from in situ transformations.

Another important consideration is the ongoing evolution of climate change, which is progressing at an increasingly rapid pace. According to the IPCC published in 2022, each of the last four decades has been successively warmer than any decade that preceded it since 1850. The global surface temperature in the first two decades of the 21st century (2001–2020) was 0.99°C (0.84°C–1.10°C) higher than 1850–1900. This warming has a number of observed consequences including the global retreat of glaciers since the 1990s (IPCC, 2022), large warming trends at low elevations (<1,000 m a.s.l.) in winter and increasingly larger warming rates at high elevations (>2,000 m a.s.l.) in summer in the Alps (Beaumet et al., 2021), decline of winter snow depth and cover duration from –7% to –15% and –5 to –7 days per decade, respectively, in Europeans Alps (Monteiro & Morin, 2023), and globally in mountain areas of ~–4% to –6% for yearly snow cover extent and of ~–15 to 27 days for snow cover duration in the period 1982–2020 (Notarnicola, 2022). This means that these frozen archives are disappearing, putting valuable information about past climate at risk of being lost.

Studying sugar dynamics in snow ecosystems presents methodological challenges due to the complexity of snow deposition, microbial activity, and environmental variability. Snow manipulation experiments, such as those
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Knowns and unknowns in biological sugar cycling in snowpacks.</figcaption></figure>

reviewed by Wipf and Rixen (2010), provide valuable insights into how changes in snow cover affect underlying ecosystem processes. These experiments, which modify snow depth or timing of snowmelt, have been instrumental in understanding plant and soil-microorganisms responses to snowpack changes. However, the production, transformation, and persistence of carbohydrates within the snowpack remain poorly understood. We can address this gap by applying similar experimental approaches, combined with high-resolution biochemical and microbial analyses, addressing existing knowledge gaps in snowpack carbon cycling, particularly the microbial processing of sugars. Given the rapid pace of climate change, it is essential to promptly improve our understanding of sugar-related processes in snowpacks, as they offer valuable insights into both current microbial activity and past vegetation, which may soon be lost.

## 7. General Conclusions and Perspectives

Rapid changes in snow-covered areas due to climate change pose significant challenges, as the loss of snow and ice disrupts critical carbon and nutrient cycles. Snowpacks act as transient reservoirs for organic carbon and microbial life, linking atmospheric deposition, microbial metabolism, and environmental transformations (Figure 2). While research has identified key drivers—such as seasonal deposition patterns, microbial activity, and geographic influences—major uncertainties remain in understanding how these processes interact and evolve under warming conditions. Addressing these uncertainties is crucial for predicting the role of snowpacks in global biogeochemical cycles.

One key knowledge gap lies in the microbial cycling of carbohydrates within snowpacks. Snow-dwelling microorganisms, including bacteria, fungi, and microalgae, can produce, consume, and transform sugars even at subzero temperatures. However, these metabolic processes remain poorly understood. Post-depositional processes further complicate our understanding of snowpack chemistry. The transformation of snow into ice can trap atmospheric particles, preserving records of past environmental conditions. However, microbial activity may modify carbohydrate content before stabilization in ice, potentially distorting historical reconstructions. Future research should assess the extent to which microbial processing alters sugar signals in ice cores and how we can refine methodologies to account for these changes in paleoclimate studies.
Understanding the broader implications of microbial activity in snowpacks requires interdisciplinary approaches. Integrating microbial genomics and chemical markers could provide insights into microbial contributions to carbon cycling. Additionally, predictive models linking snowpack microbial processes to regional and global carbon budgets are needed to assess the impact of changing snow cover on atmospheric chemistry.

Given the rapid transformation of snow ecosystems under climate change, advancing our knowledge of microbial-snow interactions is imperative. By addressing these knowledge gaps through field-based studies, laboratory experiments, and modeling efforts, we can improve predictions of how snowpack ecosystems respond to environmental change and refine our understanding of their role in global biogeochemical cycles.

## Data Availability Statement

Data were not used nor created for this research.

## Acknowledgments

Francesca Schivalocchi's PhD is funded by the French National Research Agency under the ANR-21-CE01-0021 program, project: ABS, Atmospheric Biogenic Sugars. Francesca is employed by CNRS (Centre National de la Researche Scientifique), France. Kara Sampsell's PhD is funded by the European Union under the HORIZON-MSCA-2021-DN-01 program, project number 101072761: ICEBIO. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. Kara is employed by Université Grenoble Alpes, France. Christine Piot is employed as the assistant professor at Université Savoie Mont Blanc, Le Bourget du Lac, France and conducts her research activity between EDYTEM (Laboratoire Environnements, Dynamiques et Territoires de Montagne, Université Savoie Mont Blanc) and IGE (Institut des Géosciences de l'Environnement, Université Grenoble Alpes). Catherine Larose is employed as a researcher by CNRS (Centre National de la Researche Scientifique), France and conducts her research activity at IGE (Institut des Géosciences de l'Environnement, Université Grenoble Alpes).

## References

Aikawa, M., Kajino, M., Hiraki, T., & Mukai, H. (2014). The contribution of site to washout and rainout: Precipitation chemistry based on sample analysis from 0.5 mm precipitation increments and numerical simulation. *Atmospheric Environment*, *95*, 165–174. https://doi.org/10.1016/j.atmosenv.2014.06.015

Amoroso, A., Domine, F., Esposito, G., Morin, S., Savarino, J., Nardino, M., et al. (2010). Microorganisms in dry polar snow are involved in the exchanges of reactive nitrogen species with the atmosphere. *Environmental Science & Technology*, *44*(2), 714–719. https://doi.org/10.1021/es9027309

Antony, R., Grannas, A. M., Willoughby, A. S., Sleight, R. L., Thamban, M., & Hatcher, P. G. (2014). Origin and sources of dissolved organic matter in snow on the East Antarctic Ice Sheet. *Environmental Science & Technology*, *48*(11), 6151–6159. https://doi.org/10.1021/es405246a

Antony, R., Mahalinganathan, K., Krishnan, K. P., & Thamban, M. (2012). Microbial preference for different size classes of organic carbon: A study from Antarctic snow. *Environmental Monitoring and Assessment*, *184*(10), 5929–5943. https://doi.org/10.1007/s10661-011-2391-1

Antony, R., Sanyal, A., Kapse, N., Dhakephalkar, P. K., Thamban, M., & Nair, S. (2016). Microbial communities associated with Antarctic snow pack and their biogeochemical implications. *Microbiological Research*, *192*, 192–202. https://doi.org/10.1016/j.micres.2016.07.004

Asam, S., Callegari, M., Matiu, M., Fiore, G., De Gregorio, L., Jacob, A., et al. (2018). Relationship between spatiotemporal variations of climate, snow cover and plant phenology over the Alps—An Earth observation-based analysis. *Remote Sensing*, *10*(11), 1757. https://doi.org/10.3390/rs10111757

