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Keywords:

  • CO2 efflux;
  • minirhizotron;
  • mycorrhizas;
  • photosynthesis;
  • rain pulse;
  • temperature-independent respiration;
  • wireless networks

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • • 
    Characterization of spatial and temporal variation of soil respiration coupled with fine root and rhizomorph dynamics is necessary to understand the mechanisms that regulate soil respiration.
  • • 
    A dense wireless network array of soil CO2 sensors in combination with minirhizotron tubes was used to continuously measure soil respiration over 1 yr in a mixed conifer forest in California, USA, in two adjacent areas with different vegetation types: an area with woody vegetation (Wv) and an area with scattered herbaceous vegetation (Hv).
  • • 
    Annual soil respiration rates and the lengths of fine roots and rhizomorphs were greater at Wv than at Hv. Soil respiration was positively correlated with fine roots and rhizomorphs at Wv but only with fine roots at Hv. Diel and seasonal soil respiration patterns were decoupled with soil temperature at Wv but not at Hv. When decoupled, higher soil respiration rates were observed at increasing temperatures, demonstrating a hysteresis effect. The diel hysteresis at Wv was explained by including the temperature-dependent component of soil respiration and the variation dependent on photosynthetically active radiation.
  • • 
    The results show that vegetation type and fine root and rhizomorph dynamics influence soil respiration in addition to changes in light, temperature and moisture.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Soils represent the largest carbon pool in terrestrial ecosystems (Dixon et al., 1994), and understanding the effect of climate variation on soil respiration (Rs) is crucial for accurate estimation of the global carbon balance (Schimel, 1995; Raich et al., 2002). Rs is the synthetic result of heterotrophic respiration (by decomposers) and autotrophic respiration (by roots and mycorrhizas). These processes are regulated by several physical (e.g. soil temperature, moisture, and soil porosity) and biological factors (e.g. root density, microbial community, and photosynthesis) that complicate the mechanistic understanding of Rs (Ryan & Law, 2005). Understanding how these factors regulate Rs at different temporal scales is of critical importance in determining the effect of climate variation on terrestrial carbon fluxes.

Roots are the primary belowground structural element of plants and mycorrhizal fungi are obligate symbionts that form a hyphal network that takes up nutrients and water in exchange for newly fixed plant carbon (Allen et al., 2003). Rhizomorphs are large cords of fungal hyphae that transport nutrients and water, and a large proportion appear to be mycorrhizal (Smith & Read, 1997). To date, the relationship between mycorrhizal fungi and Rs has remained unclear because limited studies have been carried out in the field (Langley et al., 2005; Heinemeyer et al., 2006; Heinemeyer et al., 2007). Thus, the study of the spatio-temporal dynamics of fine roots and rhizomorphs is a key element in understanding variations in autotrophic respiration and therefore total Rs (Hanson et al., 2000; Misson et al., 2006; Vargas & Allen, in press b).

Developments in automated measurements of Rs provide an opportunity to study relationships between Rs and soil temperature or water content at different temporal scales (Goulden & Crill, 1997; Drewitt et al., 2002). The high frequency of these measurements enables detection of responses to sudden events, such as rain pulses, which are important for the understanding of seasonal patterns (Irvine & Law, 2002; Jassal et al., 2005). Furthermore, diel Rs patterns can be studied along with variation in temperature and light (Liu et al., 2006; Carbone & Vargas, 2008). Recent studies have shown that, at the diel scale, Rs and soil temperature may be decoupled, showing a hysteresis effect in boreal forests (Gaumont-Guay et al., 2006), tropical forests (Vargas & Allen, in press a), and Mediterranean ecosystems (Tang et al., 2005a; Vargas & Allen, in press b). Several studies have postulated that photosynthesis regulates diel variation in Rs rates and may be an explanation of the temperature-independent component of Rs (Tang et al., 2005a; Liu et al., 2006). Thus, it is important to test the influence of light, temperature and moisture on Rs at multiple spatial and temporal scales.

