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Keywords:

  • Soil respiration;
  • root respiration;
  • rhizosphere;
  • mycorrhiza;
  • alder

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results and Discussion
  6. Calibration of a Soil Respiration Model
  7. Conclusions
  8. Acknowledgements
  9. References
  • • Variation in root respiration and total soil respiration measured in the field in an alder (Alnus glutinosa) forest is reported here, complementing previous studies of below-ground carbon relations.

  • • A novel technique, involving minimum disturbance to the roots, was used to measure tree fine-root respiration, while soil respiration was measured in an open system using infrared gas analysis. Calculations by process models of both rhizomicrobial, and bulk soil, respiration were compared with measurements of total soil respiration.

  • • The rhizomicrobial respiration rate was strongly temperature dependent, with the variation determined by fine root structural parameters. The data were used to calibrate a soil respiration model comprising mineralization and rhizomicrobial respiration submodels. The calculated annual rhizomicrobial respiration (1234 g m−2) matched the carbon balance of the alder trees calculated in earlier studies; however, the calculated total annual soil CO2 efflux (1754 g m−2) was very high compared with other European forest sites.

  • • The modelled total soil respiration fitted well to measured values; a changing groundwater table and modified carbon partitioning of the alder trees might account for deviations during early summer.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results and Discussion
  6. Calibration of a Soil Respiration Model
  7. Conclusions
  8. Acknowledgements
  9. References

The carbon balance of terrestrial ecosystems plays a major role in the regulation of the surface temperature of our planet, since carbon dioxide (CO2) strongly influences the global radiation budget (Schimel, 1995). Whereas the regulation of net primary production is well known for most of the earth's ecosystems, our knowledge about belowground respiratory processes is poor (Raich & Potter, 1995). Soil carbon fluxes and the resulting carbon stocks depend on several closely interrelated processes. Carbon inputs via litterfall and fine root turnover in natural ecosystems are mainly controlled by plant primary production. Mineralization of fresh and refractory organic matter depends on temperature and water conditions and also on the amount and the quality of organic matter. Decomposition is controlled by the ecophysiological features of the microbiota, which reflect the adjustment to the physical and chemical properties of the environment. All these processes lead to the release of CO2 through the soil surface, which is defined as total soil respiration.

In this study we focus on the measurement of rhizomicrobial respiration in the field. This process comprises the respiration of the roots as well as the mycorrhizal fungi and the microorganisms living on the roots and in the rhizosphere. Respiration processes are influenced by temperature and moisture. Because it utilizes plant assimilates as substrate, rhizomicrobial respiration greatly depends on primary production and carbon partitioning in the plants. In addition, root respiration of deciduous trees is affected by the nitrogen content of the root phytomass (Burton et al., 1998). However, the influences of species and seasonal dynamics of rhizomicrobial respiration have been overlooked in most studies. One reason for this is that field measurements of rhizomicrobial respiration are hampered by disturbance of the rhizomicrobial system (Vogt et al., 1989). This is especially true for nutrient-restricted forest systems that strongly depend on a recycling of nutrients out of rapidly decaying organic material and therefore develop dense root mats in the Of-horizon. In this environment, the removal of roots from the organic soil is not possible without either injuring the roots and cutting the hyphae of the mycorrhiza or including so much organic matter in the chamber that the rhizomicrobial respiration comprises only a small part of total respiration.

To solve this dilemma a novel method was applied that minimized disturbance of the roots and respiration of the bulk soil microbiota by inserting root tips into small, sand-filled containers and measuring respiration after several weeks when fine roots had developed. The measurements were carried out over several months in an alder forest on a Histosol in northern Germany. Alder (Alnus glutinosa (L.) Gaertn.) is a light-demanding species with a wide physiological amplitude. It is usually restricted to wet peat soils by competition (Eschenbach, 1995; Ellenberg, 1996). The occasionally low nutrient availability of such habitats requires particular efforts of the trees for nutrient uptake, for example by investing carbohydrates in the rhizosphere (Bar-Yosef, 1991), in the mycorrhizas (Smith & Read, 1997) and in the symbiosis with N-fixing Frankia bacteria (Dawson & Gordon, 1979). Previous studies for this alder forest (summarized by Dilly et al., 2000) have shown that the intensity of N-fixation (Dittert, 1992), mycorrhizal parameters (Pritsch, 1996), microbial activity and root growth (Middelhoff, 2000) are especially high in a 10-m wide edge zone at a lake shore. Within this edge zone the alder trees have high assimilation rates due to their greater crown surface area. High C allocation to the root system may be a consequence of high C gain (Eschenbach et al., 1997; Kutsch et al., 2001) and restricted phosphorus availability (Middelhoff, 2000).