Azzoni, R. S., Tagliaferri, I., Franzetti, A., Mayer, C., Lambrecht, A., Compostella, C., et al. (2018). Bacterial diversity in snow from mid-latitude mountain areas: Alps, Eastern Anatolia, Karakoram and Himalaya. *Annals of Glaciology*, *59*(77), 10–20. https://doi.org/10.1017/aog.2018.18

Ball, S., Colleoni, C., Cenci, U., Raj, J. N., & Tirtiaux, C. (2011). The evolution of glycogen and starch metabolism in eukaryotes gives molecular clues to understand the establishment of plastid endosymbiosis. *Journal of Experimental Botany*, *62*(6), 1775–1801. https://doi.org/10.1093/jxb/erg411

Barbaro, E., Feltracco, M., Cesari, D., Padoan, S., Zangrando, R., Contini, D., et al. (2019). Characterization of the water soluble fraction in ultrafine, fine, and coarse atmospheric aerosol. *Science of the Total Environment*, *658*, 1423–1439. https://doi.org/10.1016/j.scitotenv.2018.12.298

Barbaro, E., Kirchgeorg, T., Zangrando, R., Vecchiato, M., Piazza, R., Barbante, C., & Gambaro, A. (2015). Sugars in Antarctic aerosol. *Atmospheric Environment*, *118*, 135–144. https://doi.org/10.1016/j.atmosenv.2015.07.047

Barbaro, E., Morabito, E., Gregoris, E., Feltracco, M., Gabrieli, J., Vardè, M., et al. (2020). Col Margherita observatory: A background site in the Eastern Italian Alps for investigating the chemical composition of atmospheric aerosols. *Atmospheric Environment*, *221*, 117071. https://doi.org/10.1016/j.atmosenv.2019.117071

Barbaro, E., Zangrando, R., Padoan, S., Karroca, O., Toscano, G., Cairns, W. R. L., et al. (2017). Aerosol and snow transfer processes: An investigation on the behavior of water-soluble organic compounds and ionic species. *Chemosphere*, *183*, 132–138. https://doi.org/10.1016/j.chemosphere.2017.05.098

Basler, A., Dippold, M., Helfrich, M., & Dyckmans, J. (2015a). Microbial carbon recycling—An underestimated process controlling soil carbon dynamics—Part 1: A long-term laboratory incubation experiment. *Biogeosciences*, *12*(20), 5929–5940. https://doi.org/10.5194/bg-12-5929-2015

Basler, A., Dippold, M., Helfrich, M., & Dyckmans, J. (2015b). Microbial carbon recycling: An underestimated process controlling soil carbon dynamics—Part 2: A $C_3-C_4$ vegetation change field labelling experiment. *Biogeosciences*, *12*(21), 6291–6299. https://doi.org/10.5194/bg-12-6291-2015

Bauer, H., Claeys, M., Vermeylen, R., Schueller, E., Weinke, G., Berger, A., & Puxbaum, H. (2008). Arabitol and mannitol as tracers for the quantification of airborne fungal spores. *Atmospheric Environment*, *42*(3), 588–593. https://doi.org/10.1016/j.atmosenv.2007.10.013

Bayer, E. A., Belaich, J.-P., Shoham, Y., & Lamed, R. (2004). The Cellulosomes: Multienzyme machines for degradation of plant cell wall polysaccharides. *Annual Review of Microbiology*, *58*(1), 521–554. https://doi.org/10.1146/annurev.micro.57.030502.091022

Beaumet, J., Ménégoz, M., Morin, S., Gallée, H., Fettweis, X., Six, D., et al. (2021). Twentieth century temperature and snow cover changes in the French Alps. *Regional Environmental Change*, *21*(4), 114. https://doi.org/10.1007/s10113-021-01830-x

Bergk Pinto, B., Maccario, L., Dommergue, A., Vogel, T. M., & Larose, C. (2019). Do organic substrates drive microbial community interactions in Arctic Snow? *Frontiers in Microbiology*, *10*, 2492. https://doi.org/10.3389/fmicb.2019.02492

Berrisford, M. S. (1991). Evidence for enhanced mechanical weathering associated with seasonally late-lying and perennial snow patches, Jotunheimen, Norway. *Permafrost and Periglacial Processes*, *2*(4), 331–340. https://doi.org/10.1002/ppp.3430020408

Bhatia, M. P., Das, S. B., Xu, L., Charette, M. A., Wadham, J. L., & Kujawinski, E. B. (2013). Organic carbon export from the Greenland ice sheet. *Geochimica et Cosmochimica Acta*, *109*, 329–344. https://doi.org/10.1016/j.gca.2013.02.006

Bieleski, R. L. (1995). Onset of phloem export from senescent petals of daylily. *Plant Physiology*, *109*(2), 557–565. https://doi.org/10.1104/pp.109.2.557
Blanc-Betes, E., Welker, J. M., Sturchio, N. C., Chanton, J. P., & Gonzalez-Meler, M. A. (2016). Winter precipitation and snow accumulation drive the methane sink or source strength of Arctic tussock tundra. *Global Change Biology*, *22*(8), 2818–2833. https://doi.org/10.1111/gcb.13242

Boetius, A., Anesio, A. M., Deming, J. W., Mikucki, J. A., & Rapp, J. Z. (2015). Microbial ecology of the cryosphere: Sea ice and glacial habitats. *Nature Reviews Microbiology*, *13*(11), 677–690. https://doi.org/10.1038/nrmicro3522

Bokhorst, S., Metcalfe, D. B., & Wardle, D. A. (2013). Reduction in snow depth negatively affects decomposers but impact on decomposition rates is substrate dependent. *Soil Biology and Biochemistry*, *62*, 157–164. https://doi.org/10.1016/j.soilbio.2013.03.016

Bradley, J. A., Trivedi, C. B., Winkel, M., Mourot, R., Lutz, S., Larose, C., et al. (2023). Active and dormant microorganisms on glacier surfaces. *Geobiology*, *21*(2), 244–261. https://doi.org/10.1111/gbi.12535

Brooks, P. D., Grogan, P., Templer, P. H., Groffman, P., Öquist, M. G., & Schimel, J. (2011). Carbon and nitrogen cycling in snow-covered environments: Carbon and nitrogen cycling in snow-covered environments. *Geography Compass*, *5*(9), 682–699. https://doi.org/10.1111/j.1749-8198.2011.00420.x

Brooks, P. D., Williams, M. W., & Schmidt, S. K. (1996). Microbial activity under alpine snowpacks, Niwot Ridge, Colorado. *Biogeochemistry*, *32*(2), 93–113. https://doi.org/10.1007/bf00000354