In this study, we used continuous measurements of soil CO2 concentration in the soil profile in conjunction with minirhizotron measurements to calculate Rs. The use of minirhizotrons is a nondestructive technique to measure changes in fine roots and rhizomorphs in space and time (Pregitzer et al., 2002; Treseder et al., 2005), and we developed a wireless network array of soil sensors (Allen et al., 2007; Vargas & Allen, in press b). Using this array, we simultaneously quantified Rs at multiple points in two adjacent vegetation types of a California mixed conifer forest that included a patch of large trees and an open meadow with scattered herbaceous vegetation. This approach provided the opportunity to test the influence of vegetation type on Rs under similarly varying climatic conditions, at different temporal scales, without disturbing the environment. Our objectives were: to determine the environmental factors that regulate fine root and rhizomorph dynamics; to determine the environmental controls on seasonal and diel patterns in Rs; and to explore the relationship between Rs and fine root and rhizomorph dynamics in two adjacent vegetation types.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Study site

This study was conducted at the James San Jacinto Mountains Reserve, which is part of the UC Natural Reserve System. The James Reserve is located in the San Jacinto Mountains, California, USA (33°48′30″N, 116°46′40″W), at an elevation of 1640 m, and is surrounded by the San Bernardino National Forest. The James Reserve is a mixed conifer and oak forest with precipitation occurring mostly as rain between the months of November and April with a mean annual precipitation of 507 mm and a mean air temperature of 10.3°C (measured since 2000). The James Reserve is a test site for the National Ecological Observatory Network, serves as the Terrestrial Ecology Observing Systems field site for the Center for Embedded Networked Sensing, and is instrumented with a large wireless network of environmental sensors (Allen et al., 2007; Hamilton et al., 2007).

In October 2003, we selected an area of woody vegetation (Wv) and an adjacent area with scattered herbaceous vegetation (Hv). The vascular plants present at Wv were individuals of Quercus kelloggii Newb. (California black oak), Calocedrus decurrens (Torr.) Florin (incense cedar), Arctostaphylos pringlei Parry (manzanita), and Pinus lambertiana Dougl. (sugar pine). All of these species form ectomycorrhizas with the exception of C. decurrens, which forms arbuscular mycorrhizas, and Q. kelloggii, which may form both ecto- and arbuscular mycorrhizas. Hv was dominated by arbuscular mycorrhizal Eriogonum wrightii Torr. Ex Benth (bastard sage) of < 10 cm in height and at a density of nearly two plants m−2. Bastard sage was also present in the understory of Wv with a similar density as at Hv.

Two 5-m transects were established at both Wv and Hv, as described in Supplementary Material Fig. S1. Each transect was instrumented with three minirhizotron tubes and two sensor nodes as part of a wireless network array (see Minirhizotrons and Sensor nodes sections). Soil bulk density was 0.9 g cm−3 at Wv and 1.2 g cm−3 at Hv. Soil texture was 83% sand, 10% silt, and 7% clay at both Wv and Hv. Fine root biomass (0–16 cm) was calculated to be 18 g m−2 at Wv and 10 g m−2 at Hv, and a detailed fine root and rhizomorph profile distribution is presented in Supplementary Material Fig. S2. Fine root nitrogen was 0.58% (± 0.23% SD) and 0.53% (± 0.24% SD), respectively. Soil carbon (0–16 cm depth) at Wv was 3.1% (± 0.5% SD) and that at Hv was 2.4% (± 0.5% SD), while soil nitrogen (0–16 cm depth) was 0.08% (± 0.02% SD) at Wv and 0.05% (± 0.03% SD) at Hv.

Minirhizotrons

During October 2003 we installed three minirhizotron observation tubes 5 cm in diameter and 1 m in length at each of the 5-m transects (Supplementary Material Fig. S1). Collection of images for this research started in January 2006 to allow fine roots to recolonize the soil surrounding the tubes. Images from all the tubes were collected in weekly campaigns between February 2006 and December 2006, with a total of 59 sampling days at intervals that varied from 1 d to 1 month.

Minirhizoron images were collected using a minirhizotron microscope (BTC-10 with I-CAP software; Bartz Technology, Carpinteria, CA, USA). An average of 52 vertical images were collected per tube, and the number of rhizomorphs and fine roots was counted for all collected images. These images include fine roots and rhizomorphs to an average depth of 60 cm at both vegetation types. We used linear regression models to predict lengths based on the number of roots or rhizomorphs reported by Vargas & Allen (in press b) for the study site. We used the information from all 52 images and report length of fine roots and rhizomorphs in cm m−2.

Sensor nodes

In October 2005 we installed two sensor nodes at each 5-m transect in association with the minirhizotron tubes (Supplementary Material Fig. S1). At Wv the nodes were within a 2-m radius of plants, and at Hv within a 1-m radius. At each node we measured photosynthetically active radiation (PAR), air relative humidity, air temperature and barometric pressure at a height of 2 m, and vapor pressure deficit (VPD) was calculated from air temperature and relative humidity. In addition, we installed solid-state CO2 (GMM 222; Vaisala, Helsiniki, Finland), soil temperature, and soil moisture (ECHO EC-20; Decagon, Pullman, WA, USA) sensors at soil depths of 2, 8 and 16 cm (Allen et al., 2007). The soil temperature and moisture sensors were installed horizontally, and the CO2 sensors were installed vertically, similar to Tang et al. (2005b). All variables were recorded at 5-min intervals and transmitted using a Crossbow Mica2 868/916-Mhz (Crossbow Technology, San Jose, CA, USA) wireless platform to a centralized server at the James Reserve.

