Snow season NEE has been observed to vary according to the thickness of snow, soil temperature and vegetation composition at site H3 (Elberling, 2007). The strength of the associations between air temperature, soil temperature and NEE depends in part on the duration of snow cover and the physiological activity of vegetation during winter thaws (Starr and Oberbauer , 2003; Sullivan et al., 2008). Furthermore, the timing and magnitude
of winter CO2 transport depend on snow conditions, CO2 production, site characteristics
and weather conditions (Jones et al., 1999).
The acquisition of regional estimates of NEE is complicated by the scale dependence of NEE as well as the spatial variability of the various controlling influences on NEE such as snow, soil, vegetation and microclimate status. Arctic transect studies have indicated that
macro scale (>104 m) vegetation spatial patterns are influenced by latitudinal climatic
gradients, topography, precipitation and active layer depth (Gould et al., 2003; McGuire
et al., 2002). At the site scale (10–104 m), vegetation varies according to micro-topography
and soil type, which both influence soil moisture (Svensson and Callaghan, 1988). Sim-
ilarly, spatio-temporal variability of snow is scale dependent. At the micro (10–102 m)
scale, transport and surface roughness influence distributions of snow. At the macro scale, variations in snow are controlled by elevation, orography and latitude, as well as distance
from barriers and water, at the meso (102–103 m) scale, variations tend to be influenced
by slope, elevation, aspect, and vegetation (height, extent, density, etc.) (Bonan, 2002). Therefore, both vegetation and snow vary across the landscape and both are scale depen- dant. Likewise, a portion of the spatial variability in NEE is likely due to the influence of snow and vegetation.
Due to the spatial variability of the factors controlling snow season NEE, it is important that attempts to reduce uncertainty in sub-Arctic and Arctic NEE estimates during the snow season be founded upon the current state of knowledge regarding the influence of snow on the uptake and efflux of COat Arctic and sub-Arctic study sites.The following section therefore provides a synthesis of recent in situ findings regarding the site-scale associations between snow, vegetation and snow season NEE. Implications of these findings for representing the influence of snow on winter NEE are then discussed based on the physical processes driving these interactions [Table 2.3].
2.4.1
Greater efflux of CO
2from sites with greater snow accu-
mulation
Snow acts as an insulator because it has a small volumetric heat capacity, undergoes little heat loss by convection, and has a low thermal conductivity. The thermal conductivity
of snow has been observed to range from 0.025-1.61 W/-m−1-deg-C−1 in snowpacks with
densities of 100-800 kg/m3 (Gray and Male, 1981). Generally, low values of thermal con-
ductivity (e.g. 0.06 W-m−1-deg-C−1) are observed in the Arctic and sub-Arctic (Sturm,
1992). The thermal conductivity of a snowpack is influenced by factors such as snowpack depth, bonding, temperature, porosity, ventilation, and grain characteristics, but can be can be estimated as a simple, positive function of snow density (Sturm et al., 1997). A greater accumulation of snow is generally associated with diminished thermal conductivity of the land-atmosphere interface (Gray and Male, 1981). Snowpacks can therefore decou- ple air and soil temperatures (Olsson et al., 2003) since less heat is transferred from the soil when an overlying layer of snow is present (Bonan, 2002). As a result, the frozen soil
at 40-120 cm depth from which CO2 is emitted has been observed to be 10-40◦C warmer
than the surface air temperature at a Siberian sub-Arctic site T6 (Zimov et al., 1993). For example, at two low Arctic sites located at L3, minimum 16 cm soil temperatures in the
-10 to -5◦C range were observed with minimum air temperatures of -30◦C (Olsson et al.,
2003).
Microbial fluxes have been observed to increase as a function of temperature over both organic and mineral soils at site L1 (Oelbermann et al., 2008). The association between soil respiration and temperature is driven by intracellular desiccation or extracellular barriers to diffusion in frozen soils, and by soil organic matter in thawed soils (Mikan et al., 2002).
The influence of snow accumulation on CO2 flux has been detected experimentally at
a variety of sites using snow fences, which cause a local increase in snow accumulation through wind deposition. Across a sub-Arctic gradient in Sweden (S2), comparisons of treatment and control plots indicated that snow accumulation had an important influence on soil temperature. Between 41 to 75% of the variation in respiration could be explained as a function of soil temperature at site S2 (Grogan and Jonasson, 2006). Near the Arctic
treeline in Alaska (S3), CO2 flux varied significantly (p-value<0.01) between sites and years,
and according to both snow depth and soil surface temperature. Soil surface temperature and snow depth were correlated (r=0.73, p-value<0.01). Soil temperature and snow depth were greater in forested regions than at the treeline, and both increased in forests with greater stand density (Sullivan, 2010).
At a low Arctic site in northern Alaska (L2), warmer soil temperatures and greater rates of respiration were observed at plots that had received a greater accumulation of snow due
to the installation of snow fences (Walker et al., 1999). At low Arctic site L1, observations
of net seasonal CO2 flux were collected using soda lime traps, which accumulate mass as
CO2 is released throughout the season. These measurements indicated a 60% increase
in total snow season CO2 efflux in snow accumulation plots (1 m of snow) relative to
control plots (0.3 m of snow) (Nobrega and Grogan, 2007). At an Alaskan tussock tundra
site (L2), snow accumulation acted as a stronger control on CO2 distributions than air
temperature (Sullivan et al., 2008). Experimental snow accumulation (30-150 cm) at a high Arctic site in Svalbard (H2) led to significant increases in both soil temperature and
ecosystem respiration, leading to a doubling of CO2 efflux at both heath and meadow
sites (Morgner et al., 2010). Greater snow accumulation over several varied Arctic and sub-Arctic ecosystems therefore induced increased CO efflux.