Buchan, A., LeCleir, G. R., Gulvik, C. A., & González, J. M. (2014). Master recyclers: Features and functions of bacteria associated with phytoplankton blooms. *Nature Reviews Microbiology*, *12*(10), 686–698. https://doi.org/10.1038/nrmicro3326

Bunn, H. F., & Higgins, P. J. (1981). Reaction of monosaccharides with proteins: Possible evolutionary significance. *Science*, *213*(4504), 222–224. https://doi.org/10.1126/science.12192669

Caetano-Silva, L., Allen, A. G., Lima-Souza, M., Cardoso, A. A., Campos, M. L. A. M., & Nogueira, R. F. P. (2013). An analysis of diurnal cycles in the mass of ambient aerosols derived from biomass burning and agro-industry. *Journal of Geophysical Research: Atmospheres*, *118*(15), 8675–8687. https://doi.org/10.1002/jgrd.50630

Cameron, K. A., Müller, O., Stibal, M., Edwards, A., & Jacobsen, C. S. (2020). Glacial microbiota are hydrologically connected and temporally variable. *Environmental Microbiology*, *22*(8), 3172–3187. https://doi.org/10.1111/1462-2920.15059

Capron, E., Landais, A., Buiron, D., Cauquoin, A., Chappellaz, J., Debret, M., et al. (2013). Glacial–interglacial dynamics of Antarctic firn columns: Comparison between simulations and ice core air-δ¹⁵N measurements. *Climate of the Past*, *9*(3), 983–999. https://doi.org/10.5194/cp-9-983-2013

Cheah, W. Y., Show, P. L., Chang, J.-S., Ling, T. C., & Juan, J. C. (2015). Biosequestration of atmospheric CO₂ and flue gas-containing CO₂ by microalgae. *Bioresource Technology*, *184*, 190–201. https://doi.org/10.1016/j.biortech.2014.11.026

Crahan, K. K., Hegg, D. A., Covert, D. S., Jonsson, H., Reid, J. S., Khelif, D., & Brooks, B. J. (2004). Speciation of organic aerosols in the tropical Mid-Pacific and their relationship to light scattering. *Journal of the Atmospheric Sciences*, *61*(21), 2544–2558. https://doi.org/10.1175/JAS3284.1

Darvill, A. G., Albersheim, P., McNEIL, M., Lau, J. M., York, W. S., Stevenson, T. T., et al. (1985). Structure and function of plant cell wall polysaccharides. *Journal of Cell Science*, *1985*(Supplement 2), 203–217. https://doi.org/10.1242/jcs.1985.Supplement_2.11

Derrien, D., Marol, C., & Balesdent, J. (2007). Microbial biosyntheses of individual neutral sugars among sets of substrates and soils. *Geoderma*, *139*(1–2), 190–198. https://doi.org/10.1016/j.geoderma.2007.01.017

Dyurgerov, M. B., & Meier, M. F. (2004). Glaciers and the changing Earth system: A 2004 snapshot.

Els, N., Larose, C., Baumann-Stanzer, K., Tignat-Perrier, R., Keuschnig, C., Vogel, T. M., & Sattler, B. (2019). Microbial composition in seasonal time series of free tropospheric air and precipitation reveals community separation. *Aero biologia*, *35*(4), 671–701. https://doi.org/10.1007/s10453-019-0960-x

Elster, J., Delmas, R. J., Petit, J.-R., & Řeháková, K. (2007). Composition of microbial communities in aerosol, snow and ice samples from remote glaciated areas (Antarctica. Alps, Andes). *Biogeosciences Discussions*, *4*, 1779–1813. https://doi.org/10.5194/bgd-4-1779-2007

Fabbri, D., Torri, C., Simoneit, B. R. T., Marynowski, L., Rushdi, A. I., & Fabiańska, M. J. (2009). Levoglucosan and other cellulose and lignin markers in emissions from burning of Miocene lignites. *Atmospheric Environment*, *43*(14), 2286–2295. https://doi.org/10.1016/j.atmosenv.2009.01.030

Fan, Y., Liu, C.-Q., Li, L., Ren, L., Ren, H., Zhang, Z., et al. (2020). Large contributions of biogenic and anthropogenic sources to fine organic aerosols in Tianjin, North China. *Atmospheric Chemistry and Physics*, *20*(1), 117–137. https://doi.org/10.5194/acp-20-117-2020

Feltracco, M., Barbaro, E., Tedeschi, S., Spolaor, A., Turetta, C., Vecchiatto, M., et al. (2020). Interannual variability of sugars in Arctic aerosol: Biomass burning and biogenic inputs. *Science of the Total Environment*, *706*, 136089. https://doi.org/10.1016/j.scitotenv.2019.136089

Freppaz, M., Said-Pullicino, D., Filippa, G., Curtaz, F., Celi, L., & Zanini, E. (2014). Winter-spring transition induces changes in nutrients and microbial biomass in mid-alpine forest soils. *Soil Biology and Biochemistry*, *78*, 54–57. https://doi.org/10.1016/j.soilbio.2014.07.010

Fu, P., Kawamura, K., Kobayashi, M., & Simoneit, B. R. T. (2012). Seasonal variations of sugars in atmospheric particulate matter from Gosan, Jeju Island: Significant contributions of airborne pollen and Asian dust in spring. *Atmospheric Environment*, *55*, 234–239. https://doi.org/10.1016/j.atmosenv.2012.02.061

Gambaro, A., Zangrando, R., Gabrielli, P., Barbante, C., & Cescon, P. (2008). Direct determination of Levoglucosan at the Picogram per milliliter level in Antarctic Ice by high-performance liquid chromatography/electrospray ionization triple quadrupole mass spectrometry. *Analytical Chemistry*, *80*(5), 1649–1655. https://doi.org/10.1021/ac701655x

Grantz, D. A., Garner, J. H. B., & Johnson, D. W. (2003). Ecological effects of particulate matter. *Environment International*, *29*(2–3), 213–239. https://doi.org/10.1016/S0160-4120(02)00181-2

Greilinger, M., & Kasper-Giebl, A. (2021). Saharan Dust Records and Its Impact in the European Alps [WWW Document]. *Oxford Research Encyclopedia of Climate Science*. https://doi.org/10.1093/acrefore/9780190228620.013.827

Gunina, A., & Kuzyakov, Y. (2015). Sugars in soil and sweets for microorganisms: Review of origin, content, composition and fate. *Soil Biology and Biochemistry*, *90*, 87–100. https://doi.org/10.1016/j.soilbio.2015.07.021

Guzmán, M. I., Hoffmann, M. R., & Colussi, A. J. (2007). Photolysis of pyruvic acid in ice: Possible relevance to CO and CO₂ ice core record anomalies. *Journal of Geophysical Research*, *112*(D10), 2006JD007886. https://doi.org/10.1029/2006JD007886