Soil CO2 profile

We used a dense array of solid-state CO2 sensors with a total of 24 sensors among transects (four nodes per area). The CO2 sensors had a range of 0–10 000 ppm and were calibrated every 6 months after deployment to ensure the quality of the measurements. To keep the sensors dry, we enclosed them in a watertight container with an opening at the bottom covered with Gortex fabric. Rs was calculated using the flux-gradient method based on concentrations of CO2 in the soil profile (Tang et al. 2005b; Vargas & Allen, in press b). Briefly, the CO2 concentration from the sensors was corrected for temperature and pressure according to the manufacturer's instructions (Vaisala, Helsinki, Finland). The corrected CO2 concentrations were used to calculate Rs using Fick's first law of diffusion, and the diffusivity of soil CO2 in the soil profile was calculated using the Moldrup model (Moldrup et al., 1999).

Rs values from the gradient method were calibrated with Rs values obtained using a soil chamber (Li-8100-102) connected to a soil respiration system (LI-8100; Li-Cor, Lincoln, NE, USA). We installed 10-cm-diameter PVC soil collars associated with each minirhizotron tube in November 2005. The litter layer was very shallow at both vegetation sites (< 2 cm). Soil respiration was measured nearly four times a day (morning and/or afternoon) on the same dates on which the minirhizotron images were collected during the year 2006.

Data analysis

Depending on the best statistical fit, we used either a model for Rs using soil temperature as an independent variable:

  • image(Eqn 1)

or soil temperature and volumetric water content (VWC) as drivers for Rs:

  • image(Eqn 2)

(Rs, soil respiration in µmol CO2 m−2 s−1; T, soil temperature in °C; θ, volumetric water content in mm−3; B0, B1, B2 and B3, model parameters.) Similar models have been used previously in Mediterranean ecosystems (Xu et al., 2004; Tang et al., 2005b). To select the best statistical model for Rs, we used the root mean squared error (RMSE), and the Akaike information criterion (AIC) as a penalized likelihood criterion (Burnham & Anderson, 2002):

  • image(Eqn 3)

(L, the likelihood of the fitted model; p, the total number of parameters in the model.) The best statistical model minimizes the value of AIC.

To test for diel and seasonal hysteresis effects, we used an F-test as explained by Vargas & Allen (in press a). Briefly, we compared the F-values of a single exponential model, using Eqn 1 and assuming no hysteresis effect, with the sum of the F-values of two independent exponential models (Eqn 1) by splitting the data into two sets based on maximum and minimum daily temperatures, assuming a hysteresis effect.

To model significant daily hysteresis loops we first calculated the temperature-dependent component of Rs based on Eqn 1. Then the residuals from Eqn 1 were fit to a linear model based on PAR to explain the diel temperature-independent variation in soil respiration using a similar rational as Liu et al. (2006). The final diel Rs model when hysteresis was present took the form:

  • image(Eqn 4)

In addition, repeated measurements using the GLM procedure were used to test for differences in fine root and rhizomorph lengths between the vegetation types. Pearson correlation coefficients were calculated to test the relationships between the biophysical variables and Rs. All statistical analyses were performed with spss v13 (SPSS, Chicago, IL, USA).

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Environmental variables

We divided Rs into phases from I to VI based on variations in soil temperature and soil VWC during 2006, and we will refer to these throughout the text (Fig. 1). Phase I included days of the year 1 to 50, which corresponded to low soil temperature and low VWC. Phase II included days 51 to 125, which corresponded to increasing soil temperature and high VWC. Phase III included days 126 to 195, which corresponded to increasing soil temperature and decreasing VWC. Phase IV included days 196 to 225 and represents the influence of a monsoon event. Phase V included days 226 to 330, which corresponded to decreasing temperatures with low VWC. Phase VI included days 331 to 365, which corresponded to low temperatures with increasing VWC.

image

Figure 1. Daily means of climate variables at the James Reserve during 2006, including (a) mean soil temperature in the 0–16-cm layer, (b) mean soil volumetric water content (VWC) in the 0–16-cm layer, and (c) vapor pressure deficit (VPD). Solid line, woody vegetation; dashed line, herbaceous vegetation. Vertical dashed lines divide the phases of study (I to VI) according to changes in soil moisture and temperature (see the Results). DOY, day of the year during 2006. Phase IV represents a monsoon event.

