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Keywords:

  • boreal forest;
  • carbon cycle;
  • snow;
  • tussock tundra

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

[1] Soils in arctic and boreal ecosystems hold large stocks of soil carbon (C), which may be sensitive to changes in climate. Recent studies suggest that winter CO2 efflux from the subnivean environment may be an important component of annual C budgets in arctic and boreal ecosystems. The present study was designed to examine the seasonal patterns and magnitudes of winter CO2 efflux from arctic tussock tundra near Toolik Lake, Alaska, and upland boreal forest in Anchorage, Alaska. The seasonal pattern of winter CO2 efflux differed strongly between the two sites. Tussock tundra showed a prolonged period with very low flux rates between late December and mid-April. In contrast, rates of CO2 efflux were relatively high, but variable, throughout the winter at the boreal site. Estimates of C efflux for the snow-covered season were within the range of previous studies in tussock tundra (24 g C m−2) and upland boreal forest (75 g C m−2). A simple exponential model, using shallow soil temperatures, explained much of the variation in CO2 efflux from tussock tundra. In contrast, air temperature was an important secondary control on winter CO2 efflux from the boreal forest, suggesting that trees became active during prolonged winter thaws. Results of the study imply that warmer winters may increase rates of C efflux from high-latitude ecosystems. Changes in the depth or duration of snow cover will, however, modulate the relationship between air and soil temperatures and could amplify or dampen the effects of climate warming.

1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

[2] The cold and, in some instances, wet soils of arctic and boreal ecosystems have long held rates of ecosystem respiration below rates of photosynthesis, creating large globally important stocks of soil carbon (C) [Post et al., 1982; Post, 2002]. Belowground respiration has been shown to continue throughout the winter in a wide variety of northern ecosystems [e.g., Zimov et al., 1993, 1996; Oechel et al., 1997; Winston et al., 1997; Fahnestock et al., 1998; Jones et al., 1999; Alm et al., 1999; Wang et al., 2002]. Persistence of belowground respiration during much of the winter has been attributed to the insulating properties of the snowpack, which may hold soil temperatures above the threshold for microbial respiration for some or all of the winter (−16 to −10°C [Panikov and Dedysh, 2000; Mikan et al., 2002]).

[3] The presence of winter belowground respiration was first suggested by an observation that subnivean [CO2] was higher than atmospheric [CO2], particularly during the early and late winter periods near Barrow, AK [Kelly et al., 1968]. More recently, investigators in arctic and boreal ecosystems have used a variety of methods to estimate “instantaneous” fluxes of subnivean CO2 to the atmosphere, in an effort to confirm the presence of winter respiration, compare rates across ecosystems and estimate total wintertime C efflux [e.g., Zimov et al., 1993, 1996; Oechel et al., 1997; Winston et al., 1997; Fahnestock et al., 1999; Panikov and Dedysh, 2000; Vogel et al., 2005]. Logistical difficulties have limited the frequency of sampling dates, particularly in arctic ecosystems, such that we currently lack a clear vision of the seasonal pattern of wintertime CO2 efflux. Because we have not resolved the seasonal patterns of winter CO2 efflux, our estimates of annual C budgets remain uncertain.

[4] The present study was designed to resolve and compare the seasonal patterns of winter CO2 efflux from a tussock tundra site in northern Alaska and an upland white spruce-paper birch forest in south-central Alaska. Nondispersive infrared (NDIR) CO2 probes were used to continuously monitor [CO2] in the subnivean environment and the atmosphere, in conjunction with a full suite of micrometerological measurements. Periodic measurements of atmospheric and subnivean [CO2] were made using a portable infrared gas analyzer (IRGA), equipped with a snow probe, to check the validity of data from the CO2 probes and to place the continuous measurements in the context of measurements over a larger area.

