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Stolbovoy Vladimir, Luca Montanarella, Nicola Filippi, Senthil-Kumar Selvaradjou and Javier Gallego
European Commission, Joint Research Centre, Institute for Environment and SustainabilityLand Management & Natural Hazards Unit, Ispra (VA), Italy
Soil Sampling to Certify the Changes of Organic Carbon in Mineral Soils
Table 1. Number of sampling sites depending on the field size.
0
5 0
1 0 0
1 5 0
2 0 0
2 5 0
3 0 0
3 5 0
5 4 3
tC
A v e r a g e A v e D e v
0
1 0 0
2 0 0
3 0 0
4 0 0
5 0 0
6 0 0
7 0 0
5 4 3
tC
0
5 0
1 0 0
1 5 0
2 0 0
2 5 0
3 0 0
3 5 0
5 4 3
N u m b e r o f s a m p l i n g s i t e s
tC
0
5 0
1 0 0
1 5 0
2 0 0
2 5 0
3 0 0
3 5 0
5 4 3
tC
A v e r a g e A v e D e v
0
1 0 0
2 0 0
3 0 0
4 0 0
5 0 0
6 0 0
7 0 0
5 4 3
tC
0
5 0
1 0 0
1 5 0
2 0 0
2 5 0
3 0 0
3 5 0
5 4 3
N u m b e r o f s a m p l i n g s i t e s
tC
a) Cropland
b) Pasture
c) Forest
Calculations
cm
0
10
20
30
40
50
60
70
80
Sub
soil
hor
izon
c. Forest
Sam
plin
g de
pths
Sub
soil
hor
izon
b. Pasture
Plo
ugh
hori
zon
Sub
soil
hor
izon
a. Cropland
Min
eral
ho
rizo
nO
rgan
ic
laye
r
Cylinders to test bulk density
cm
0
10
20
30
40
50
60
70
80
cm
0
10
20
30
40
50
60
70
80
0
10
20
30
40
50
60
70
80
Sub
soil
hor
izon
c. Forest
Sam
plin
g de
pths
Sub
soil
hor
izon
b. Pasture
Plo
ugh
hori
zon
Sub
soil
hor
izon
a. Cropland
Min
eral
ho
rizo
nO
rgan
ic
laye
rM
iner
al
hori
zon
Org
anic
la
yer
Cylinders to test bulk density
Figure 2. Sampling depths are different for: a. Cropland (homogeneous ploughed horizon), b. Pasture (gradual change of the SOC content) and c. Forest (litter and mineral soil). This substantialization avoids over sampling and links the AFRSS with the monitoring of the forest soils in Europe.
Source: Stolbovoy et al., 2006
Results & Conclusions
The test of the RP of the AFRSS method in the cropland (region Piemonte, Italy) shows that changes greater than 3 % of initial C stock can be verified. For example, for the cropland (Skeletic Cambisol) with the SOC stock 70-80 tC/ha only measures having potential to accumulate more than 2.1-2.4 tC/ha can be applied.
Acknowledgements The authors thank Mauro Piazzi and Fabio Petrella from the Soil Department of the Institute for Forestry and Environment (IPLA, Region Piemonte, Italy) for their collaboration.
ReferencesIntergovernmental Panel on Climate Change (IPCC), 2003. Penman J., M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, R. Pipatti, L. Buendia, K. Miwa, T. Ngara, K. Tanabe and F. Wagner (Eds). Good Practice Guidance for Land Use, Land Use Change and Forestry. IPCC/OECD/IEA/IGES, Hayama, Japan.
Stolbovoy, V., L. Montanarella, N. Filippi, S. Selvaradjou, P. Panagos and J. Gallego, 2005. Soil Sampling Protocol to Certify the Changes of Organic Carbon Stock in Mineral Soils of European Union. EUR 21576 EN, 12 pp. Office for Official Publications of the European Communities, Luxembourg.
Figure 1. The randomized template (a) unifies identification of the sampling sites. The fitting with the field defines dimension of the template (b) and makes computation of the position of the profiles and sampling points easy (c).
Reproducibility (RP) is a difference in the averages resulting from two parallel samplings, which is an error of the average coming from the spatial shift of the sites positioning in the course of the repeated parallel sampling. The RP shows the minimum detectable difference in C stock.