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The annual mean soil temperature was 11.9°C at Wv and 10.9°C at Hv. The soil VWC content was higher at Wv, especially during phases II and III. VPD was lower during phase II (mean = 0.18 kPa) and higher during phases III and IV (mean = 0.96 and 0.7 kPa, respectively) in both areas. The monsoon event reduced the mean soil temperature from nearly 25 to 18°C, increased the mean soil VWC from nearly 0.1 to 0.9 m3 m−3 and reduced the mean VPD from nearly 1.4 to 0.28 kPa in both areas.

Fine root and rhizomorph lengths

The minirhizotron measurements showed significant differences in belowground architecture and seasonality of fine roots (F = 171.139, P < 0.001) and rhizomorphs (F = 1714.66, P < 0.001) between vegetation types. Fine root length was significantly higher (P < 0.05) at Wv during phases I, II, and VI (Fig. 2a). The mean length of fine roots varied from 47.9 to 75.2 cm1 m−2 at Wv and between 29.6 and 56.4 cm1 m−2 at Hv. Greater fine root length was observed during phase IV at both sites. Fine roots were significantly (P < 0.05) positively correlated with soil temperature at Wv and with soil temperature, VPD and PAR at Hv (Table 1).

image

Figure 2. Length of (a) fine roots and (b) rhizomorphs in the woody (circles) and herbaceous (triangles) areas during the phases of the year of study (see Fig. 1). Error bars represent standard deviations of the mean. *P < 0.05, **P < 0.01, ***P < 0.001.

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Table 1.  Pearson correlation coefficients between soil respiration (Rs), fine root length, rhizomorph length, soil temperature, volumetric water content (VWC), vapor pressure deficit (VPD), and photosynthetically active radiation (PAR) at the woody vegetation (Wv) and the herbaceous vegetation (Hv) sites
 FineSoil
Rsroot lengthRhizomorph lengthtemperatureVWCVPDPAR
  1. n = 59; *P < 0.05; ***P < 0.001.

Woody vegetation (Wv)
Rs10.583***0.393*0.871***−0.405***0.586***0.685***
Fine root length 10.1430.277*−0.01 0.109 0.218
Rhizomorph length  10.537***−0.510***0.406*** 0.05
Soil temperature   1−0.626***0.774***0.554***
VWC     1−0.658***−0.075
VPD      10.507***
PAR       1
Herbaceous vegetation (Hv)
Rs10.287*0.0720.595*** 0.0380.320***0.593***
Fine root length 10.0720.614*** 0.0120.330*0.790***
Rhizomorph length  10.118−0.045 0.043 0.034
Soil temperature   1−0.630***0.766***0.638***
VWC     1−0.708***−0.066
VPD      10.442***
PAR       1

Rhizomorph length was always significantly (P < 0.05) higher at Wv, with mean values between 123.9 and 205 cm1 m−2. The length of rhizomorphs associated with Hv ranged from 29.4 to 94.2 cm1 m−2 (Fig. 2b). Rhizomorph development responded positively to the monsoon event (phase IV) at Wv but not at Hv. Rhizomorph length was significantly (P < 0.001) positively correlated with soil temperature and VPD, and negatively correlated (P < 0.001) with VWC at Wv (Table 2). We did not find a significant correlation between rhizomorph length and environmental variables at Hv.

Table 2.  Results of regression analyses relating soil respiration to soil water content and soil temperature at the woody vegetation (Wv) and the herbaceous vegetation (Hv) sites
PeriodModelVegetation typeB0B1B2B3r2P valueRMSEAIC
  1. Model I has the form inline image, model II the form inline image, and model III the form inline image.

  2. The best-fit model parameters (B0, B1, B2 and B3) are reported for each model together with the squared coefficient of regression (r2), the root mean squared error (RMSE) and the Akaike information criterion (AIC; for the seasonal estimates). T is temperature (°C) at a depth of 8 cm, θ is volumetric water content (m−3 m−3), PAR is photosynthetically active radiation (mol m−2 s−1), and Rs is soil respiration (µmol CO2 m−2 s−1). Model parameters were estimated using the Levenberg–Marquardt method.