2. Methods

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

2.1. Site Descriptions

[5] Continuous measurements of atmospheric and subnivean CO2 concentrations were made during the winter of 2006–2007 in acidic tussock tundra near, Toolik Lake, Alaska (68°37′N, 149°36′W, 740 m asl), and in upland boreal forest on the University of Alaska campus in Anchorage, Alaska (61°12′N, 149°49′W, 42 m asl). Vegetation at the tussock tundra site is nearly equally distributed among graminoids, deciduous shrubs, evergreen shrubs and mosses (Shaver and Chapin, 1991) and the soil contains approximately 10.0 kg SOC/m2 in the upper 20 cm of the profile (Schimel et al., 2006). The overstory of the upland boreal forest site is a near even mixture of Picea glauca and Betula papyrifera. The forest has approximately 6000 stems/ha, which amount to a basal area of 170 m2/ha. The stems are approximately 50% P. glauca and 50% B. papyrifera, although the B. papyrifera individuals are generally much larger, such that the species accounts for approximately 70% of the basal area. Cores taken following 2007 radial growth at 25 cm above the ground surface revealed 65 annual increments in the largest P. glauca and 80 annual increments in the largest B. papyrifera individual, providing a minimum time since the last stand-clearing disturbance. Dominant species in the understory include Ledum palustre, Empetrum nigrum, Vaccinium vitis-idaea, Cornus canadensis, Lycopodium clavatum and the mosses Hylocomium splendens and Pleurozium schreberi. Soils at the site hold approximately 4.5 kg SOC/m2 in the upper 20 cm of the profile.

2.2. Continuous Measurements

[6] In tussock tundra, micrometeorological sensors and sensors for atmospheric and subnivean [CO2] were mounted on a 3.5 m tower. Power for the system was delivered by a 1 kW wind turbine (Southwest Windpower, Flagstaff, AZ) and a battery bank consisting of 16 200AH/6V absorbent glass mat batteries wired in series (Trojan Battery Co., Santa Fe Springs, CA). At the upland boreal forest site, sensors were mounted on a 10 m meteorological tower and supplied with AC power from the Ecosystems and Biomedical Laboratory on the University of Alaska campus in Anchorage. Micrometeorological stations consisted of sensors for air temperature and relative humidity, wind speed, barometric pressure, snow depth, snow temperatures, soil temperatures and soil water contents, in addition to sensors for atmospheric and subnivean [CO2] (Table 1). Sensors were read every 30 s and hourly averages were logged, with the exception of barometric pressure and soil water sensors, which were read and logged once per hour.

Table 1. Description of Micrometeorological Stations Established in Arctic Tussock Tundra Near Toolik Lake, Alaska, and in Upland Boreal Forest in Anchorage, Alaskaa
VariableTussock TundraUpland Boreal Forest
  • a

    Sensors were mounted on a 3.5 m tower at the arctic site and on a 10 m tower at the boreal forest site.

  • b

    Supplied by Campbell Scientific Inc., Logan, Utah.

  • c

    Supplied by Vaisala Inc., Helsinki, Finland.

  • d

    Supplied by Onset Computer Corp, Bourne, Massachusetts.

  • e

    Supplied by Southwest Windpower, Flagstaff, Arizona.

Air temperature and RH at 3 mCS215bCS500b
Wind speed at 3 m014Ab014Ab
Atmospheric [CO2] at 3 mGMP343cGMP343c
Barometric pressureCS105bCS105b
Snow depthSR50bSR50b
Snow temperature 0.1 m intervalsHobo H8dCS107b
Subnivean [CO2] at 0.02 mGMP343cGMP343c
Soil temperature at 0.05 mNACS107b
Soil temperature at 0.10 mCS107bNA
Soil temperature at 0.25 mCS107bCS107b
Soil water content at 0.25 mCS616bCS615b
Data loggerCR3000bCR10 and CR800b
Power supplyWHI-200 wind turbineeAC line power

[7] Atmospheric CO2 probes at both sites were housed in modified radiation shields, while subnivean CO2 probes were suspended 0.02 m above the soil surface using laboratory scaffolding. In tussock tundra, the subnivean CO2 probe was installed in an area visually determined to be microtopographically intermediate between a tussock and an inter-tussock area. In the upland boreal forest, the subnivean CO2 probe was installed approximately 30 cm beyond the canopy of a white spruce tree. At both sites, subnivean CO2 probes were placed approximately 1.0 m from the site where soil temperature and soil water probes were installed in a qualitatively similar microenvironment. CO2 probes were checked against a series of calibration gases before and following the winter measurement period. Linear corrections were applied when there was evidence of sensor drift.

[8] Measurements of snowpack density were made using snow pits (n = 2 or 3) excavated on monthly intervals at both sites during the winter of 2006–2007. Density measurements were made in continuous 10 cm increments using a stainless-steel RIP 1 density cutter [Elder et al., 1991] (Snowmetrics, Fort Collins, CO) and a 600 g capacity spring scale with 5 g resolution (Pesola AG, Baar, Switzerland). Snowpack density was taken as the average of the 10 cm measurements.

