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80 correlation coefficient 1.0 0.8 0.6 0.4 0.2 0.0 0 20 40 60 80 100 120 140 160 180 -0.2 -0.4 -0.6 time since measurements (in hours) Fig.8 Pearson correlation coefficients of temperature normalized root-derived respiration against gross primary productivity (GPP) from 0 to 7 days prior to respiration measurements. Ra vs.GPP GPP in h Beta B t p-level 0 -2.48 -0.22 -1.72 0.16 2 4.24 0.39 2.28 0.08 4 -0.53 -0.05 -0.75 0.50 20 1.60 0.24 2.97 0.01 22 -3.33 -0.30 -2.44 0.07 28 0.36 0.04 0.65 0.55 24 1.17 0.09 1.17 0.31 Table 5. Multiple linear regression analysis. Coefficients of regression determination: Ra vs. GPP in hours after the measurements. Significant is marked in red. Correlation with GPP for root-derived respiration was stronger for non-normalized respiration data, confirming a tight relation between the photosynthetic C supply and autotrophic component of soil respiration. Correlation coefficient was especially high on the second and third day after measurement of Ra, giving the peaks on the 20 th , 28 th , 44 th and 52 d hours after the measurements were performed, decreasing slowly with time. Example of diurnal variability of GPP and Ts is shown on the figure 9. Clear, that day peaks of GPP and Ts appear in different time. For the GPP often could be distinguished two peaks with the midday depression in between. Multiple linear regression analyses indicated that the best predictor of changes in root- derived respiration with significant coefficient of regression determination resulted was GPP 20h after the measurements of soil respiration (Table 5).
GPP (mmol m -2 s -1 ) 25 20 15 10 5 0 0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 22.5 -5 5 4 3 2 1 0 -1 -2 -3 3 2 2 1 1 Fig.9 Diurnal patterns of Gross Primary Production (GPP) and Soil Temperature (Ts) for May, July and August at Amplero. Values represent daily month averages. May 0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 0 0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 22.5 -1 -1 -2 -2 -3 Time July August 14.0 13.8 13.6 13.4 13.2 13.0 12.8 12.6 12.4 12.2 12.0 19.0 18.8 18.6 18.4 18.2 18.0 17.8 17.6 17.4 17.2 20.2 20.0 19.8 19.6 19.4 19.2 19.0 18.8 Temperature ( o C) 81
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explain diurnal and seasonal change
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sull’intensità del flusso respir
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8 3.2.4. Data analyses and definiti
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1. INTRODUCTION AND OVERVIEW 11
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times as much carbon as the terrest
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Fig. 3 Different soil C pools with
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1.3. Soil respiration sources Soil
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conditions, like soil type, plants
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For grasslands, the nature, frequen
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(a) (b) (c) Fig.7 Amplero (AQ, Ital
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magnitude of root respiration and o
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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 56 and 57: 2.4. Discussion 2.4.1. Partitioning
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: Total Label Recovered (TLR, %) Ra R
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
Page 106 and 107: Fig. 11 Cumulative microbial respir
Page 108 and 109: 108 After the calculation of synthe
Page 110 and 111: Fig. 16: a) Relationship between sy
Page 112 and 113: an annual mowing the measurement wa
Page 114 and 115: mineral N available to plants and N
Page 116 and 117: Cambardella C.A., Elliott E.T., (19
Page 118 and 119: Rice C.W., Moorman T.B., Beare M, 1
Page 120 and 121: 120
Page 122 and 123: 5.1. Introduction 122 Nitrogen (N)
Page 124 and 125: specie, c) an additional aim was to
Page 126 and 127: 5.2.4. Sampling and analyses 126 Na
Page 128 and 129: 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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