SeasonIWv1.3960.0490.354< 0.00011.211444
Hv0.5160.0530.750< 0.00010.11 956
IIWv0.1930.08922.149−61.2020.919< 0.00010.42 611
Hv0.1680.05922.095−97.2730.899< 0.00010.091205
Diel
Phase IIIIWv0.0020.614 1.791  0.0010.734< 0.00010.009
IHv0.5180.0590.787< 0.00010.005
Phase IIIWv2.0080.0420.812< 0.00010.003
IHv0.5470.0330.835< 0.00010.001
Phase IIIIIIWv1.9430.034 0.855  0.0010.941< 0.00010.019
IHv1.0750.0130.876< 0.00010.003
Phase IVIWv3.7940.0190.859< 0.00010.017
IHv1.5090.0130.673< 0.00010.004
Phase VIIIWv0.0280.164 1.152  0.0010.912< 0.00010.025
IHv0.6620.250.894< 0.00010.005
Phase VIIIIWv0.0020.745 1.505  0.0010.846< 0.00010.008
IHv0.4930.0310.799< 0.00010.005

Gradient flux method validation

Our calculations of Rs using the gradient method showed a significant positive relationship with Rs using the chamber method during 59 d of measurements. At Wv we found a slope of 0.996 with r2 = 0.73 and P < 0.001 (Fig. 3a). At Hv we found a strong relationship, with a slope of 0.9 and an r2 = 0.91 with P < 0.001 (Fig. 3b). At both sites the intercept was not significantly different from zero and the slope was not significantly different from the 1 : 1 line. The gradient flux method assumes steady-state conditions in CO2 diffusion in the soil. In nearly 5% of our measurements this condition was not met and these measurements were eliminated from the analysis, and the gaps were filled by linear interpolation if they were less than 2 h.

image

Figure 3. Comparisons between soil respiration values from the gradient method and from the chamber method using a soil respiration system (LI-8100) with woody vegetation (a) and scatter herbaceous vegetation (b).

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Seasonal variation of soil respiration

Mean annual Rs at Wv was 2.7 µmol CO2 m−2 s−1, but the mean annual value ranged between 3.3 and 1.9 µmol CO2 m−2 s−1 with a coefficient of variation (CV) of 15.5% among nodes (Fig. 4a). Despite the large variation in mean annual Rs, we found a similar seasonal pattern among the nodes at Wv, especially in their response to the monsoon event at phase IV (Fig. 4a,c). During this phase we observed a mean Rs of 5.6 µmol CO2 m−2 s−1, which represents an increase of nearly 100% from the mean annual rate.

image

Figure 4. Seasonal patterns of soil respiration. (a, b) Seasonal course of daily mean soil respiration with (a) woody vegetation and (b) herbaceous vegetation at the James Reserve. Each ‘node’ represents a sampling point within two transects at each site (see Materials and Methods). (c, d) Daily mean of soil respiration for (c) woody vegetation and (d) herbaceous vegetation generated from values of all nodes at each site. Roman numbers indicate phases of the study (see Fig. 1). DOY, day of the year during 2006.

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The mean annual Rs at Hv was 0.9 µmol CO2 m−2 s−1, and we found that the mean annual value at this site ranged between 0.6 and 1.2 µmol CO2 m−2 s−1 with a CV of 5% among nodes (Fig. 4b). The monsoon event (phase IV) was not evident for nodes 5, 6 and 8, but this event increased Rs at node 7 to nearly 5 µmol CO2 m−2 s−1 (Fig. 3b,d). During this phase we observed a mean Rs of 1.9 µmol CO2 m−2 s−1, which also represents an increase of nearly 100% from the mean annual rate.

The best model to explain seasonal variation in Rs for Wv was a function of soil temperature and soil VWC (Table 2). In addition, we observed a significant (P < 0.001) hysteresis effect of Rs with respect to soil temperature, with higher rates when temperatures were increasing and lower rates when temperatures were decreasing (Fig. 5a). When temperatures were increasing, Rs at 17°C on day of the year 136 was 5.7 µmol CO2 m−2 s−1, but when temperatures were decreasing, Rs at the same temperature but on day of the year 270 was 0.82 µmol CO2 m−2 s−1. This represents a difference of nearly 86% in Rs at similar temperatures. The most parsimonious model to explain Rs at Hv, based on the AIC, was soil temperature alone (Fig. 5b). However, the addition of moisture to the model increased the r2 value and reduced the RMSE (Table 2), suggesting that soil VWC also has an important influence on Rs at Hv.

image

Figure 5. Relationship between daily mean soil respiration and daily soil temperature at a depth of 8 cm for (a) woody vegetation and (b) herbaceous vegetation. Open circles, increasing temperatures; closed circles, decreasing temperatures during the year of 2006. Solid line, best fit of an exponential equation (see Table 1).