This study was designed to complement these findings by analysing belowground C relations of the alder forest. This was done in two steps: during the vegetation period of 1992 the total soil respiration was measured using an open dynamic system; in 1995, direct measurements of rhizomicrobial respiration were made in the field, in order to determine the major factors influencing the rhizomicrobial respiration in the field. In addition, calculations by process models of the rhizomicrobial respiration and of the bulk soil respiration were compared with the measurements of total soil respiration.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results and Discussion
  6. Calibration of a Soil Respiration Model
  7. Conclusions
  8. Acknowledgements
  9. References

The research site of the Kiel Ecosystem Research Center (Hörmann et al., 1992) is located in the Bornhöved Lake District, 30 km south of Kiel (54°06′ N, 10°14′ E). The alder forest, growing on the west shore of Lake Belau is an Alnetum glutinosae. In 1992 the trees of the edge zone under investigation had an average tree age of 45 y. The forest is typical of the North German landscape, representing conditions highly influenced by near-surface groundwater dynamics. The soil properties are summarized in Table 1.

Table 1.  Some properties of alder forest soil under consideration
HorizonDepth (cm)pH (CaCl2) Corg (mg g−1) Norg (mg g−1)C/N
Litter 1–04.3541.724.422
Of 0–2.55.2507.522.423
H2.5–195.4451.325.718

Field measurements of total soil respiration and rhizomicrobial respiration

Soil CO2 efflux can be measured by several techniques, reviewed and compared by Janssens et al. (2000). In the present study an open dynamic system was used. The system (Fig. 1) comprised eight parallel channels, each with its own measuring and reference gas units consisting of a pump (WISA, Wuppertal, Germany), a mechanical flow controller (Krohne, Düsseldorf, Germany), and a magnetic valve (Herion, Fellbach, Germany). This technical device allowed both overpressure and underpressure to be applied to the chambers. Behind the magnetic valve the air stream was passed through an electronic flowmeter (Tylan General, USA) and a gas cooling unit (Walz, Effeltrich, Germany) to an infrared gas analyzer (Fisher-Rosemount, Hanau, Germany).

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Figure 1. System developed for field measurements of total soil respiration and rhizomicrobial respiration. Abbreviations: P, pump; mFC, mechanical flow controller; mV, magnetic valve; eFM, electronic mass flowmeter; C, gas cooler (for drying the air); IRGA, infrared gas analyzer.

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Ambient air was continuously sucked through the chamber with a flow rate of 1 l min−1. The diameter of the inlet was 3 cm, which was large enough to avoid an underpressure higher than 1 µbar in the system (pressure sensor type 223, MKS Baratron, München, Germany, for details see: Kutsch, 1996). The channels were measured subsequently at 3 min intervals. In parallel, ambient air was passed through a reference tube to the gas analyzer measuring in the differential mode. The chambers having about 2.8 l volume covered an area of 16 × 12.5 cm. To measure CO2 flux they were attached to aluminum frames which were fixed in the soil. Each measurement period lasted no longer than 3 d to minimize chamber-induced changes in soil moisture. After this period the chamber was attached to another frame. The frames remained at the same place during the whole growing season of 1992.