2.3. Point Measurements

[9] Point measurements of atmospheric and subnivean CO2 concentrations were made in tussock tundra on 5 December 2006, 15 March 2007 and 9 May 2007 and in upland boreal forest on 17 November 2006, 22 December 2006, 6 February 2007, 24 February 2007, 21 March 2007 and 13 April 2007. Measurements were made using a hollow stainless steel probe, equipped with a perforated tip and plumbed with 3.2 mm ID bev-a-line tubing [Fahnestock et al., 1998, 1999; Brooks et al., 1999; Welker et al., 2000; Hubbard et al., 2005]. The tubing was attached to a LI-800 NDIR CO2 analyzer (LI-COR Biosciences, Lincoln, NE), which was equipped with a 5 cm optical bench, a micro-diaphram pump downstream of the optical bench (850 mL/min, KNF Neuberger Inc., Trenton, NJ) and a digital multimeter (Fluke Corporation, Everett, WA). The LI-800 was allowed to warm-up for 1.5 h and checked against a series of calibration gases before each measurement campaign. Measurements were made by inserting the probe to the base of the snowpack and drawing air through the analyzer until CO2 concentrations stabilized.

2.4. Data Processing and Statistical Analyses

[10] Monthly measurements of snowpack density were interpolated with cubic spline curves to generate daily estimates of snowpack density using the Expand procedure of SAS 9.1 (SAS Institute, Cary, NC). Snow densities typical of cold, fresh snow (arctic: 250 g/L, boreal: 150 g/L) were applied to the first day, while a density value typical of isothermic snow (arctic: 425 g/L, boreal: 375 g/L) was applied to the final day, to enable interpolation to the tails the measurement period at both sites. Different initial and final snow densities were applied to account for differences in wind speeds between the sites.

[11] Estimates of CO2 efflux from the subnivean environment to the atmosphere were made using Fick's law of diffusion through unsaturated porous media [Mast et al., 1998]:

  • equation image

where q is the rate of CO2 efflux (μmol m−2 s−1), dC is the difference in [CO2] between the subnivean and the atmosphere (μmol/mol), dz is snow depth (cm) and Deff is the effective diffusion constant through the snowpack, estimated as:

  • equation image

where θ is snowpack porosity (estimated as 1-(density/973), with ice density = 973 g/L), τ is snowpack tortuosity (estimated as θ1/3), and DCO2 is the diffusion constant for CO2 through air at STP, corrected for pressure (P) and temperature (T) in the final terms. Estimates of CO2 efflux were restricted the period when soils were consistently covered by at least 15 cm of snow.

[12] A wide variety of models have been used to describe the correlation between temperature and respiration and investigators have generally concluded that no one model provides the best fit across a full range of soil temperatures [Lloyd and Taylor, 1994; Fang and Moncrieff, 2001]. In the present study, CO2 efflux data were fit with a simple, commonly used exponential model [e.g., Buchmann, 2000; Mikan et al., 2002; Litton et al., 2003]:

  • equation image

where T is soil temperature (°C) and α and β were fit using nonlinear regression in Proc NLIN of SAS 9.1 (SAS Institute, Cary, NC). It is common that respiration-temperature correlations fail to meet the assumptions of regression analysis, in particular the assumption of homogeneity of variance [Lloyd and Taylor, 1994; Fang and Moncrieff, 2001]. Regressions in the present study are not exceptional in this respect and should, therefore, be treated with caution. Q10 values, which describe the increase in CO2 efflux expected for a 10°C increase in temperature, were calculated as follows:

  • equation image

where β was taken from equation (3).