Hawkins, L. N., & Russell, L. M. (2010). Polysaccharides, proteins, and phytoplankton fragments: Four chemically distinct types of marine primary organic aerosol classified by single particle spectromicroscopy. *Advances in Meteorology*, *2010*, 1–14. https://doi.org/10.1155/2010/612132

Held, M. A., Jiang, N., Basu, D., Showalter, A. M., & Faik, A. (2014). Plant cell wall polysaccharides: Structure and biosynthesis. In K. G. Ramawat & J.-M. Mérillon (Eds.), *Polysaccharides* (pp. 1–47). Springer International Publishing. https://doi.org/10.1007/978-3-319-03751-6_73-1

Hoham, R. W. (1989). Snow as a habitat for microorganisms.
Hood, E., Fellman, J., Spencer, R. G. M., Hernes, P. J., Edwards, R., D'Amore, D., & Scott, D. (2009). Glaciers as a source of ancient and labile organic matter to the marine environment. *Nature*, **462**(7276), 1044–1047. https://doi.org/10.1038/nature08580

Hood, E., & Scott, D. (2008). Riverine organic matter and nutrients in southeast Alaska affected by glacial coverage. *Nature Geoscience*, **1**(9), 583–587. https://doi.org/10.1038/ngeo280

Huttunen, K., Kaarakainen, P., Meklin, T., Nevalainen, A., & Hirvonen, M.-R. (2010). Immunotoxicological properties of airborne particles at landfill, urban and rural sites and their relation to microbial concentrations. *Journal of Environmental Monitoring*, **12**(6), 1368. https://doi.org/10.1039/c002579h

Ibrahim, M., Barrie, L. A., & Fanaki, F. (1983). An experimental and theoretical investigation of the dry deposition of particles to snow, pine trees and artificial collectors. *Atmospheric Environment*, **17**(4), 781–788. https://doi.org/10.1016/0004-6981(83)90427-4

Intergovernmental Panel On Climate Change (IPCC). (2022). *The ocean and cryosphere in a changing climate: Special report of the inter-governmental panel on climate change* (1st ed.). Cambridge University Press. https://doi.org/10.1017/9781009157964

Intergovernmental Panel On Climate Change (IPCC). (2023). *Climate change 2021—The physical science basis: Working group I contribution to the sixth assessment report of the intergovernmental panel on climate change* (1st ed.). Cambridge University Press. https://doi.org/10.1017/9781009157896

Iordachescu, M., & Imai, R. (2008). Trehalose biosynthesis in response to abiotic stresses. *Journal of Integrative Plant Biology*, **50**(10), 1223–1229. https://doi.org/10.1111/j.1744-7909.2008.00736.x

Jacobsen, E. E., & Anthonsen, T. (2015). 2-C-Methyl-<sup>D</sup>-erythritol. Produced in plants, forms aerosols in the atmosphere. An alternative pathway in isoprenoid biosynthesis. *Biocatalysis and Biotransformation*, **33**(4), 191–196. https://doi.org/10.3109/10242422.2015.1095677

Jansson, P., Hock, R., & Schneider, T. (2003). The concept of glacier storage: A review. *Journal of Hydrology*, **282**(1–4), 116–129. https://doi.org/10.1016/S0022-1694(03)00258-0

Jia, Y., & andy Fraser, M. (2011). Characterization of saccharides in size-fractionated ambient particulate matter and aerosol sources: The contribution of primary biological aerosol particles (PBAPs) and soil to ambient particulate matter. *Environmental Science & Technology*, **45**(3), 930–936. https://doi.org/10.1021/es103104e

Jobbágy, E. G., & Jackson, R. B. (2000). The vertical distribution of soil organic carbon and its relation to climate and vegetation. *Ecological Applications*, **10**(2), 423–436. https://doi.org/10.1890/1051-0761(2000)010[0423:TVDOSO]2.0.CO;2

Jones, H. G. (1999). The ecology of snow-covered systems: A brief overview of nutrient cycling and life in the cold. *Hydrological Processes*, **13**(14–15), 2135–2147. https://doi.org/10.1002/(SICI)1099-1085(199910)13:14/15<2135::AID-HYP862>3.0.CO;2-Y

Junge, K., Eicken, H., & Deming, J. W. (2003). Motility of *Colwellia psychrerythraea* strain 34H at subzero temperatures. *Applied and Environmental Microbiology*, **69**(7), 4282–4284. https://doi.org/10.1128/AEM.69.7.4282-4284.2003

Junge, K., Eicken, H., & Deming, J. W. (2004). Bacterial activity at –2 to –20°C in Arctic Wintertime Sea Ice. *Applied and Environmental Microbiology*, **70**(1), 550–557. https://doi.org/10.1128/AEM.70.1.550-557.2004

Junge, K., Eicken, H., Swanson, B. D., & Deming, J. W. (2006). Bacterial incorporation of leucine into protein down to –20°C with evidence for potential activity in sub-eutectic saline ice formations. *Cryobiology*, **52**(3), 417–429. https://doi.org/10.1016/j.cryobiol.2006.03.002

Kaarakainen, P., Meklin, T., Rintala, H., Hyvärinen, A., Kärkkäinen, P., Vepsäläinen, A., et al. (2008). Seasonal variation in airborne microbial concentrations and diversity at landfill, urban and rural sites. *Clean - Soil, Air, Water*, **36**(7), 556–563. https://doi.org/10.1002/clen.200700179

Kajino, M., & Aikawa, M. (2015). A model validation study of the washout/rainout contribution of sulfate and nitrate in wet deposition compared with precipitation chemistry data in Japan. *Atmospheric Environment*, **117**, 124–134. https://doi.org/10.1016/j.atmosenv.2015.06.042

Kallos, G., Astitha, M., Katsafados, P., & Spyrou, C. (2007). Long-range transport of anthropogenically and naturally produced particulate matter in the Mediterranean and North Atlantic: Current state of knowledge. *Journal of Applied Meteorology and Climatology*, **46**(8), 1230–1251. https://doi.org/10.1175/JAM2530.1

Kang, J.-H., Hwang, H., Lee, S.-J., Choi, S.-D., Kim, J.-S., Hong, S., et al. (2021). Record of North American boreal forest fires in northwest Greenland snow. *Chemosphere*, **276**, 130187. https://doi.org/10.1016/j.chemosphere.2021.130187

Kehrwald, N., Zangrando, R., Gabrielli, P., Jaffrezo, J.-L., Boutron, C., Barbante, C., & Gambaro, A. (2012). Levoglucosan as a specific marker of fire events in Greenland snow. *Tellus B: Chemical and Physical Meteorology*, **64**(1), 18196. https://doi.org/10.3402/tellusb.v64i0.18196

