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2.4. Discussion 2.4.1. Partitioning of soil respiration 56 In our study the relative contribution of Ra to total CO2 efflux over the 3 years amounted to 29%. During the growing seasons the relative contribution of Ra varied from 2 to 70%, however an increase in the relative input of root respiration to the total one was associated mainly with a considerable decrease in microbial respiration under the water stress conditions (Fig. 3). The observed average value of root contribution to soil respiration is less than 38-40% and 43-56% reported respectively by Craine et al. (1999) and Wang et al. (2007) for temperate grasslands, and 39-41% reported by Tang et al. (2005) for oak-savannah. The lower value could be attributed to the fact that Amplero is subjected to the annual mowing and grazing, which influence the photosynthetic C supply to roots and thus root respiration itself (see below). In fact, our estimate is consistent with the results obtained in semi-arid grazed grassland of China (15%-37% by Li et al., 2002). The methods used for partitioning also vary between various studies, each with its own shortcomings and limitations, which could also influence the final result, making the comparison between studies especially difficult. As all soil respiration partitioning methods, the calculated here fluxes are an approximation of real field fluxes. The mesh-exclusion technique we used to partition soil respiration is associated with various limitations and assumptions, which result in a possible overestimation of microbial- derived respiration and underestimation of root-derived one. Namely, the shortcomings of the method are: disturbance of the soil structure by sieving, lateral diffusion of CO2 (Jassal and Black, 2006) to the mesh bags from the surrounding soil and inability to separate root respiration from rhizomicrobial one. The advantage of the nylon mesh bag technique over other trenching and root- exclusion methods is that it permits to exclude and control the roots in-growth inside the plot and in the same time allows the exchange of water and other substances with an exterior soil. We tried to minimise the effect of the soil disturbance on microbial activity and respiration fluxes by installing an additional mesh of 1cm, and obtaining the value of root-derived respiration as a difference between two meshes with the equally disturbed soil. However, here we make an assumption that there is no difference in the in-growth patterns of roots between non disturbed soil and soil which was previously sieved. Microbial-derived respiration was calculated further from the difference between control (non disturbed soil) plots and root respiration. The rate of the influence of the lateral diffusion of CO2 from the surrounding soil is difficult to estimate. Moyano et al. (2008) reported a value of ca. 10%. It results in a systematic overestimation of the microbial- derived respiration. Here we make a second assumption: the influence of the lateral flow of CO2 is constant during the growing season, and doesn’ t modify the seasonal trend in contribution of soil respiration components to the total one.
2.4.2. Diurnal, seasonal and inter-annual variability Soil CO2 efflux varied significantly during the growing seasons with lower respiratory losses during the winter months (around 0.25 µmol m -2 s -1 ), accompanied by low ambient temperatures and low gross primary production and during summer drought period (around 1.5 µmol m -2 s -1 ) with high temperatures and low SWC. Low CO2 efflux was compensated by high respiration rates in early and late summer (up to 8 µmol m -2 s -1 ) with comparatively high GPP and favourable Ts and SWC. This variability yielded the cumulative respiration for the period January - September in three years of measurements in the range of 440-490 gC m -2 . Model application resulted in the increase of cumulative respiration for the same measurement period to the range of 722-875 gC m -2 , indicating that a simple summing of the respiration assuming linear changes in soil CO2 efflux between the measurement days, used in some studies as an estimate of the year efflux, result in a two fold underestimation of the cumulative fluxes. Care should be taken while comparing annual fluxes, calculated with different approaches. The modelled values are in agree with the one, reported by Bahn et al. (2008) for European grasslands and Raich and Schlesinger (1992) for temperate and tropical grasslands and savannas. Evidently, seasonal variability of soil respiration was much higher than the inter-annual one. Diurnal variation of soil respiration of root and microbial origin showed different patterns (Fig. 5). Throughout the experimental period soil respiration peaked in different times of the day. However, morning peaks were registrated only in the very end of the growing season and in the most cases respiration reached its maximum in the afternoon or late evening. Notably, root and microbial derived respiration peaked in various times of the day, indicating the possibility of different controlling factors or different response-time to the same one. All the respiration sources were out of phase with changes in soil temperature, demonstrating that it is a weak indicator of diurnal variation in soil respiration. SWC showed weak diurnal fluctuations (Fig 6), and was not influencing the soil CO2 efflux on diurnal basis. During most of the measurement days was observed some kind of a loop after plotting soil respiration versus changes in soil temperature, meaning that under the same soil temperature soil respiration was different, changing with the time of the day. All these suggest that another factor was driving diurnal variation of soil respiration of various origin in addition to soil temperature, which is more likely a photosynthesis. Soil respiration didn’ t show an instantaneous correlation with photosynthesis, however after shifting it 6 h backward, soil respiration of root origin was proportional to photosynthesis in months of June, August and July, with R2 around 0.70, though the correlation didn’ t result significant (data not shown). We have expected to observe a coupling of root-derived respiration with GPP with some time lag on a diurnal basis, however, due to technical limitations: the number of diurnal measurement was too low, ranging from 3 to 6 also with different time periods between the 57