We preferred an open dynamic system in this study because it enabled continuous measurements as close as possible to the natural conditions. In open systems: CO2-concentration in the chamber is close to ambient; pressure difference between inside and outside the chamber can be minimized; and pressure fluctuations induced by the vertical wind component are transmitted to the soil surface. The latter induce an increase of the mass flow of soil air through the soil surface and can increase the efflux of CO2 during periods of high wind speed (Janssens et al., 2000; Rayment & Jarvis, 2000). However, the evaluation of the data showed that our system not only transmitted but also modified the natural pressure fluctuations caused by an inappropriate design of the chamber inlet (Kutsch, 1996). Placing the inlet at one side of the chamber caused an overpressure inside the chamber when the wind blew directly onto the inlet and an underpressure inside the chamber in all other directions. Fig. 2 shows this dependency of chamber internal pressure on wind speed and wind direction measured in the laboratory using a fan. Two consequences were drawn for the data evaluation: data measured when wind was directed to the inlet were rejected; and measurements made during periods with wind speed > 3.5 m s−1 causing an underpressure lower than −20 µbar were interpreted as ‘influenced more by a chamber effect than by natural pressure fluctuations’ and were also eliminated. In late 1992 these problems were avoided by covering the inlets of the chambers by a dome-shaped, gauze-covered shelter (Fig. 3). In addition, a second chamber was inserted in the reference gas stream. This closed chamber adjusted the volume of the reference gas stream to that of the measuring gas stream in order to prevent fluctuations in the flux signal after rapid changes in the CO2-concentration of the ambient air (Kutsch, 1996). The new chamber design showed no dependency of the pressure fluctuations inside the chamber on wind direction during laboratory tests.

image

Figure 2. Pressure difference between chamber and ambient air in relation to wind speed and wind direction. When wind comes from the direction of the inlet it caused an overpressure up to more than 100 µbar inside the chamber at 5-m s −1 . Other directions caused underpressure down to −30 µbar at 5 m s −1 . Measurements were taken in the laboratory using a fan.

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image

Figure 3. Modified chamber design used after autumn 1992. The inlet of the chamber is sheltered by a gauze-covered dome. The additional chamber adjusts the volume of the reference gas stream to that of the measuring gas stream to prevent fluctuations in the flux signal after rapid changes in the ambient air CO 2 -concentration.

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Each chamber was equipped with a Pt 100 temperature sensor. Every 10 s temperature, flow rate, CO2 difference and absolute concentration were recorded for each chamber and registered as a mean value over a 3 min sampling period.

Most of the direct measurements of rhizomicrobial respiration reported in the literature were performed with potted plants in the laboratory (Lambers et al., 1991). Field measurements are difficult because roots can not be extracted from the soil without any disturbance. To minimize root disturbance, Gansert (1994, 1995) developed the subtraction method. He inserted roots together with the surrounding soil into a measuring chamber. After the measurement the root was removed and the respiration of the remaining soil was measured. The rhizomicrobial respiration was calculated as the difference between the total respiration and the respiration of the remaining soil. The weak point of Gansert's approach was that the respiration rates of the root and soil samples were measured directly after they were taken from the soil and put into the chamber which means a disturbance to the rhizomicrobial system.

The improvement of the method in this study was that tips of fresh fine roots (referring to the German terminology ‘Langwurzel’ or long-root, Büsgen, 1901) were inserted into small plastic containers (18 × 13 × 6 cm) filled with sand in April 1995 where they developed a fine root system during the next month. From July to October each container received a weekly addition of 100 ml nutrient solution (5.0 mMol Ca2+ l−1 as CaCl2, 2.5 mMol Mg2+ l−1 as MgSO4, 12.5 mMol K+ l−1 as K2SO4, and KH2PO4, 2.5 mMol P l−1 as KH2PO4, 2.5 mMol N l−1 as NH4NO3). When grown in sand containers, fine roots had a different pattern of mycorrhizal colonization compared to the Of-horizon; only few poorly structured morphotypes were observed but these were very abundant (K. Pritsch pers. comm.). Previous experiments with a comparable design showed that fine roots of alder grown in sand have lower values of specific root length (0.8–1.5 m g−1 compared to a 3-yr mean of 8.0 m g−1 in the Of-horizon) and were more branched. The ratio of the length of fine lateral roots to that of the main roots on which they were borne (see definitions below) was more than doubled in sand containers compared to long-term means of the Of-horizon (Jacobsen, 1993; Middelhoff, 2000).