Keuschnig, C., Vogel, T. M., Barbaro, E., Spolaor, A., Koziol, K., Björkman, M. P., et al. (2023). Selection processes of Arctic seasonal glacier snowpack bacterial communities. *Microbiome*, **11**(1), 35. https://doi.org/10.1186/s40168-023-01473-6

Komárek, J., & Nedbalová, L. (2007). Green cryostatic algae. In J. Seckbach (Ed.), *Algae and cyanobacteria in extreme environments, cellular origin, life in extreme habitats and astrobiology* (pp. 321–342). Springer. https://doi.org/10.1007/978-1-4020-6112-7_17

Komor, E. (2000). The physiology of sucrose storage in sugarcane. In *Developments in crop science* (pp. 35–53). Elsevier. https://doi.org/10.1016/S0378-519X(00)80003-3

Krug, L., Erlacher, A., Markut, K., Berg, G., & Cernava, T. (2020). The microbiome of alpine snow algae shows a specific inter-kingdom connectivity and algae-bacteria interactions with supportive capacities. *The ISME Journal*, **14**(9), 2197–2210. https://doi.org/10.1038/s41396-020-0677-4

Krůmal, K., Mikuška, P., Vojtěsek, M., & Večeča, Z. (2010). Seasonal variations of monosaccharide anhydrides in PM1 and PM2.5 aerosol in urban areas. *Atmospheric Environment*, **44**(39), 5148–5155. https://doi.org/10.1016/j.atmosenv.2010.08.057

Larose, C., Dommergue, A., & Vogel, T. (2013). The dynamic Arctic snow pack: An unexplored environment for microbial diversity and activity. *Biology*, **2**(1), 317–330. https://doi.org/10.3390/biology2010317

Larsen, K. S., Grogan, P., Jonasson, S., & Michelsen, A. (2007). Respiration and microbial dynamics in two subarctic ecosystems during winter and spring thaw: Effects of increased snow depth. *Arctic Antarctic and Alpine Research*, **39**(2), 268–276. https://doi.org/10.1657/1523-0430(2007)39[268:RAMDIT]2.0.CO;2

Lemoine, R., Camera, S. L., Atanassova, R., Dédaldéchamp, F., Allario, T., Pourtau, N., et al. (2013). Source-to-sink transport of sugar and regulation by environmental factors. *Frontiers in Plant Science*, **4**, 272. https://doi.org/10.3389/fpls.2013.00272

Li, X., Fu, P., Tripathee, L., Yan, F., Hu, Z., Yu, F., et al. (2022). Molecular compositions, optical properties, and implications of dissolved brown carbon in snow/ice on the Tibetan Plateau glaciers. *Environment International*, **164**, 107276. https://doi.org/10.1016/j.envint.2022.107276

Liu, H., Hu, Z., Zhou, M., Hu, J., Yao, X., Zhang, H., et al. (2019). The distribution variance of airborne microorganisms in urban and rural environments. *Environmental Pollution*, **247**, 898–906. https://doi.org/10.1016/j.envpol.2019.01.090

Liu, Y., Yao, T., Kang, S., Jiao, N., Zeng, Y., Shi, Y., et al. (2006). Seasonal variation of snow microbial community structure in the East Rongbuk glacier, Mt. Everest. *Scientific Bulletin*, **51**(12), 1476–1486. https://doi.org/10.1007/s11434-006-1476-7

Locker, H. B. (1988). The use of Levoglucosan to assess the environmental impact of residential wood-burning on air quality PhD thesis (p. 137). Dartmouth College, Hanover NH.
Loos, H., Krämer, R., Sahm, H., & Sprenger, G. A. (1994). Sorbitol promotes growth of Zymomonas mobilis in environments with high concentrations of sugar: Evidence for a physiological function of glucose-fructose oxidoreductase in osmoprotection. *Journal of Bacteriology*, **176**(24), 7688-7693. https://doi.org/10.1128/jb.176.24.7688-7693.1994

Maccario, L., Carpenter, S. D., Deming, J. W., Vogel, T. M., & Larose, C. (2019). Sources and selection of snow-specific microbial communities in a Greenlandic sea ice snow cover. *Scientific Reports*, **9**(1), 2290. https://doi.org/10.1038/s41598-019-38744-y

Maccario, L., Sanguino, L., Vogel, T. M., & Larose, C. (2015). Snow and ice ecosystems: Not so extreme. *Research in Microbiology*, **166**(10), 782-795. https://doi.org/10.1016/j.resmic.2015.09.002

Maccario, L., Vogel, T. M., & Larose, C. (2014). Potential drivers of microbial community structure and function in Arctic spring snow. *Frontiers in Microbiology*, **5**, 413. https://doi.org/10.3389/fmicb.2014.00413

Maheras, P., Xoplaki, E., Davies, T., Martin-Vide, J., Bariendos, M., & Alcoforado, M. J. (1999). Warm and cold monthly anomalies across the Mediterranean basin and their relationship with circulation; 1860-1990. *International Journal of Climatology*, **19**(15), 1697-1715. https://doi.org/10.1002/(SICI)1097-0088(199912)19:15<1697::AID-JOC442>3.0.CO;2-S

Maréchal, E., & Nedbalová, L. (2022). Editorial: Ice and snow algae. *Frontiers in Plant Science*, **13**, 868467. https://doi.org/10.3389/fpls.2022.868467

Mariko, S., Nishimura, N., Mo, W., Matsui, Y., Kibe, T., & Koizumi, H. (2000). Winter CO₂ flux from soil and snow surfaces in a cool-temperate deciduous forest, Japan. *Ecological Research*, **15**(4), 363-372. https://doi.org/10.1046/j.1440-1703.2000.00357.x

Martin, F., Ramstedt, M., Söderhäll, K., & Canet, D. (1988). Carbohydrate and amino acid metabolism in the ectomycorrhizal ascomycete *Sphaerosporella brunnea* during Glucose Utilization: A ¹³C NMR Study. *Plant Physiology*, **86**(3), 935-940. https://doi.org/10.1104/pp.86.3.935

Massimi, L., Simonetti, G., Buiarelli, F., Di Filippo, P., Pomata, D., Riccardi, C., et al. (2020). Spatial distribution of levoglucosan and alternative biomass burning tracers in atmospheric aerosols, in an urban and industrial hot-spot of Central Italy. *Atmospheric Research*, **239**, 104904. https://doi.org/10.1016/j.atmosres.2020.104904

Mast, M. A., Wickland, K. P., Striegl, R. T., & Clow, D. W. (1998). Winter fluxes of CO₂ and CH₄ from subalpine soils in Rocky Mountain National Park, Colorado. *Global Biogeochemical Cycles*, **12**(4), 607-620. https://doi.org/10.1029/98GB02313

Medeiros, P. M., Conte, M. H., Weber, J. C., & Simoneit, B. R. T. (2006). Sugars as source indicators of biogenic organic carbon in aerosols collected above the Howland Experimental Forest, Maine. *Atmospheric Environment*, **40**(9), 1694-1705. https://doi.org/10.1016/j.atmosenv.2005.11.001

Mikhailov, E. F., Ivanova, O. A., Nebosko, E. Y., Vlasenko, S. S., & Ryshkevich, T. I. (2019). Subpollen particles as atmospheric cloud condensation nuclei. *Izvestiya - Atmospheric and Oceanic Physics*, **55**(4), 357-364. https://doi.org/10.1134/S000143381904008X

Mohler, O., DeMott, P. J., Vali, G., & Levin, Z. (2007). Microbiology and atmospheric processes: The role of biological particles in cloud physics 13.