[13] During the snow-covered season, air and soil temperatures may be strongly decoupled and belowground respiration in forest ecosystems may show a response to both, as trees extend above the snow surface. Multiple linear regression analyses were used in Proc Reg of SAS 9.1 to examine the potential importance of air temperature as a secondary control on winter CO2 efflux. Nonlinear terms were implemented prior to the multiple regression analysis and it was necessary to include intercepts in the models. First, Proc NLIN was used to fit β in equation (3) for both air and soil temperatures, then stepwise selection was employed in multiple regression analyses to fit coefficients and test the significance of two linear (air and soil) and two exponential terms (air and soil, equation (3)). In both tussock tundra and the upland boreal forest, a linear air temperature and an exponential soil temperature term proved significant at alpha = 0.05. The multivariate models were, then, refit in Proc NLIN to update the β values and reexamined using stepwise selection in a multiple regression to generate the final fit statistics. The multivariate models, which use daily mean air and soil temperatures to estimate daily mean CO2 efflux, were used to estimate CO2 efflux on days with relatively high wind speeds, when turbulence-induced pressure pumping [Massman et al., 1997] may have affected diffusion-based estimates of CO2 efflux. This approach was used on 60 days in tussock tundra and on 20 days for the boreal forest site.

2.5. Potential Sources of Error in Estimates of CO2 Efflux

[14] The continuous estimates of winter CO2 efflux may be influenced by several sources of error. Takagi et al. [2005] discussed the effects of similar CO2 sensors on temperatures in the surrounding snow and concluded that the effects were relatively minor. In their study, the sensors were turned off between measurements while, in the present study, sensors were run continuously to reduce the likelihood of sensor drift. Consequently, there was probably some effect of the sensors on the stratigraphy of surrounding snow. These artifacts were likely greatest when the snowpack was shallow and when snow temperatures were near 0°C.

[15] A linear gradient in CO2 concentration from the subnivean environment to the atmosphere is required to estimate CO2 flux using the diffusion model (equations (1) and (2)), but there are several phenomena that could disrupt the linear gradient expected under steady state conditions. The presence of relatively impermeable wind slabs and or ice layers within the snowpack may disrupt the linear gradient [Mast et al., 1998; Jones et al., 1999]. Turbulence-induced pressure pumping during high wind events may also disrupt the CO2 concentration gradient and lead to pulses of CO2 efflux that are not addressed by the diffusion model [Massman et al., 1997; Jones et al., 1999]. Data were eliminated from the arctic site on days when wind speeds were greater than 3.5 m/s and from the boreal site when wind speeds exceeded 0.5 m/s, after visually analyzing the graph of subnivean [CO2] as a function of wind speed. Failure to eliminate data from all days when pressure pumping was active would lead to a systematic underestimation of total winter C efflux.

[16] The model described in equations (1) and (2) describes diffusion of CO2 from the subnivean environment to the atmosphere directly above the snow surface. Atmospheric CO2 sensors were installed at 3 m height, where CO2 concentrations may be lower than those at the snow surface during periods of limited atmospheric mixing. During these time periods, CO2 efflux was likely overestimated. This error was probably greatest during the nighttime at the boreal forest site and was probably less important at the arctic site.

3. Results

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

3.1. Microclimate

[17] Air and soil temperatures were considerably colder in arctic tussock tundra, than at the upland boreal forest site (Figure 1). Air temperatures dropped below the sensor's low temperature limit (−41°C) on 9, 10 and 13 March in tussock tundra and reached a minimum of −28°C on 9 January at the boreal forest site. Both sites showed a similar air temperature pattern during the winter measurement period, with warm spells in early December and early February and a prolonged period of deep cold in March. Soil temperatures at 25 cm were much less variable than air temperatures, reaching minima of −13.6°C on 26 March in tussock tundra and of −3.0°C on 21 March at the boreal forest site. The wet mineral soils of tussock tundra froze in late November, after a prolonged period with soil temperatures very near 0°C. The better drained mineral soils of the boreal forest site froze in mid-December, following colder than normal air temperatures in November (National Weather Service, Anchorage Forecast Office, Anchorage, AK).

image

Figure 1. Comparison of daily mean values for select climate variables at the tussock tundra and upland boreal forest sites between 1 November 2006 and 31 May 2007.

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[18] Snowpack development began in late-October at both sites (Figure 2). Snow depth increased gradually to reach a maximum, sustained depth of approximately 45 cm in mid-April at the tussock tundra site. At the boreal forest site, snow depth increased rapidly in December and January and reached a maximum, sustained depth of approximately 55 cm in late March. The snowpack became isothermal and dissipated rapidly in late May at the tundra site, while the boreal forest site was left snow-free in late April. Snowpack density was consistently higher at the tussock tundra site, than at the boreal forest site, averaging 284 and 225 g/L, respectively. Higher snowpack density at the tundra site is a consequence of greater exposure and much higher wind speeds. It is worth noting that tussock tundra snowpack density often varied strongly with depth. It was common to observe high-density layers (>300 g/L) near the snow surface and low-density layers composed of strongly metamorphosed crystals (<200 g/L) near the soil surface.

image

Figure 2. Comparison of daily mean atmospheric [CO2], snow depth, wind speed and subnivean [CO2] at the tussock tundra and upland boreal forest sites between 1 November 2006 and 31 May 2007.