Average deviation (AveDev) declines with the higher average (Average) SOC content. This illustrates that the uncertainty of the verification is less where the soil approaches the SOC saturation.
79 40
100
44 93 16 67 54
64 32 47 95 24 58
51
53
56 1 72 43 97
8
91 1825
68 94 22 85 17
70
34
31 73
42
84 50
61
33
87
27
48
10
28
66
88
4 69 75 12 90 76 23 41 99 2
60 29 7 92 19 45 57
20 80 78 21 83
98
719
38
7459 14
30 39 35 49 82 3
9646
89 6 66 77 13 81
65
1537
11
3626
63
52
55
5
62
Max
is
Maxis
Profile
Point for composite sample
Point = GS/5
GS Grid size
Pro
file
= G
S/2
GS
= M
axis
/10
a. Randomized template
c. Sampling site
b. Fitting of the field (red) with the template.
Size of the field, ha Number of sampling sites
<5 3
5-10 4
10-25 5
>25 50
10
20
30
40
50
60
1 2 3 4 5
0.00
5.00
10.00
15.00
20.00
25.00
30.00
35.00
Plot area, ha Euro/tC
Eur
o
tC
Land cover
Conventional (IPCC, 2003) This study (AFRSS)
Variability%
Number of
samples
Cost per tC
Variability%
Number of
samples
Cost per tC
Cropland 9 216 576 n.a. 3 8
Pasture 15 300 800 n.a. 9 24
The conventional sampling (IPCC, 2003) requests detecting the changes in carbon stock with the 95% confidential level. At an observed variability of carbon content in the test fields the laboratory analysis results in 576 (cropland) and 800 (pasture) Euro per one tC. The AFRSS ignores soil variability, which reduces the laboratory costs to the practical level (e.g. 8 and 24 Euro per tC for cropland and pasture respectively).
Land Management and Natural Hazards Unit
Technical ContactVladimir Stolbovoy
European CommissionJoint Research Centre, 21020 Ispra (VA), ItalyTel. +39 0332 786330 • Fax +39 0332 786394
E-mail: [email protected]
Congress ContactLuca MontanarellaEuropean Commission DG Joint Research Centre
Exhibition Booth No. 313
Many soil functions are driven by the soil organic carbon (SOC) content, (e.g. fertility, buffering capacity, adsorption and absorption of chemicals, filtering to maintain water quality, regulation of atmospheric gas composition, etc.). The SOC is a universal soil quality indicator, which is also critical to monitor the major global environmental conventions on climate change (UNFCC), biodiversity (CBD) and desertification (UNCCD). The detection of the SOC changes is very complicated and is mostly applicable to scientific research at present.
Introduction
Objective
This study is to develop a simple, transparent, measurable and cost effective method to detect the changes in the SOC in soils.
The sampling depths (Figure 2) tend to minimize amount of samples and make sampling consistent with the European monitoring of the forest soils.
A new Area-Frame Randomized Soil Sampling (AFRSS) combines traditional composite soil sampling with random position of the sampling sites based on randomized template (Figure 1).
Methods
1. Represent the plot/field margins in coordinates of the standard local projection used for topographic or cadastral maps (Figure 1b).
2. Define Maxis value to setup a square accordingly.3. Overlay on the square the template with 100 points
numbered from 1 to 100, as represented in Figure 1a.4. Determine the number ‘n’ of sampling sites that is
conditioned by the plot area (Table 1) and the need to keep the costs to a minimum.
5. Select the first ‘n’ points of the grid if they fall inside the plot. Otherwise select subsequent sampling point (n + 1, n + 2, etc.) until you have ‘n’ points inside the plot (Figure 1b).
The implementation of the AFRSS needs to:
Laboratory costs of the analysis per unit of carbon (tC) is less for the fields with the bigger size. For example, for the average carbon sink about 1.5 tC/ha and prize of the analysis 16 euro per sample the analysis cost is as much as 33 Euro in one tC. This cost will be less than 1 Euro if the field size is 50 ha.
ΔSOCstock ± s(ΔSOCstock )
The changes are given in
The changes in C stock (ΔSOCstock) is a difference between average reference and new measurement
ΔSOCstock = SOCrefstock - SOCnew
RP(%) = (SOCnew / SOCrefstock )*100