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We compared the full data set based on daily averages when all biophysical variables were available (fine root length, rhizomorph length, soil temperature, VWC, VPD, and PAR; n = 59 d). At Wv we found that Rs was significantly correlated (P < 0.05) with fine root length, soil temperature, VWC, VPD, PAR and rhizomorph length (Table 1). By contrast, Rs at Hv was significantly correlated (P < 0.05) with soil temperature, VPD, PAR and fine root length (Table 1).

Diel variation of soil respiration

Diel Rs was processed as the mean for all days during a specific phase for both vegetation types. During all phases, diel Rs showed higher rates at Wv than at Hv. At Wv we observed that Rs was decoupled from soil temperature and we observed a significant hysteresis effect (P < 0.001) during phases I, III, V, and VI (Fig. 6). We tested whether this effect was an artefact of soil temperature at different depths, but we found the effect to be significant at all measured depths. In addition, soil CO2 production was higher in the 2–8-cm layer than in the 8–16-cm layer (data not shown), and root length was also greater at shallower depths (Supplementary Material Fig. S2). Thus, we used soil temperature at 8 cm to represent the diel and seasonal patterns. Hysteresis was always clockwise, and maximum Rs rates were between 13:00 and 17:00 h during all phases. Although all these loops were significant, phases III and V showed the largest effects. During phases with hysteresis, Rs rates were higher when temperatures were increasing than when temperatures were decreasing (Fig. 6a,c,e,f). The mean difference in Rs between 11:00 and 23:00 h across phases was 0.9 µmol CO2 m−2 s−1 or 24%. The difference during phase V between 12:00 and 20:00 h was 1.1 µmol CO2 m−2 s−1 or 69%.

image

Figure 6. Diel patterns of soil respiration and soil temperature at a depth of 8 cm for woody vegetation (closed circles) and herbaceous vegetation (triangles). Open circles, increasing temperatures during the day under woody vegetation. The arrows indicate the direction of the hysteresis effect, and time in parentheses indicates maximum soil respiration rates. Letters indicate different phases during 2006: (a) phase I, (b) phase II, (c) phase III, (d) phase IV, (e) phase V, and (f) phase VI (see Fig. 1 for details).

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The diel hysteresis of Rs with soil temperature at Wv was observed when daily VPD maximums were > 0.6 kPa. At similar VPD values soil temperature was coupled with Rs at Hv (Supplementary Material Fig. S3). When diel Rs was decoupled with soil temperature at Wv, a model including PAR (Eqn 4) was able to represent the observed variation, with r2 values between 0.7 and 0.9 (P < 0.001), increasing the predictability compared with the use of temperature alone (Eqn 1; Table 2). By contrast, at Hv during all phases Rs was explained by Eqn 1, with an overall r2 value of nearly 0.8 and P < 0.001 (Table 2).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Seasonal variation of soil respiration

We observed larger spatial variation in Rs at Wv than at Hv, suggesting higher variation at small scales in the presence of woody vegetation and with greater root and rhizomorph length. Furthermore, we found that individual nodes can vary by up to 30% of the stand-level mean annual Rs in both vegetation types. Our results support the idea that systematic errors, based on spatial heterogeneity, may have large implications for modeling ecosystem Rs (Law et al., 2001).

Seasonal patterns of Rs were explained by a function that combined soil temperature and VWC at Wv. A similar function has been used to explain seasonal Rs in Mediterranean ecosystems where water is limiting during the dry season (Xu et al., 2004; Tang et al., 2005b). Although the most parsimonious model for Hv included only soil temperature, our results suggest that soil VWC is an important driver for Rs, as is expected for a site with hot, dry summers and cold, moist winters. However, differences in model structures reflect differences in the response of the autotrophic and heterotrophic components of Rs to variation in environmental factors. Thus, our results suggest that the processes that regulate Rs at Wv may be more complex than at Hv.

We found a seasonal hysteresis effect on Rs at Wv, with higher rates when temperatures were increasing early in the growing season. The high rates were associated with higher soil VWC, increasing soil temperatures and greater lengths of fine roots and rhizomorphs. Lower rates of Rs were associated with decreasing temperatures, the late summer drought conditions and a decrease in rhizomorph lengths. A similar pattern of seasonal hysteresis effect on Rs with respect to soil temperature, VWC and root production has been observed in a boreal aspen (Populus tremuloides) stand (Gaumont-Guay et al., 2006). By contrast, an opposite pattern of seasonal hysteresis was observed in other temperate forests where Rs was lower in early summer (Moren & Lindroth, 2000; Drewitt et al., 2002). These sites exhibited an increase in Rs that was attributed to high soil microbial activity in response to the warming of deeper soil layers during late summer. We did not find a seasonal hysteresis effect on Rs at Hv; therefore, we further hypothesize that either (1) this effect may be a result of a differential contribution of heterotrophic and autotrophic components to Rs and their response to changes in soil temperature and soil VWC, or (2) there could be a difference in the relative contributions of growth respiration and maintenance respiration in the autotrophic component of Rs that may vary seasonally and may contribute to the hysteresis effect at Wv. Further studies combining automated measurements of Rs, fine root length and rhizomorph length with isotopic techniques may help to separate the contributions of the components of Rs. Carbone et al. (in press) have reported the advantages of combining autochambers and isotope measurements to partition soil respiration in arid ecosystems.