For the respiration measurements the containers were inserted into measuring chambers placed on the soil surface. To avoid an increase of the apparent respiration rate due to a CO2 concentration lower than that of the soil air (Palta & Nobel, 1989; Qi et al., 1994; Burton et al., 1997), the CO2-content of the measuring air stream, which was pressed continuously through the chambers, was held constant at 1500 ppm by means of a gas mixing unit (Walz, Effeltrich, Germany). To avoid drying effects in the chamber the air was passed through a bottle with distilled water. During the measurement the temperature inside the chambers was monitored with a Pt 100 at the surface of the root containers. The air in each channel was measured subsequently at 5 min intervals in the differential mode against air from the gas mixing unit. CO2 difference, absolute CO2 content of the air, temperature in and flow through the chambers were measured every 10 s and recorded as a mean value over the sampling period. After each measurement the root system was removed for further analyzes (see below) and the substrate was measured separately. Fig. 4 shows typical data sets for two containers measured from 10 to 14 October 1995. During the first 48 h of the experiment the containers included roots and sand. At noon on 12 October the roots were removed. Thereafter, the CO2 efflux of the containers was very small. Since the scatter of this basal respiration rate was very high it was not possible to fit temperature and moisture response curves for each single container. Thus the data of all measurements were pooled to fit a common correction term of the basal respiration, which was subtracted from the total container respiration to calculate the respiration of the rhizomicrobial system. At noon on 11 October a disturbance in the gas mixing unit caused a high scatter of the respiration values. These measurements were removed from the data-set. Finally, 811 data sets measured at 14 root containers were used for the data evaluation. Parallel measurements of roots recently extracted from the soil resulted in an up to six-fold higher respiration rate. This shows that the original approach of Gansert (1995) can not be applied to this organic soil.

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Figure 4. Diurnal courses of the CO 2 -efflux from two of the root containers in October 1995. During the first part the containers contained an intact rhizomicrobial system, which was removed after 2 d of measurement. After that the sandy substrate was measured alone for 1.5 d. The arrows mark a period with a disturbance inside of the gas mixing unit, which caused fluctuations in the signal. Closed circles, root container 1; open circles, root container 2.

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Root parameters

Definitions  We distinguish two morphological and functional types of fine roots (< 2 mm). The woody, more elongated root type that evolves after secondary growth out of long roots is called ‘main-roots’ (also ‘mother roots’, Wilcox, 1964 ). They carry short-lived branches that are almost entirely mycorrhizal ( Pritsch, 1996 ) and in alder have only two orders of branching. The biomass relation [g g −1 ] between these lateral-roots and the main-roots is introduced as a measure of the branching intensity (BI).

When the soil respiration measurements in the alder forest were finished the soil within the frames was excavated to a depth of 20 cm and the mass of all roots with a diameter less than 5 mm and of the nodules was determined. After the direct measurements of the rhizomicrobial respiration the root system was removed from the container and main-roots and lateral-roots that had developed during the incubation were separated. Length and diameter of the main-roots was measured with a vernier gauge, the total length of the lateral-roots according to the ‘line intersection method’ (Tennant, 1975), which has an uncertainty of 5% (Tennant, 1975, own tests). D. wt of the main-roots and the lateral-roots were measured separately after drying at 65°C. Respiration rates were related to d. wt, total length, surface and volume of the roots gaining the best correlation against total root length (r2 = 0.45 for 110 measurements between 14° and 16°C).

Results and Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results and Discussion
  6. Calibration of a Soil Respiration Model
  7. Conclusions
  8. Acknowledgements
  9. References

Fig. 5 shows the diurnal courses of the rhizomicrobial respiration in the two chambers measured between 10 and 12 October 1995, as shown in Fig. 4 . The bulk soil respiration has already been subtracted and the respiration rate is related to the biomass of the roots. In addition, the data measured during the short disturbance in the gas mixing unit were removed. The rhizomicrobial respiration rates of the two samples closely parallel temperature variations throughout the day. However, the two samples differed considerably in the respiration rate. Sample 1 varied between 7 and 15 µmol CO 2 g −1 dry mass s −1 , and sample 2 between 17 and 29 µmol CO 2 g −1 dry mass s −1 although the temperature for sample 2 was lower. The difference in the respiration rates corresponded to the biomass ratio between main-roots and lateral-roots. Sample 1 with a BI of 3.2 had a lower proportion of side-roots than sample 2 with a BI of 11.3.

