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: vladimir.stolbovoy@jrc.it

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