Our research provides evidence that the study of fine root and rhizomorph dynamics may help in interpreting seasonal variation and pulses of Rs. Our data suggest that rhizomorph length was correlated with Rs at the seasonal scale. Furthermore, rhizomorphs appeared to be crucial to maintaining activity during drier events and to the ability to access water from the smaller micropores in the soil (Allen, 2007). It has been observed that rhizomorph length can change by up to 100 cm m2 in < 4 d, demonstrating the high plasticity of these structures, and could influence Rs rates (Vargas & Allen, in press b).

Fine root dynamics followed a similar seasonal pattern at both sites but this was not the case for rhizomorphs. Rhizomorphs showed greater variation at Wv, suggesting higher activity than at Hv. At the end of phase III, soil VWC decreased to nearly 10%, with soil temperatures of nearly 25°C, resulting in decreases in Rs in both vegetation types. During the monsoon event (phase VI), we observed an increase in Rs associated with an increase in root and rhizomorph lengths at Wv, but only of fine root length at Hv. This pulse in Rs represented an increase of 100% over the annual mean rate, and is comparable with that found in previous studies (Tang et al., 2005b; Misson et al., 2006). Similar responses of Rs following rain events have been attributed to an increase in CO2 production in the soil as a result of enhanced decomposition of available carbon compounds and microbial population growth (Xu et al., 2004; Jassal et al., 2005). We found that during this phase Rs was coupled with soil temperature, but our results suggest that a fraction of the enhancement of CO2 production may be associated with an increase in fine root and rhizomorph metabolic activity, as seen in a previous study (Heinemeyer et al., 2007). Therefore, subsequent studies should aim to partition heterotrophic and autotrophic sources (accounting for root and rhizomorph components) of Rs during rain pulses in this ecosystem.

Diel variation of soil respiration

Our results show that diel patterns of Rs were different depending on the vegetation type, suggesting the influence of different plant physiological factors influencing Rs. We found that diel Rs at Hv was coupled with soil temperature, while diel Rs at Wv was always higher when temperatures were increasing than when temperatures were decreasing, producing a clockwise hysteresis loop. We postulate that this pattern may be regulated by photosynthesis of woody plants, as the temperature-independent component of the diel variation was explained by variation in PAR, as seen in a previous study (Liu et al., 2006). These results add to the increasing evidence that photosynthesis may play a role in regulating diel Rs (Högberg et al., 2001; Bowling et al., 2002; Irvine et al., 2005; Tang et al., 2005a; Liu et al., 2006), and we observed lags between Rs and PAR of up to 5 h that are comparable with the photosynthesis lags from hours to days that have been reported (Bowling et al., 2002; McDowell et al., 2004; Tang et al., 2005a; Carbone & Trumbore, 2007). The diel hysteresis effect was observed at Wv when VPD values were higher than 0.6 kPa. These plants are deep-rooted and may have access to deeper water at the site. Many studies have shown that higher VPD promotes partial stomatal closure which decreases photosynthesis, especially in ecosystems with low soil moisture (Baldocchi, 1997; Arneth et al., 1998; Hunt et al., 2002). We postulate that, under stress conditions of low soil moisture and higher VPD values, woody vegetation may experience lags between photosynthesis and Rs. A similar pattern has been observed during the dry season in another Mediterranean ecosystem (Tang et al., 2005a). Furthermore, under these conditions we observed an increase in rhizomorph lengths, suggesting a carbon investment from the plants to the fungi that may also influence autotrophic Rs rates.

We cannot exclude the possibility that diel Rs may be regulated by a combination of physical and biological processes. It is known that changes in soil temperature and soil moisture affect soil CO2 diffusivity in the soil profile (Simunek & Suarez, 1993). Other studies suggest that time lags associated with photosynthesis and soil respiration are independent of photosynthesis and are commensurate with timescales of CO2 diffusion from the roots to the soil surface (Stoy et al., 2007), or caused by wind-induced pressure pumping (Flechard et al., 2007). Wv and Hv have similar soil texture and soil bulk density and at both sites we observed higher CO2 production from the 2–8-cm soil depth; therefore, we do not attribute diel lags to diffusion differences.