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3.2. CO2 Measurements

[19] Measurements of atmospheric [CO2] at 3 m showed very different patterns across the two sites (Figure 2). Atmospheric [CO2] at the tussock tundra site showed limited diurnal variation and increased seasonally from approximately 375 μmol/mol in late October to approximately 385 μmol/mol in May. In contrast, atmospheric [CO2] at 3 m in the boreal forest showed substantial diurnal variation, particularly during the darkest months of the year, with early morning [CO2] approaching 600 μmol/mol and daily average [CO2] as high as 500 μmol/mol.

[20] Comparison of CO2 concentration measurements and CO2 efflux estimates made using the portable IRGA and snow probe agreed well with those made using the permanently installed CO2 sensors (Figure 3). There was a strong positive linear correlation between measurements of subnivean [CO2] made using the two approaches (n = 11, r2 = 0.94, F = 149.5, P < 0.01), with a slope very close to unity (0.89, S.E.: 0.07). The correlation between CO2 efflux estimates made using the two approaches was similarly strong (n = 11, r2 = 0.95, F = 157.0, P < 0.01) and, again, the slope was very close to unity (1.07, S.E.: 0.09).

image

Figure 3. Comparison of subnivean [CO2] measurements and CO2 efflux estimates made using permanently installed NDIR CO2 probes and those made with a portable NDIR CO2 analyzer and a snow probe. The solid line represents a least squares regression, while 1:1 is indicated by the dotted line. Bars are 1.0 SE.

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[21] The seasonal patterns of subnivean [CO2] differed markedly between the tussock tundra and boreal forest sites. In tussock tundra, subnivean [CO2] decreased from relatively high values in early December (∼500 μmol/mol) and remained low (generally within 15 μmol/mol of atmospheric [CO2]) for a prolonged period from late December until early April. Subnivean [CO2] increased through April and May, briefly reaching its highest recorded values (∼625 μmol/mol) during snowmelt. Subnivean [CO2] at the boreal forest site was more variable than at the tundra site and much higher overall. Subnivean [CO2] was modestly high during the initial stages of snowpack development, presumably because soils were still unfrozen at depth. Subnivean [CO2] declined in early December, as soils froze, and increased again in two distinct peaks: one in early February, during a midwinter thaw, and a second during snowmelt in mid-April. The highest recorded daily mean subnivean CO2 concentrations (∼975 μmol/mol) were observed during the early February and mid-April peaks.

3.3. Controls on CO2 Efflux

[22] There was some evidence of turbulence-induced pressure pumping during high wind events at both sites, as high values of subnivean [CO2] were disproportionately observed when wind speeds were relatively light (Figure 4). In tussock tundra, relatively high values of daily mean subnivean [CO2] (>500 μmol/mol) were rarely observed when daily average wind speeds exceeded 3.5 m/s. The boreal forest site, where snow density was lower, appeared to be more sensitive to pressure pumping, as high values of daily mean subnivean [CO2] (>700 μmol/mol) were rarely observed when daily average wind speeds were greater than 0.5 m/s. Days with average wind speeds greater than 3.5 m/s in tussock tundra and 0.5 m/s at the boreal forest site were, therefore, removed from analyses designed to examine the controls on CO2 efflux.

image

Figure 4. Daily mean subnivean [CO2] as a function of daily mean wind speed at the tussock tundra and upland boreal forest sites. Data to the right of the vertical dotted lines were eliminated from subsequent analyses because turbulence-induced pressure pumping may have reduced subnivean [CO2] during periods with relatively high winds. Data were subsequently gap-filled using observed correlations between temperature and CO2 efflux to produce a continuous record for the snow-covered season.