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Figure 5. Diurnal courses of rhizomicrobial respiration for two samples measured in an alder forest of the Bornhöved lake district. Large closed circles, respiration of root in container 1; large open circles, respiration of root in container 2; small closed circles, temperature in container 1; small open circles, temperature in container 2.

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The dependence of the rhizomicrobial respiration rate on temperature and BI was observed for most of the measurements. Thus, we were able to differentiate between two data sets of different BIs: five roots with a BI > 10; eight roots with a BI > 7. Fig. 6 shows data from 811 measurements carried out between August and November 1995. The data correlated closely with two exponential temperature response curves. The Q10-values were 1.95 and 2.17, respectively. Considerable respiration rates were even detected at temperatures below zero.

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Figure 6. Temperature response curves of rhizomicrobial respiration for two classes of alder roots. Circles, roots with a fine-root : long −1 -root ratio (branching intensity (BI)) > 10; squares, roots with a fine-root (BI): long −1 -root ratio < 7.

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At 15°C the rhizomicrobial respiration rate was around 20 nmol CO2 g−1 d. wt s−1 for the roots with the BI > 10 and 10 nmoles CO2 g−1 d. wt s−1 for the roots with lower BI. The latter value is comparable with the rate of Fagus sylvatica fine-roots measured by Gansert (1995) but more than twice as high as the rates reported by Rakonczay et al. (1997) for Acer rubrum, Quercus rubra and Pinus strobus roots. However, the roots of the latter species were isolated from soil and rinsed before exposure in the chamber with the effect that the rhizosphere was removed. This may have caused a loss of up to 20% of total soil respiration (Kelting et al., 1998). In our experimental design we took care that the rhizosphere was intact.

Fig. 7(a ) shows diurnal courses of soil respiration in the alder forest in August 1992 measured by means of four CO 2 exchange chambers running in parallel. The soil temperature at a depth of 10 cm exhibited little diurnal variation. The short-term variations of the soil CO 2 efflux seem to be mainly induced by air turbulence. Fig. 7(b ) shows the correlations between wind speed and soil respiration for this data set. They indicate increases in soil CO 2 -efflux between 5 and 22% when wind speed increased from 0 to 1 m s −1 . Similar observations were also reported by Rayment & Jarvis (2000 ) from measurements in a boreal forest. They calculated a decrease of 8.8% in the apparent flux rate when pressure fluctuations were excluded. The two observations support the hypothesis that the transport of CO 2 from the soil to the atmosphere is driven by diffusion and advection due to pressure fluctuations ( Kimball & Lemon, 1971 ). However, the question of how much of the measured increase is induced by natural pressure fluctuations and how much by a chamber influence has to remain unsolved until further technical checking of the method.

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Figure 7. (a) Diurnal courses of soil respiration measured parallely at four frames in the alder forest. Wind speed was measured at 16 m over a nearby crop field. Squares, chamber 1; diamonds, chamber 2; triangles, chamber 3; circles, chamber 4; line with small circles, windspeed; line, temperature. (b) Correlations between the measured soil respiration and the wind speed measured at 16 m over a nearby crop field. Squares and thick line, chamber 1; diamonds and thin line, chamber 2; triangles and dotted line, chamber 3; circles and dashed line, chamber 4; Ch1, y = 1.2555x + 7.6627; R2 = 0.6015: Ch2, y = 1.7672x + 12.277; R2 = 0.6015: Ch3, y = 1.8499x + 8.3226; R2 = 0.6173: Ch4, y = 0.4901x + 9.6817; R2 = 0.4395.

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Throughout the whole growing season total soil respiration had the highest correlation with soil temperature (correlation coefficients between 0.32 and 0.62 for the four subplots, 315 hourly means each) as described also, for example by Janssens et al. (2000) or Rayment & Jarvis (2000) for forest ecosystems and Kutsch & Kappen (1997) for agricultural soils. It is noteworthy that the Q10-values of these correlations varied between 5.6 and 10.1 which are extraordinarily high numbers.