Monteiro, D., & Morin, S. (2023). Multi-decadal analysis of past winter temperature, precipitation and snow cover data in the European Alps from reanalyses, climate models and observational datasets. *The Cryosphere*, **17**(8), 3617-3660. https://doi.org/10.5194/tc-17-3617-2023

Moorman, B. J. (2005). Glacier-permafrost hydrological interconnectivity: Stagnation Glacier, Bylot Island, Canada. *Geological Society, London, Special Publications*, **242**(1), 63-74. https://doi.org/10.1144/GSL.SP.2005.242.01.06

Nagar, S., Antony, R., & Thamban, M. (2021). Extracellular polymeric substances in Antarctic environments: A review of their ecological roles and impact on glacier biogeochemical cycles. *Polar Science*, **30**, 100686. https://doi.org/10.1016/j.polar.2021.100686

Notarnicola, C. (2022). Overall negative trends for snow cover extent and duration in global mountain regions over 1982-2020. *Scientific Reports*, **12**(1), 13731. https://doi.org/10.1038/s41598-022-16743-w

Oduber, F., Calvo, A. I., Castro, A., Alves, C., Blanco-Alegre, C., Fernández-González, D., et al. (2021). One-year study of airborne sugar compounds: Cross-interpretation with other chemical species and meteorological conditions. *Atmospheric Research*, **251**, 105417. https://doi.org/10.1016/j.atmosres.2020.105417

Oliver, J. E. (2008). *Encyclopedia of world climatology*. Springer Science & Business Media.

Panikov, N. S., Flanagan, P. W., Oechel, W. C., Mastepanov, M. A., & Christensen, T. R. (2006). Microbial activity in soils frozen to below -39°C. *Soil Biology and Biochemistry*, **38**(4), 785-794. https://doi.org/10.1016/j.soilbio.2005.07.004

Pautler, B. G., Simpson, A. J., Simpson, M. J., Tseng, L.-H., Spraul, M., Dubnick, A., et al. (2011). Detection and structural identification of dissolved organic matter in Antarctic Glacial Ice at natural abundance by SPR-W5-WATERGATE ¹ H NMR Spectroscopy. *Environmental Science & Technology*, **45**(11), 4710-4717. https://doi.org/10.1021/es0020697c

Penczykowski, R. M., Connolly, B. M., & Barton, B. T. (2017). Winter is changing: Trophic interactions under altered snow regimes. *Food Webs*, **13**, 80-91. https://doi.org/10.1016/j.fooweb.2017.02.006

Pokhrel, A., Kawamura, K., Kunwar, B., Ono, K., Tushima, A., Seki, O., et al. (2020). Ice core records of levoglucosan and dehydroabietic and vanillic acids from Aurora Peak in Alaska since the 1660s: A proxy signal of biomass-burning activities in the North Pacific Rim. *Atmospheric Chemistry and Physics*, **20**(1), 597-612. https://doi.org/10.5194/acp-20-597-2020

Post, W. M., Emanuel, W. R., Zinke, P. J., & Stangenberger, A. G. (1982). Soil carbon pools and world life zones. *Nature*, **298**(5870), 156-159. https://doi.org/10.1038/298156a0

Procházková, L., Leya, T., Křížková, H., & Nedbalová, L. (2019). Sanguina nivaloides and Sanguina aurantia gen. et spp. nov. (Chlorophyta): The taxonomy, phylogeny, biogeography and ecology of two newly recognised algae causing red and orange snow. *FEMS Microbiology Ecology*, **95**(6), fiz064. https://doi.org/10.1093/femsec/fiz064

Qian, Y., Yasunari, T. J., Doherty, S. J., Flanner, M. G., Lau, W. K. M., Ming, J., et al. (2015). Light-absorbing particles in snow and ice: Measurement and modeling of climatic and hydrological impact. *Advances in Atmospheric Sciences*, **32**(1), 64-91. https://doi.org/10.1007/s00376-014-0010-0

Remias, D., Lütz-Meindl, U., & Lütz, C. (2005). Photosynthesis, pigments and ultrastructure of the alpine snow alga *Chlamydomonas nivalis*. *European Journal of Phycology*, **40**, 259-268. https://doi.org/10.1080/09670260500202148

Rizwan, M., Tanveer, H., Ali, M. H., Sanaullah, M., & Wakeel, A. (2024). Role of reactive nitrogen species in changing climate and future concerns of environmental sustainability. *Environmental Science & Pollution Research*, **31**(39), 51147-51163. https://doi.org/10.1007/s11356-024-34647-2

Robinson, C. T., & Kawecka, B. (2005). Benthic diatoms of an Alpine stream/lake network in Switzerland. *Aquatic Sciences*, **67**(4), 492-506. https://doi.org/10.1007/s00027-005-0783-4

Russell, L. M., Hawkins, L. N., Frossard, A. A., Quinn, P. K., & Bates, T. S. (2010). Carbohydrate-like composition of submicron atmospheric particles and their production from ocean bubble bursting. *Proceedings of the National Academy of Sciences of the United States of America*, **107**(15), 6652-6657. https://doi.org/10.1073/pnas.0908905107
Sanchez-Cid, C., Keuschnig, C., Vogel, T. M., & Larose, C. (2023). Impact of *in situ* solar irradiation on snow bacterial communities and functional potential. *FEMS Microbiology Ecology*, 99(6), fiad042. https://doi.org/10.1093/femsec/fiad042

Saros, J. E., Rose, K. C., Clow, D. W., Stephens, V. C., Nurse, A. B., Arnett, H. A., et al. (2010). Melting alpine glaciers enrich high-elevation lakes with reactive nitrogen. *Environmental Science & Technology*, 44(13), 4891-4896. https://doi.org/10.1021/es100147j

Schimel, D. S., House, J. I., Hibbard, K. A., Bousquet, P., Ciais, P., Peylin, P., et al. (2001). Recent patterns and mechanisms of carbon exchange by terrestrial ecosystems. *Nature*, 414(6860), 169-172. https://doi.org/10.1038/35102500