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[23] In tussock tundra, a simple, first-order exponential model explained much of the observed variation in the relationship between soil temperature at 10 cm and CO2 efflux (n = 138, r2 = 0.84, P < 0.01), with a Q10 of 18.2 (Figure 5). CO2 efflux was more closely correlated with soil temperature at 10 cm, than with soil temperature at 25 cm (r2 = 0.61, P < 0.01). When introduced as a linear term in a multiple regression framework, along with the exponential soil temperature term, air temperature was also a significant predictor of CO2 efflux (partial r2 = 0.01, P = 0.01). In the upland boreal forest site, a simple exponential model explained considerably less of the relationship between soil temperature at 5 cm and CO2 efflux (n = 137, r2 = 0.43, P < 0.01), with a Q10 of 81.5. Again, CO2 efflux was more closely correlated with soil temperature at 5 cm, than with soil temperature at 25 cm (r2 = 0.16, P < 0.01). In contrast with results in tussock tundra, including air temperature as a linear term in a multiple regression model substantially helped to explain variation in CO2 efflux (partial r2 = 0.19, P < 0.01).

image

Figure 5. Correlations between daily mean shallow soil temperatures and daily mean C efflux at the tussock tundra and upland boreal forest sites. Air temperature was an important secondary control on C efflux at the boreal forest site, as shown in the three-dimensional plot.

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3.4. CO2 Efflux Estimates

[24] In tussock tundra, the seasonal pattern of CO2 efflux closely resembled the seasonal pattern of subnivean [CO2], with a period of relatively high efflux rates in late November (∼0.5 g C m−2 day−1), a prolonged period with very low rates (<0.03 g C m−2 day−1) and a gradual resumption of relatively high efflux rates during late April and May (Figure 6). There was a brief pulse of CO2 efflux during snowmelt (∼0.5 g C m−2 day−1) that corresponded with the highest observed values of subnivean [CO2] in tussock tundra. At the boreal forest site, the seasonal pattern of CO2 efflux was somewhat dissimilar to that of subnivean [CO2], as a result of seasonal changes in atmospheric [CO2], snow depth and snow density. Peak rates of CO2 efflux were observed during snowpack development, before soils had frozen to depth (∼1.2 g C m−2 day−1), during a brief thaw in early December (∼0.8 g C m−2 day−1), during a second brief thaw in early February (∼1.0 g C m−2 day−1) and during snowmelt in April (∼1.2 g C m−2 day−1).

image

Figure 6. Seasonal pattern of winter C efflux from the tussock tundra and upland boreal forest sites. Estimates of C efflux were made for the period when snow depths were consistently greater than 15 cm: 6 November 2006 to 22 May 2007 in tussock tundra and 10 November 2006 to 15 April 2007 in the upland boreal forest.

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[25] In tussock tundra, the soil was consistently covered by at least 15 cm of snow from 6 November 2006 to 22 May 2007. During this snow-covered period, the soils of tussock tundra lost an estimated 23.6 g C m−2 to the atmosphere. At the upland boreal forest site, soils were consistently covered by more than 15 cm of snow between 10 November 2006 and 15 April 2007. During this period, an estimated 74.7 g C m−2 were lost from the soil to the atmosphere.

4. Discussion

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

4.1. CO2 Measurements

[26] Our measurements of atmospheric and subnivean [CO2] were generally consistent with those in previous studies. In tussock tundra, the limited diurnal variation and both the timing and amplitude of the seasonal increase in atmospheric [CO2] are consistent with observations in Barrow, AK [Keeling and Whorf, 2005]. The strong diurnal, daily and seasonal variations in atmospheric [CO2] observed at our boreal forest site, which lies within the Municipality of Anchorage, are much like those reported for Salt Lake City, UT [Pataki et al., 2003]. As demonstrated in Salt Lake City, ecosystem respiration and fossil fuel combustion were probably major sources of CO2, while seasonal and diurnal variation in the depth of the planetary boundary layer and periodic atmospheric inversions were probably important controls on atmospheric [CO2] at our site.

[27] Kelly et al. [1968] presented continuous measurements of subnivean [CO2] from coastal beach ridge tundra, near Barrow, AK. The seasonal pattern of beach ridge subnivean [CO2] was very similar to our observations in tussock tundra, with the highest values observed during the early winter months, a prolonged midwinter period with subnivean [CO2] only slightly higher than atmospheric [CO2], and an increase in subnivean [CO2] during snowmelt in the late spring. The seasonal development and maximum depth of the beach ridge snowpack was similar to that observed at our tussock tundra site. The differences between subnivean and atmospheric [CO2] during the early winter and late spring were generally greater at our site, though the difference observed during the prolonged midwinter period were very similar (5–10 μmol/mol). We are not aware of another study that has continuously measured subnivean [CO2] in a boreal forest, though our analyses suggest the seasonal pattern may vary strongly from one year to the next with inter-annual differences in air temperatures, snow cover and soil temperatures.