Calibration of a Soil Respiration Model

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results and Discussion
  6. Calibration of a Soil Respiration Model
  7. Conclusions
  8. Acknowledgements
  9. References

Model calibration

A mathematical model of total soil respiration consisting of two subunits was developed and calibrated. This model summarized respiration processes on a surface area basis working in daily steps. In the first submodel mineralization is formulated as a first order reaction with rate constants modified by soil water content (Θ) and soil temperature (T):

  • An  =  kn · Cn · f (Θ)· f ( T )

(An, mineralization rate of the respective pool or horizon n; Cn, carbon content; and kn, specific rate constant. F(Θ) and f(T) describe the dynamic adjustment of the Q10-value to the temperature and to drought and re-wetting as was described by Kutsch & Kappen (1997). Observations by Dilly et al. (1997) suggested a correlation between the basal respiration rates measured in the laboratory and field-measured mineralization rates. Thus, the specific rate constants kn were calibrated by the results of basal respiration measurements (Dilly & Munch, 1996; Kutsch et al., 2000) on three different C pools (fresh litter, gradually degraded litter in the Of-horizon, H-horizon). For the year 1992 a total mineralization of 520 g C m−2 yr−1 was calculated.

In the rhizomicrobial submodel root biomass was separated into three classes according to their specific activity. Root biomass of the main-roots (40 g dry mass m−2) and the coarse roots (> 2 mm diameter, 500 g dry mass m−2) were assumed to be constant throughout the year, whereas the lateral-root biomass varied between 25 g dry mass m−2 during winter and 450 g dry mass m−2 during summer reflecting the range of BI's observed in this study. Similar annual courses of lateral-root biomass were reported for beech forests (Hertel, 1999), a pine forest (Steele et al., 1997) and for grasslands (Fitter et al., 1998).

The temperature response of the rhizomicrobial respiration was modelled with a constant Q10-value of 2, as calculated from our direct measurements. The specific respiration rate of the lateral-roots was calibrated by means of the results from our direct measurements for the roots with a BI > 10, the specific activity of the main-roots with the results measured from roots with a BI < 3. Rates for the woody root parts were taken from Gansert (1995). Based on these assumptions a rhizomicrobial respiration of 1234 g C m−2 was calculated for the year 1992. This concurred with the C balance of the trees calculated in earlier studies for this part of the alder forest. Eschenbach et al. (1997) and Kutsch et al. (2001) calculated that about 1600 g C m−2 of assimilates were partitioned below-ground by the alder trees and about 300 g C m−2 of them were used for root growth. Thus, 1300 g C m−2 was calculated for rhizomicrobial respiration.

Model validation

The sum of modelled mineralization and rhizomicrobial respiration rates was related to the total soil respiration measured in the field. The comparison between the measured and modelled values over the course of the year 1992 (Fig. 5) was consistent at most times, except in June when the measured soil respiration exceeded the modelled values by up to 100%. On a daily means basis the regression coefficient between measured and modelled soil respiration rates was r2 = 0.21 (n = 48), but it increased to r2 = 0.51 when the values of June were excluded (n = 40). Also the slope of the regression line increased from y = 0.90 to y = 0.99. In June 1992 the groundwater table sank by about 30 cm due to a warm and dry weather period of c. 6 wk (Fig. 8) (Fig. 9). It is assumed that consequently, a higher amount of organic C was available for the decomposition by the microbiota.

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Figure 8. Annual course of the measured and the modelled total soil respiration rate. Line, modelled: closed circles, measured mean value; open squares, measured chamber 1; open diamonds, measured chamber 2; open triangles, measured chamber 3; open circles, measured chamber 4.

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Figure 9. Modelled course of the groundwater table in the wet alder forest during a drought period in summer 1992 (unpublished data from W. Kluge). The symbols represent different plots within the forest. Closed circles, plot A; open circles, plot B; triangles, plot C; line, Lake Belau.

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The high soil respiration rates also indicate changes in the C partitioning of the alder trees towards below-ground plant parts. As data from an ingrowth-core experiment show, exceptional root growth occurred in deeper soil layers during this period, while normally 90% of the fine root biomass is located in the Of-horizon, which is 4 cm deep (Middelhoff, 2000). In parallel a significant temporal flush of fine root production was measured in the Of-horizon.