The implications of not accounting for daily or seasonal hysteresis at Hv may result in overestimation or underestimation of Rs depending on the shape and direction of the loop. In the case of a large daily asymmetric loop, as in phase V, daily mean Rs when temperatures were increasing was 2.3 µmol CO2 m−2 s−1, while the daily mean calculated for decreasing temperatures was 1.6 µmol CO2 m−2 s−1. These calculations represent a difference of +28 and −11%, respectively, from the daily mean value of 1.8 µmol CO2 m−2 s−1, accounting for hysteresis. If this exercise is performed for all days during phase V, then the results for cumulative carbon loss vary from a high of 247.9 g C m−2 to a low of 172.8 g C m−2, and a measured value of 195.5 g C m−2 accounting for hysteresis. At the seasonal scale, Rs at Hv had a mean value of 3.1 µmol CO2 m−2 s−1 when temperatures were increasing and a mean value of 2.3 µmol CO2 m−2 s−1 when temperatures were decreasing, representing a difference of nearly ±15%, respectively, from the annual mean value of 2.7 µmol CO2 m−2 s−1. These results suggest that ecosystem soil respiration may be under- or overestimated if systematic measurements are made at maximum or minimum soil respiration rates when a hysteresis effect is present both at diurnal and at seasonal scales. More research is needed to identify how common this effect is in other ecosystems, the biophysical factors that regulate it, and the implications for daily, annual and interannual Rs modeling.

Conclusions

A novel aspect of this study was the integration of multiple points of continuous measurements of soil CO2 profiles with detailed observations of fine roots and rhizomorphs using minirhizotrons. Our results show that higher soil respiration (Rs) rates were associated with woody vegetation (Wv) at both seasonal and diel scales. Further, vegetation at Wv tended to have greater numbers of fine roots and greater rhizomorph lengths than the sparse herbaceous vegetation at Hv. Environmental variables may influence the changes in the lengths of fine roots and rhizomorphs in different ways in the different vegetation types studied. Of note, Rs was positively correlated with fine roots and rhizomorphs at Wv but only with fine roots at Hv. We found a hysteresis loop for seasonal Rs at Wv, where a difference of up to 86% in Rs was observed between increasing and decreasing temperatures. We observed a pulse of Rs during a monsoon event equivalent to a 100% increase compared with the mean annual value of Rs in both vegetation types. This pulse was associated with an increase in fine roots and rhizomorphs at Wv, but only of fine roots at Hv. Rs was decoupled from soil temperature at the diel scale and we found a significant hysteresis effect at Wv but not at Hv. The temperature-independent component of Rs was explained by variation in PAR and in combination with the temperature-dependent component we were able to model the diel hysteresis loops at Wv. In addition, the diel hysteresis was only present at higher VPD values and during periods of rhizomorph growth, suggesting further biological controls on Rs. We suggest that failure to account for possible hysteresis in Rs at diel and seasonal scales may result in the over- or underestimation of Rs, depending on the shape and direction of the loop. Further research is needed to fully understand the biophysical controls on the diel and seasonal patterns of Rs and how plant types and dynamics of fine roots and rhizomorphs influence these patterns.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

We thank Hector Estrada, Alisha Glass, Niles Hasselquist, Kuni Kitajima, Laurel Saltzman, Ayesha Sirajuddin, and William Swenson for help with acquiring minirhizotron images and soil respiration chamber measurements. Chris Glover helped in processing the images. This research was undertaken with funding from the National Science Foundation (grant no. EF-0410408) and from the Center for Embedded Networked Sensing (grant no. CCR-0120778). RV received support from the Consejo Nacional de Ciencia y Tecnologia and the Kearney Foundation. RV was supported by grant DEB-0639235 while writing this manuscript. Dennis Baldocchi, Mariah Carbone, Siyan Ma, and Youngryel Ryu provided helpful comments on an early draft of the manuscript. The authors would like to thank Richard Norby and three anonymous referees for useful comments on a previous draft of this work.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Fig. S1 Experimental design at the James San Jacinto Mountains Reserve, a mixed temperate forest in Southern California, USA.

Fig. S2 Profile of fine roots and rhizomorphs at the woody vegetation and the scatter herbaceous vegetation sites.

Fig. S3 Diel patterns of vapor pressure deficit (VPD), photosynthetically active radiation (PAR), and soil respiration at the James Reserve.

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NPH_2481_sm_FigS1-S3.doc17450KSupporting info item