4.2. CO2 Efflux Estimates

[28] In previous studies of tussock tundra, investigators have made point measurements, using either snow probes or flux chambers at the snow surface, and estimated total winter C efflux at between 20 and 70 g C m−2 [Oechel et al., 1997; Fahnestock et al., 1999; Welker et al., 2000]. Our estimate of total C efflux during the snow-covered season of 2006–2007 (23.6 g C m−2) falls within the lower end of the range observed in studies that have used snow probes or flux chambers. Previous estimates of total winter C efflux from tussock tundra have, however, been applied to a period of between 229 [Oechel et al., 1997] and 243 days [Fahnestock et al., 1999; Welker et al., 2000]. The 2006–2007 snowpack did not develop until late October and we calculated C efflux over a 198 day period between 6 November 2006 and 22 May 2007, when the snow depth was greater than 15 cm. After taking this difference into account, our estimate of total winter C efflux agrees very well with previous estimates made using snow probes and flux chambers in tussock tundra. Investigators have also used chemical base traps to estimate total winter C efflux. Studies using base traps have generated estimates of winter C efflux that are both well below (1 g C m−2 [Welker et al., 2000]) and well above the range estimated using snow probes and flux chambers (190 g C m−2 [Grogan and Chapin, 1999]). Chemical base traps reduce chamber air [CO2] and may draw CO2 out of the soil that would not efflux naturally. Furthermore, a low CO2 environment may stimulate respiration [Bekku et al., 1997]. When compared with other methods, base traps tend to overestimate low fluxes [Davidson et al., 2002], helping to explain the results of Grogan and Chapin [1999]. The low fluxes reported in the study of Welker et al. [2000] may reflect inter-annual differences in climate, as air temperatures were very cold during November and the snowpack did not develop until December of 1994. Alternatively, the low flux estimates may reflect methodological problems associated with the use of liquid base traps in subzero temperatures.

[29] Investigators in boreal forests have used both flux chamber and snow CO2 profiles to estimate winter C efflux from soils to the atmosphere. Estimates of total C efflux for the snow-covered season in a wide variety of boreal forest ecosystems have fallen between 20 and 144 g C m−2 [Winston et al., 1997; Wang et al., 2002; Vogel et al., 2005; Ilvesniemi et al., 2005; Kim et al., 2007]. Our estimate of total winter C efflux from the soils of a mixed white spruce/paper birch ecosystem (74.7 g C m−2) is intermediate among those from a wide range of boreal forests and generally greater than estimates from black spruce forests in central Alaska [Vogel et al., 2005]. Monson et al. [2006a] showed that winter CO2 efflux from tree wells, where the snowpack is relatively shallow and soils are colder, is considerably lower than CO2 efflux from open areas in a subalpine forest. Our measurements were made in an open area, approximately 30 cm beyond the canopy of the nearest spruce tree. Total winter C efflux from the soils of our upland boreal forest site would likely have been lower, had we accounted for the reduced flux from tree wells.

4.3. Controls on CO2 Efflux

[30] Cold temperature laboratory incubations (−10 to −0.5°C) of soils from tussock tundra have shown a close relationship between respiration and temperature, with very high temperature coefficients (Q10s) [Mikan et al., 2002]. We found a close correlation between CO2 efflux and soil temperature at 10 cm over the course of the winter, with a Q10 value of 18.2. While not nearly as high as the Q10 values reported by Mikan et al. [2002], our results do support the conclusion that respiration is controlled by different processes above versus below freezing. Mikan et al. [2002] suggested that respiration in frozen soils may be limited by indirect effects of cold temperatures, such as extracellular barriers to diffusion and or intracellular desiccation. It is worth noting that earlier efforts to model winter CO2 efflux from high-latitude ecosystems have used much lower Q10 values of 1.5 to 2.0 [McGuire et al., 2000], which do not account for the rapid decline in respiration as soils begin to freeze.