Schmidl, C., Marr, I. L., Caseiro, A., Kotianová, P., Berner, A., Bauer, H., et al. (2008). Chemical characterisation of fine particle emissions from wood stove combustion of common woods growing in mid-European Alpine regions. *Atmospheric Environment*, 42(1), 126-141. https://doi.org/10.1016/j.atmosenv.2007.09.028

Schultz, M. G., Akimoto, H., Bottenheim, J., Buchmann, B., Galbally, I. E., Gilge, S., et al. (2015). The global atmosphere watch reactive gases measurement network. *Elementa-Science of the Anthropocene*, 3, 000067. https://doi.org/10.12952/journal.elementa.000067

Schultz, T., Müller, R., Gross, D., & Humbert, A. (2021). Modelling the transformation from snow to ice based on the underlying sintering process. *Proceedings in Applied Mathematics and Mechanics*, 20(1), e202000212. https://doi.org/10.1002/pamm.202000212

Schüpbach, S., Fischer, H., Rasmussen, S., Svensson, A., Dahl-Jensen, D., Steffensen, J., & White, J. (2016). Ice cores: High-resolution archive of rapid climate changes. *Past Global Changes Magazine*, 24(1), 12-13. https://doi.org/10.22498/pages.24.1.12

Sciuto, K., & Moro, I. (2015). Cyanobacteria: The bright and dark sides of a charming group. *Biodiversity & Conservation*, 24(4), 711-738. https://doi.org/10.1007/s10531-015-0898-4

Seinfeld, J. H., & Pankow, J. F. (2003). Organic atmospheric particulate material. *Annual Review of Physical Chemistry*, 54(1), 121-140. https://doi.org/10.1146/annurev.physchem.54.011002.103756

Semenzato, R. (1995). A simulation study of sugar cane harvesting. *Agricultural Systems*, 47(4), 427-437. https://doi.org/10.1016/0308-521X(95) 92108-1

Shoham, Y., Lamed, R., & Bayer, E. A. (1999). The cellulosome concept as an efficient microbial strategy for the degradation of insoluble polysaccharides. *Trends in Microbiology*, 7, 275-281. https://doi.org/10.1016/S0966-842X(99)01533-4

Simoneit, B. R. T., Elias, V. O., Kobayashi, M., Kawamura, K., Rushdi, A. I., Medeiros, P. M., et al. (2004). SugarsDominant water-soluble organic compounds in soils and characterization as tracers in atmospheric particulate matter. *Environmental Science & Technology*, 38(22), 5939-5949. https://doi.org/10.1021/es0403099

Simoneit, B. R. T., Kobayashi, M., Mochida, M., Kawamura, K., & Huebert, B. J. (2004). Aerosol particles collected on aircraft flights over the northwestern Pacific region during the ACE-Asia campaign: Composition and major sources of the organic compounds. *Journal of Geophysical Research*, 109(D19), D19S09. https://doi.org/10.1029/2004JD004565

Simoneit, B. R. T., Kobayashi, M., Mochida, M., Kawamura, K., Lee, M., Lim, H., et al. (2004). Composition and major sources of organic compounds of aerosol particulate matter sampled during the ACE-Asia campaign. *Journal of Geophysical Research*, 109(D19), D19S10. https://doi.org/10.1029/2004JD004598

Simoneit, B. R. T., Schauer, J. J., Nolte, C. G., Oros, D. R., Elias, V. O., Fraser, M. P., et al. (1999). Levoglucosan, a tracer for cellulose in biomass burning and atmospheric particles. *Atmospheric Environment*, 33(2), 173-182. https://doi.org/10.1016/S1352-2310(98)00145-9

Singer, G. A., Fasching, C., Wilhelm, L., Niggemann, J., Steier, P., Dittmar, T., & Battin, T. J. (2012). Biogeochemically diverse organic matter in Alpine glaciers and its downstream fate. *Nature Geoscience*, 5(10), 710-714. https://doi.org/10.1038/ngeo1581

Slemmons, K. E. H., Saros, J. E., & Simon, K. (2013). The influence of glacial meltwater on alpine aquatic ecosystems: A review. *Environmental Science: Processes & Impacts*, 15(10), 1794. https://doi.org/10.1039/c3em00243h

K. A. Smith (2010). *Nitrous oxide and climate change*. Earthscan. https://doi.org/10.4324/9781849775113

Song, Y., Wu, D., Ju, X., Dörsch, P., Wang, M., Wang, R., et al. (2023). Nitrite stimulates HONO and NOx but not N₂O emissions in Chinese agricultural soils during nitrification. *Science of the Total Environment*, 902, 166451. https://doi.org/10.1016/j.scitotenv.2023.166451

Styrvold, O. B., & Strøm, A. R. (1991). Synthesis, accumulation, and excretion of trehalose in osmotically stressed Escherichia coli K-12 strains: Influence of amber suppressors and function of the periplasmic trehalase. *Journal of Bacteriology*, 173(3), 1187-1192. https://doi.org/10.1128/jb.173.3.1187-1192.1991

Takeuchi, N., Sera, S., Fujita, K., Aizen, V. B., & Kubota, J. (2019). Annual layer counting using pollen grains of the Grigoriev ice core from the Tien Shan Mountains, central Asia. *Arctic Antarctic and Alpine Research*, 52(1), 605-616. https://doi.org/10.1080/15230430.2019.1638202

Tanaka, H., Hamada, R., Kondoh, A., & Sakagami, K. (1990). Determination of component sugars in soil organic matter by HPLC. *Zentralblatt für Mikrobiologie*, 145(8), 621-628. https://doi.org/10.1016/S0232-4393(11)80282-9

Teeling, H., Fuchs, B. M., Bennke, C. M., Krüger, K., Chafee, M., Kappelmann, L., et al. (2016). Recurring patterns in bacterioplankton dynamics during coastal spring algae blooms. *eLife*, 5, e11888. https://doi.org/10.7554/eLife.11888

Thomson, D. J. (1995). The seasons, global temperature, and precession. *Science*, 268(5207), 59-68. https://doi.org/10.1126/science.268.5207.59

Tignat-Perrier, R., Dommergue, A., Thollot, A., Keuschnig, C., Magand, O., Vogel, T. M., & Larose, C. (2019). Global airborne microbial communities controlled by surrounding landscapes and wind conditions. *Scientific Reports*, 9(1), 14441. https://doi.org/10.1038/s41598-019-51073-4

Tominaga, S., Matsumoto, K., Kaneyasu, N., Shigihara, A., Katono, K., & Igawa, M. (2011). Measurements of particulate sugars at urban and forested suburban sites. *Atmospheric Environment*, 45(13), 2335-2339. https://doi.org/10.1016/j.atmosenv.2010.09.056