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explain diurnal and seasonal change
Page 6 and 7: sull’intensità del flusso respir
Page 8 and 9: 8 3.2.4. Data analyses and definiti
Page 11 and 12: 1. INTRODUCTION AND OVERVIEW 11
Page 13 and 14: times as much carbon as the terrest
Page 15 and 16: Fig. 3 Different soil C pools with
Page 17 and 18: 1.3. Soil respiration sources Soil
Page 19 and 20: conditions, like soil type, plants
Page 21 and 22: For grasslands, the nature, frequen
Page 23 and 24: (a) (b) (c) Fig.7 Amplero (AQ, Ital
Page 25 and 26: magnitude of root respiration and o
Page 27 and 28: efficiency, indicating future posit
Page 29 and 30: approaches for studying of the cont
Page 31 and 32: Houghton R.A., 2003. Revised estima
Page 33: Vleeshouwers L.M., Verhagen A. 2002
Page 36 and 37: 2.1. Introduction 36 Soil respirati
Page 38 and 39: 38 In the year 2005 ten PVC collars
Page 40 and 41: 2.2.4. Biochemical analyses Microbi
Page 42 and 43: 42 Variation of soil respiration fr
Page 44 and 45: CO 2 efflux (mmol m -2 s -1 ) 44 CO
Page 46 and 47: 46 All diurnal measurements of root
Page 48 and 49: 48 Q10 R 2 p Rs 2.51 0.77 0.000 Ra
Page 50 and 51: the photosynthesis and its followin
Page 52 and 53: 2.3.3. Inter-annual variation of so
Page 54 and 55: 54 RS RHET 8 6 6 4 25 4 2 2 25 20 T
Page 58 and 59: measurements, the possibility to fi
Page 60 and 61: and Schlesinger, 1992; Moyano et al
Page 62 and 63: Janssens I.A., Pilegaard K., 2003.
Page 64: Xu X., Kuzyakov Y., Wanek W., Richt
Page 67 and 68: 3.1. Introduction Soil respiration
Page 69 and 70: Our experiment was conducted in a m
Page 71 and 72: Lactic acid 13 C 13 CO2 Root-derive
Page 73 and 74: At the end of the process, the subl
Page 75 and 76: where, MAs - the mean age of the co
Page 77 and 78: 13C of respiration ( o / oo ) 155 1
Page 79 and 80: Total Label Recovered (TLR, %) Ra R
Page 81 and 82: GPP (mmol m -2 s -1 ) 25 20 15 10 5
Page 83 and 84: frequent and possibly they missed t
Page 85 and 86: 3.4.3. Destructive vs. Non-destruct
Page 87 and 88: Gavrichkova O., Kuzyakov Y., 2008.
Page 90 and 91: Chapter source: 90 4. THE EFFCT OF
Page 92 and 93: Bardgett et al. (1997) showed that
Page 94 and 95: 94 Partitioning plots were installe
Page 96 and 97: Microbial C was calculated as a dif
Page 98 and 99: taken from 1 µg N-NO2 ml -1 soluti
Page 100 and 101: ates between clipped and unclipped
Page 102 and 103: Fig. 7 Total (Rs), root (Ra)- and m
Page 104 and 105: 104 Rh, (CO 2 , mmolm -2 s -1 ) 7 6
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Fig. 11 Cumulative microbial respir
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108 After the calculation of synthe
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Fig. 16: a) Relationship between sy
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an annual mowing the measurement wa
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mineral N available to plants and N
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Cambardella C.A., Elliott E.T., (19
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Rice C.W., Moorman T.B., Beare M, 1
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120
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5.1. Introduction 122 Nitrogen (N)
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specie, c) an additional aim was to
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5.2.4. Sampling and analyses 126 Na
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the differences between N and contr
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130 specific root respiration (max
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Fig. 4 a) Intensity of 14 CO2 efflu
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Fig. 6 a) values above zero: root-d
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136 Zea mays: A clear diurnal dynam
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plants. The growth stage could cont
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nitrates. At temperatures of 15 - 2
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experiment could be responsible for
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Horwath W.R., Pretziger K.S., Paul,
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146
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148 6.1 . Introduction In studies o
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Regression analyses technique, whic
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152 The respiratory response with g
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154 100% 80% 60% 40% 20% 0% 85% 13%
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6.3.2. 2008: Mesh- exclusion vs. re
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6.4. Discussion 6.4.1. Mesh-exclusi
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introduction in a small soil sample
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component, expressing a total soil
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Kucera C.L., Kirkham D.R., 1971. So
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Acknowledgements This work was poss
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