[31] A simple modeling exercise, using respiration- temperature relationships developed in the laboratory, substantially overestimated CO2 efflux estimates made in the field and suggested that deep mineral soils may contribute more than half of the CO2 produced during winter [Schimel et al., 2006]. We found that soil temperatures at 10 cm in the organic layer were more closely correlated with our estimates of CO2 efflux than were soil temperatures at 25 cm, in the upper layers of the mineral soil. This observation suggests that deep mineral soils may not be as important to winter CO2 efflux as suggested by laboratory incubations [Schimel et al., 2006]. Many of the discrepancies between cold-temperature laboratory incubations and field observations of winter CO2 efflux could be explained if CO2 production and CO2 efflux are strongly decoupled in frozen soils. Several studies have shown evidence that CO2 may be physically forced from soil pores during freezeup or trapped in ice [Coyne and Kelley, 1971; Oechel et al., 1997]. Alternatively, laboratory incubations using disturbed soils may not provide a realistic depiction of cold temperature CO2 production.

[32] At our upland boreal forest site, we found a much better correlation between winter CO2 efflux and shallow soil temperatures (5 cm) than we did between CO2 efflux and deep soil temperatures (25 cm), consistent with our observations in tussock tundra. The correlation between CO2 efflux and soil temperature at the boreal site was, however, much weaker than observed in tussock tundra. We were able to explain a much greater proportion of the variation when winter CO2 efflux was modeled as a function of both air and soil temperatures, as the snowpack at our boreal site was deep enough to decouple air and soil temperatures. The importance of air temperature is illustrated during a brief thaw event in early February. During this period, air temperatures rose above freezing for 8 consecutive days, while soil temperatures remained unchanged. Subnivean [CO2] reached the highest values observed outside of the snowmelt period and our estimates of CO2 efflux reached the highest values observed during the midwinter period. Snow pits were excavated and snow density measurements were made within a few days of the end of the thaw, ensuring that our CO2 efflux estimates reflect the change in snowpack density.

[33] The importance of air temperature as a predictor of winter CO2 efflux at our boreal forest site suggests that white spruce trees became active during at least one warm period. This conclusion is consistent with observations in a mixed conifer-broadleaf forest in northern Japan, where a close correlation was observed between air temperature and CO2 concentrations in soil pores beneath the snowpack [Takagi et al., 2005]. Net photosynthesis has been shown under field conditions in red spruce [Schaberg et al., 1995] and eastern hemlock [Hadley, 2000] during winter at lower latitudes, particularly during multiday thaws. Observations at our site have revealed low levels of light saturated net photosynthesis (∼0.50 μmol CO2 m−2 s−1) in white spruce with needle temperatures slightly below 0°C (P. Sullivan, unpublished data). White spruce trees at our site may contribute directly, through increased rates of root respiration, or indirectly to increased rates of winter CO2 efflux. Brooks et al. [2004] showed that winter microbial respiration may be constrained by the availability of labile C. Trees may contribute high-quality C to winter microbial communities through exudation or fine root death. Mature trees probably first rely upon water stored in sapwood to meet winter transpiration demands [Boyce and Lucero, 1999]. If the sapwood reservoir becomes depleted, trees may become dependant upon water uptake from frozen soils, which could lead to water stress and, perhaps, fine root death. Widespread fine root mortality may, in turn, stimulate microbial respiration.

[34] Results of our study clearly show that temperature is an important within-site control on belowground respiration during winter, implying that warmer air and soil temperatures in a changing climate may increase rates of winter C efflux from arctic and boreal ecosystems. Monson et al. [2006b], however, clearly showed that snow depth is an important control on winter soil temperatures and winter CO2 efflux. If winter snowpacks decline in arctic and boreal ecosystems, loss of their insulating properties may reduce winter C losses, even while air temperatures rise.

Acknowledgments

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

[35] This project was supported by National Science Foundation grants 0528748 and 0612534, along with an award from the University of Alaska Anchorage Chancellor's Fund. We thank S. Cahoon and S. Baaken for field assistance. Toolik Field Station and Veco Polar Resources provided valuable logistical support. G. Shaver and J. Laundre provided barometric pressure data from the Arctic Long-term Ecological Research program, supported by National Science Foundation grant 9810222. Two anonymous reviewers provided comments that improved earlier drafts of this manuscript.

References

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Methods
  5. 3. Results
  6. 4. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information
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