2.4.2
Influence of vegetation on snow and snow season NEE
Interactions between snow and vegetation have been observed to alter snow season photo- synthesis (Larsen et al., 2007a) and respiration (Grogan and Jonasson, 2006) at site S2. In regions where tree wells form, the size of tree wells and the resulting soil heat loss depend
on micro-scale (10–102 m) vegetation distributions (Sturm, 1992). The species distribu-
tions of vegetation at a site can therefore influence the soil temperature and respiration.
At the meso scale (102–103 m), groupings of trees act as windbreaks, causing an increase in
snow deposition nearby (Gray and Male, 1981), which could potentially increase the rate of soil respiration.
Vegetation species composition also has an influence on subnivean photosynthesis and respiration. Shrub stems encourage the growth of large faceted crystals via metamorphism under strong temperature gradients. Faceted crystals have one fifth to one twentieth of the effective thermal conductivity of a high density wind slab (Zhang et al., 1996), resulting
in the release of greater effluxes of CO2 from areas containing shrubs, as observed at site
S2 (Sullivan, 2010). Also, although cold temperatures and diminished light availability re-
duce photosynthetic assimilation of CO2 (Billings and Mooney, 1968), the species present
at a site influence the resulting rate of photosynthesis. While in a dormant state, ever- green vegetation protects itself from light stress through non-photochemical dissipation
of absorbed light ( ¨Oquist and Huner , 2003). Following frost hardening, evergreen trees
have been observed to undergo no growth and “no measurable net photosynthesis” as long
as subzero air temperatures persist ( ¨Oquist and Huner , 2003). Although vascular plants
cannot conduct photosynthesis when their tissues are frozen, evidence exists that lichens
can perform photosynthesis at temperatures below -10◦C (Kappen, 1993). Furthermore,
be capable of performing photosynthesis at greatly diminished rates under thin snow cover, as long as conditions are suitably warm (Tieszen, 1974).
(Larsen et al., 2007a) reported that cold season (October to May) photosynthesis ac- counted for up to 19% of annual photosynthesis in a mesic, moss-dominated sub-Arctic heath with little (30-40 cm) snow (site S2). Similarly, (Starr and Oberbauer , 2003) found evidence of subnivean photosynthesis by Arctic evergreens on the north slope of Alaska (site L2) during a two to four week period at the end of the snow season in the presence
of air temperatures above 0◦C and encouraged by elevated subnivean concentrations of
CO2. At a High Arctic site in Zackenberg (H1), (Christensen et al., 2012) observed low
levels of photosynthesis to continue to occur at the start of the snow season. Vegetation therefore shows greatly reduced rates of photosynthesis in the presence of snow, even in Arctic species which are adapted to perform photosynthesis in sub-zero conditions.
2.4.3
Implications for models of NEE
Remote sensing observations of snow water equivalent (SWE) or snow depth could be used in combination with observations of air temperature to gain more accurate estimates of subnivean temperatures. The influence of greater snow accumulation on increased rates of soil respiration observed at many high, low and sub-Arctic sites (e.g. S2- (Grogan and Jonasson, 2006); S1- (Sullivan, 2010); L1- (Nobrega and Grogan, 2007); H2- (Morgner et al., 2010)) could therefore be represented in models of NEE. This influence could be represented using remote sensing observations of SWE or snow depth to determine more accurate estimates of soil respiration, or by assimilating remote sensing observations of SWE into model estimates of snowpack accumulation to better constrain estimates of soil respiration.
The initial appearance of snow and concurrent drops in air and soil temperatures greatly limit the rate of photosynthetic uptake in Arctic vegetation (Billings and Mooney, 1968;
Carstairs and Oechel , 1978; ¨Oquist and Huner , 2003). The influence of snow on limiting
the rate of snow season photosynthesis could be represented in models of NEE using ob- servations of fractional snow cover area, and then diminishing the rate of photosynthesis in regions where snow is accumulating by an appropriate quantity given the vegetation distribution. The differing abilities of vascular and non-vascular plants to conduct pho- tosynthesis in sub-zero conditions could therefore be represented. Greater benefits may be accrued by representing fractional snow cover in autumn than spring as photosynthesis is more heavily influenced by air temperature and photoperiod at the start of the snow season than at the end of the snow season, as described by (Euskirchen et al., 2012).
The influence of vegetation on snowpack properties such as the formation of tree wells (Sturm, 1992) and faceted crystals in shrub-dominated regions (Zhang et al., 1996), and their influences on increasing and diminishing local snow thermal conductivities, respec- tively, could be represented using vegetation species-specific expressions to determine soil respiration as a function of snow accumulation. Another option may be to incorporate field observations of grain characteristics to represent the growth of faceted crystals, or high resolution LiDAR observations to detect the formation of tree wells.