Uchida, M., Mo, W., Nakatsubo, T., Tsuchiya, Y., Horikoshi, T., & Koizumi, H. (2005). Microbial activity and litter decomposition under snow cover in a cool-temperate broad-leaved deciduous forest. *Agricultural and Forest Meteorology*, 134(1-4), 102-109. https://doi.org/10.1016/j.agrformet.2005.11.003

Uemura, M., & Steponkus, P. L. (2003). Modification of the intracellular sugar content alters the incidence of freeze-induced membrane lesions of protoplasts isolated from *Arabidopsis thaliana* leaves: Effects of sugar on freezing tolerance of *A. thaliana*. *Plant, Cell and Environment*, 26(7), 1083-1096. https://doi.org/10.1046/j.1365-3040.2003.01033.x

Ullah, A., Rahman, L., Yazdani, M. B., Irfan, M., Khan, W. S., & Rehman, A. (2021). Cell wall polysaccharides. In Inamuddin, M. I. Ahamed, R. Boddula, & T. Altalhi (Eds.), *Polysaccharides* (pp. 23-36). Wiley. https://doi.org/10.1002/9781119714141.ch2

Valledor, L., Furuhashi, T., Hanak, A.-M., & Weckwerth, W. (2013). Systemic cold stress adaptation of chlamydomonas reinhardtii. *Molecular & Cellular Proteomics*, 12(8), 2032-2047. https://doi.org/10.1074/mcp.M112.026765

Vanin, S., Bubacco, L., & Beltramini, M. (2008). Seasonal variation of trehalose and glycerol concentrations in winter snow-active insects. *Cryo Letters*, 29(6), 485-491.

Vick-Majors, T. J., Michaud, A. B., Skidmore, M. L., Turetta, C., Barbante, C., Christner, B. C., et al. (2020). Biogeochemical connectivity between freshwater ecosystems beneath the West Antarctic Ice Sheet and the sub-ice marine environment. *Global Biogeochemical Cycles*, 34(3), e2019GB006446. https://doi.org/10.1029/2019GB006446
Wang, Z., Wu, D., Li, Z., Shang, X., Li, Q., Li, X., et al. (2021). Measurement report: Saccharide composition in atmospheric fine particulate matter during spring at the remote sites of southwest China and estimates of source contributions. *Atmospheric Chemistry and Physics*, *21*(16), 12227–12241. https://doi.org/10.5194/acp-21-12227-2021

Winkel, M., Trivedi, C. B., Mourot, R., Bradley, J. A., Vieth-Hillebrand, A., & Benning, L. G. (2022). Seasonality of glacial snow and ice microbial communities. *Frontiers in Microbiology*, *13*, 876848. https://doi.org/10.3389/fmicb.2022.876848

Wipf, S., & Rixen, C. (2010). A review of snow manipulation experiments in Arctic and alpine tundra ecosystems. *Polar Research*, *29*(1), 95–109. https://doi.org/10.1111/j.1751-8369.2010.00153.x

Xu, Y., Simpson, A. J., Eyles, N., & Simpson, M. J. (2010). Sources and molecular composition of cryoconite organic matter from the Athabasca Glacier, Canadian Rocky Mountains. *Organic Geochemistry*, *41*(2), 177–186. https://doi.org/10.1016/j.orggeochem.2009.10.010

You, C. (2021). Levoglucosan records in the zangsegangri ice core. In *Geochemical behavior of Levoglucosan in Tibetan Plateau Glacier snow and ice*, *springer theses* (pp. 45–61). Springer, Singapore, Singapore. https://doi.org/10.1007/978-981-15-7973-8_5

You, C., Song, L., Xu, B., & Gao, S. (2016). Method for determination of levoglucosan in snow and ice at trace concentration levels using ultra-performance liquid chromatography coupled with triple quadrupole mass spectrometry. *Talanta*, *148*, 534–538. https://doi.org/10.1016/j.talanta.2015.11.030

You, C., & Xu, C. (2018). Review of levoglucosan in glacier snow and ice studies: Recent progress and future perspectives. *Science of the Total Environment*, *616–617*, 1533–1539. https://doi.org/10.1016/j.scitotenv.2017.10.160

You, C., Yao, T., Xu, B., Xu, C., Zhao, H., & Song, L. (2016). Effects of sources, transport, and postdepositional processes on levoglucosan records in southeastern Tibetan glaciers. *Journal of Geophysical Research: Atmospheres*, *121*(14), 8701–8711. https://doi.org/10.1002/2016JD024904

Yttri, K. E., Dye, C., & Kiss, G. (2007). Ambient aerosol concentrations of sugars and sugar-alcohols at four different sites in Norway. *Atmospheric Chemistry and Physics*, *7*(16), 4267–4279. https://doi.org/10.5194/acp-7-4267-2007

Zangrando, R., Barbaro, E., Kirchgeorg, T., Vecchiato, M., Scalabrin, E., Radaelli, M., et al. (2016). Five primary sources of organic aerosols in the urban atmosphere of Belgrade (Serbia). *Science of the Total Environment*, *571*, 1441–1453. https://doi.org/10.1016/j.scitotenv.2016.06.188

Zangrando, R., Barbaro, E., Vecchiato, M., Kehrwald, N. M., Barbante, C., & Gambaro, A. (2016). Levoglucosan and phenols in Antarctic marine, coastal and plateau aerosols. *Science of the Total Environment*, *544*, 606–616. https://doi.org/10.1016/j.scitotenv.2015.11.166

Zhao, B., & Su, Y. (2014). Process effect of microalgal-carbon dioxide fixation and biomass production: A review. *Renewable and Sustainable Energy Reviews*, *31*, 121–132. https://doi.org/10.1016/j.rser.2013.11.054

Zhu, C., Kawamura, K., & Kunwar, B. (2015). Effect of biomass burning over the western North Pacific Rim: Wintertime maxima of anhydrosugars in ambient aerosols from Okinawa. *Atmospheric Chemistry and Physics*, *15*(4), 1959–1973. https://doi.org/10.5194/acp-15-1959-2015

Zhu, C., Miller, M., Lusskin, N., Bergk Pinto, B., Maccario, L., Häggblom, M., et al. (2020). Snow microbiome functional analyses reveal novel aspects of microbial metabolism of complex organic compounds. *MicrobiologyOpen*, *9*, e1100. https://doi.org/10.1002/mbo3.1100

Zhu, R.-G., Xiao, H.-Y., Cheng, L., Zhu, H., Xiao, H., & Gong, Y. (2022). Measurement report: Characterization of sugars and amino acids in atmospheric fine particulates and their relationship to local primary sources. *Atmospheric Chemistry and Physics*, *22*(21), 14019–14036. https://doi.org/10.5194/acp-22-14019-2022