Jacobsen (1993 ) and Middelhoff (2000 ) also showed that flushes of fine-root growth are accompanied by high growth rates of lateral-roots resulting in a high branching intensity. The data presented in this paper clearly demonstrated the effect of fine-root structural parameters on respiration rates. Additionally, changes in the C partitioning of the alder trees towards below ground may generally promote the activity of the rhizomicrobial system, as was already suggested by Pizelle (1984 ). The formation of new roots is often associated with high fluxes of assimilates to the mycorrhiza ( Cairney & Alexander, 1992 ).

Conclusions

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results and Discussion
  6. Calibration of a Soil Respiration Model
  7. Conclusions
  8. Acknowledgements
  9. References

Our method of measuring rhizomicrobial respiration after several weeks of root development in sand-filled containers seems to be a promising tool as it minimizes disturbance of roots and rhizosphere. Although the physico-chemical conditions in our artificial substrate have changed fine-root structure and ectomycorrhiza, the results show a clear dependence of fine-root respiration on structural parameters that indicate an enhanced root activity (e.g. branching intensity). We hypothesize that the branching intensity can be perceived as an indicator of the activity of the whole rhizomicrobial system, including rhizosphere microbiota, mycorrhizas and root-nodules. In our case, this system is supported by high amounts of assimilates because the site we studied is a forest edge characterized by high photosynthetic C gain (Dilly et al., 2000).

This hypothesis may also explain the extraordinarily high Q10-values calculated from the correlation between the measured total soil respiration and soil temperature. Assuming that the pure temperature response of biological systems leads to Q10-values between 1.5 and 3, a second constraint with a similar annual course as soil temperature has to be responsible for an ‘amplification’ of the soil respiration curve. In the model this is achieved by the variation of the branching intensity. The model fits generally to the measured fluxes, when an increase of the side-roots in spring and a decrease in autumn is assumed. It does not explain all observed fluctuations of the measured soil respiration, especially the high fluxes in June 1992. However, field measurements as well as modeling indicate that photosynthesis and C partitioning within the plant and the assimilate fluxes to the roots and further to the rhizosphere and the mycorrhizal fungi during such active periods, are the driving forces of the respiration patterns of the rhizomicrobial system.

Due to the edge effect the total annual soil respiration of 1754 g C m−2 that was calculated for the alder forest in 1992 was higher than most of the values reported in literature, for example Janssens et al. (2001) reported rates between 400 and 1200 mg C m−2 for 14 different European forest soils. Microbiological characterization of the soil and the litter in our alder forest (Dilly & Munch, 1996; Dilly et al., 1999; Kutsch et al., 2001) indicate that soil respiration was influenced by the great amount and high N content of the litter which stimulated the activity of the bulk soil microorganisms. This and the extraordinarily high rhizomicrobial activity are mainly responsible for the higher value than that of the other forests. The C balance shown here indicates that the alder trees under consideration shift more than two thirds of the assimilates to the root system.

Our findings confirm the opinion of Janssens et al. (2001) that temperature can not explain the differences in soil respiration rates between different European forest sites. However, in addition to productivity and disturbance mentioned by these authors as ‘overshading’ factors we propose that species composition and nutrient availability of the site also strongly influence total soil respiration because fine root turnover and rhizomicrobial respiration vary between tree species and are differently stimulated by various chemical site conditions.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results and Discussion
  6. Calibration of a Soil Respiration Model
  7. Conclusions
  8. Acknowledgements
  9. References

The authors thank Helge Petrikowski, Lutz Becker and Dr Wolfgang Schaefer for technical support, Dr Oliver Dilly for a lot of helpful discussions, Paulette Clowes as a native speaker for improving the English language and two anonymous referees and the subject editor of the New Phytologist for a lot of helpful comments. This study was part of the interdisciplinary project ‘Ecosystem research in the Bornhöved lake district’ funded by the German Federal Ministry of Education, Research, and Technology (BMBF), project number 0339077E, and the State Schleswig-Holstein.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results and Discussion
  6. Calibration of a Soil Respiration Model
  7. Conclusions
  8. Acknowledgements
  9. References
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