EVALUACIÓN DEL MODELO DE CALIFICACIÓN (SISTEMA DE CONTROL

The relatively small surface CO2 fluxes measured throughout the 48-h sampling period are consistent

with in situ surface flux rates measured in Taylor Valley by Burkins et al. (2001) and Parsons et al. (2004), as well as results presented in Chapter 3. However, they are an order of magnitude lower than in situ surface CO2 flux rates measured by Ball et al. (2009). All studies utilised sites with similar

soil pH, EC, organic and inorganic C values; soil moisture content and the magnitude of diel

temperature variability were also comparable. Despite the relatively high flux rates measured by Ball et al. (2009), the variability in surface CO2 fluxes seen in their study and by Parsons et al. (2004)

showed similar diel patterns to those observed in this study, with positive and negative surface fluxes corresponding to periods when soil temperatures were increasing, and decreasing, respectively. Surface CO2 fluxes were most strongly correlated with air temperature, measured 2 cm above the

soil surface (R2_{= 0.96; p = <0.001), and less so with soil temperature at 5 cm depth (R}2 _{= 0.78; p =}

<0.001; Figure 4.5). Aside from the correlation with air temperature, the best explanatory variable for the magnitude of surface flux rates was the rate of change in soil temperature at 15 cm depth (R2

= 0.85; p = <0.001; Figure 4.6). The rate of change in soil temperature at 5 cm depth only explained 43% of flux variability (p = 0.02).

The strong correlation between surface CO2 flux rate and air temperature is difficult to interpret, and

there may in fact be no direct causative link. However, the strong correlation between surface CO2

flux rate and ΔT/Δt at 15 cm depth is consistent with surface CO2 fluxes being driven by temperature-

controlled solubility of CO2 in soil solution, according to Henry’s Law, as posited by Parsons et al.

(2004) and Ball et al. (2009). The greater influence of soil temperature changes at 15 cm depth relative to 5 cm is surprising, as the amplitude of temperature variability is greater at 5 cm depth,

and soil moisture content is similar at both depths. The correlation between surface CO2 flux rate and

the rate of change in soil temperature at 15 cm depth in this study contrasts with the strong

correlation between surface CO2flux rates and the rate of change in soil temperature at 5 cm depth

shown by Parsons et al. (2004), although their study did not include soil temperature measurements at any other depths.

Figure 4.5 Relationship between average temperature over the surface flux sampling period and surface CO2 flux rates at Site B, Taylor Valley.

Figure 4.6 Relationship between the average rate of change in soil temperature over the surface

flux sampling period at 5 cm and 15 cm depth with surface CO2 flux rates at Site B, Taylor

Valley.

Whereas Ball et al. (2009) inferred from their heat sterilised in situ microcosm study that a biological CO2 flux was superimposed on the abiotic temperature-related fluxes, cumulative 24-hr CO2 fluxes in

this study detect no statistically significant net flux over six successive 24-hr periods (Figure 4.7), and hence suggest a purely abiotically-driven system, where influxes and effluxes balance. Nonetheless, the presence of a biotic component to the flux must be considered. This is explored further below in

relation to the δ13_C

CO2 of the soil atmosphere and surface CO2 fluxes. Regardless of the significance of

a biological component to the total CO2 flux, abiotic processes must be invoked – at least to explain

CO2 consumption beneath the opaque surface chambers used in this study, which precluded

photosynthetic uptake of CO2.

Figure 4.7 Net cumulative surface CO2 fluxes at Site B, Taylor Valley, over consecutive 24-h periods

beginning at 14:30 h on Day 1. Maximum and minimum net fluxes represent uncertainties calculated from the standard error of the mean.

In Chapter 3, temperature-controlled exsolution and dissolution of CO2, according to Henry’s Law,

were modelled analytically and compared to measured changes in subsurface soil CO2

concentrations, as a test of the hypothesis that this phenomenon was the main driver of CO2

dynamics. However, this approach was predicated on a closed-system approximation. In this study, the relatively high frequency at which subsurface CO2 concentration measurements were made

enables subsurface storage fluxes (fluxes that result in changes in CO2 storage in the soil) to be

estimated over four-hourly intervals. Results show the amplitude of surface fluxes is more than five times larger than storage fluxes, and hence a closed system assumption is not appropriate, at least

for near-surface samples. However, the storage fluxes themselves provide another test of the hypothesis, as they reflect the production and consumption of CO2 in the soil, and can be considered

alongside soil temperature changes.

Like surface fluxes, storage fluxes also showed diel variation (Figure 4.3A), switching from positive to negative as CO2 concentration within the profile increased and decreased, respectively. This

variability led surface flux variations by 4−6 hours. Storage fluxes were explained by the rate of

change in soil temperature at 5 cm depth (R2 _{= 0.84; p = <0.001; Figure 4.8), but showed no}

relationship to the rate of change in soil temperature at 15 cm depth. This is consistent with the

suggestion that Henry’s Law-driven dissolution and exsolution of CO2 drives changes in subsurface

CO2 concentrations, and indicates that, as expected, the shallower depths of the soil (where diel

temperature changes are greatest) are the most important for determining the subsurface CO2

concentration changes that ultimately drive surface fluxes. The better correlation between surface CO2flux rates and the rate of change in soil temperature at 15 cm depth compared to 5 cm depth

discussed above is most likely an artefact. Lags in warming and cooling of the subsoil relative to shallower depths, and the lag between subsurface CO2 production or consumption and changes in

surface CO2 flux may bring about coincidence of their behaviours and promote the strong

correlation.

Figure 4.8 Relationship between the rate of change in soil temperature at 5 cm and 15 cm depth

with subsurface storage CO2 flux rates at Site B, Taylor Valley. The solid black lines

represent linear relationships with equations as follows. At 5 cm depth, y = 0.0059x + 0.0002. At 15 cm depth, y = 0.0047x - 0.0001.