This presentation was presented during the 1 Parallel session on Theme 3.3, Managing SOC in: Dryland soils, of the Global Symposium on Soil Organic Carbon that took place in Rome 21-23 March 2017. The presentation was made by Mr. Sergio Saia, from CREA – Italy, in FAO Hq, Rome

1. GLOBAL SYMPOSIUM ON SOIL ORGANIC
CARBON, Rome, Italy, 21-23 March 2017
Protection of soil from the loss of organic carbon by taking into
account erosion and managing land use at varying soil type:
indication from a model semiarid area
Sergio Saia1*, Calogero Schillaci2,3, Aldo Lipani4, Maria Fantappiè5, Michael Märker3,6, Luigi
Lombardo7, Maria G. Matranga8, Vito Ferraro8, Fabio Guaitoli9, Marco Acutis2
1 [Italy Council for Agricultural Research and Economics (CREA), Cereal Research Center (CREA-CER), Foggia, Italy, sergio.saia@crea.gov.it, *corresponding author]
2 [Department of Agricultural and Environmental Science (DISAA), University of Milan Via Celoria 2, 20133 Milan, calogero.schillaci@unimi.it]
3 [Department of Geosciences, Tübingen University, Germany Rümelinstr 19-23 Tübingen, Germany]
4 [Institute of Software Technology and Interactive Systems, TU Wien, aldo.lipani@gmail.com]
5 [Council for Agricultural Research and Economics (CREA), Centre for Agrobiology and Pedology (CRA-ABP), Florence, Italy, maria.fantappie@crea.gov.it]
6 [Department of Earth and Environmental Sciences, University of Pavia, Italy. Michael.maerker@unipv.it]
7 [Physical Sciences and Engineering Division, King Abdullah University of Science and Technology, Tuwal, Jeddah. luigi.lombardo83@gmail.com]
8 [Regional Bureau for Agriculture, Rural Development and Mediterranean Fishery, the Department of Agriculture, Service 7 UOS7.03 Geographical Information
Systems, Cartography and Broadband Connection in Agriculture, Palermo, mariagabriella.matranga@regione.sicilia.it, vito.ferraro@regione.sicilia.it]
9 [Regional Bureau for Agriculture, Rural Development and Mediterranean Fishery, the Department of Agriculture, Service 5 UOS5.05 - Valutazione territoriale e
gestione del rischio in agricoltura, , fabio.guiaitoli@regione.sicilia.it]
sergio.saia@crea.gov.it

2. State of the art
Drylands cover nearly of the half of the world and are inhabited by
ca. 40 % of the world’s population.
In such lands, net primary and agricultural production is limited by
- water scarcity and high temperatures;
- low water holding capacity (WHC)
and low fertility of the soil and other
soil-specific traits
(e.g. soil organic carbon [SOC]);
- soil erosion.
- fragile (agro-)ecosystems;

3. State of the art
World Soil C stock
(Minasny et al. 2017)

4. State of the art
Preservation/increase of the soil organic carbon (SOC)
Potential to mitigate the loss of fertility and thus yield, and increase the CO2
sequestration in soil.
This implies that SOC management plays a direct and crucial role in the world
economy and is strategic to combat hunger and poverty.

5. State of the art
Several measures can be adopted at wide scale to mitigate loss of SOC and
preserve soil ecosystem service:
• Managing land use/land cover;
• Choice of crop species and genotypes;
• Reduction of Soil tillage and other agronomical management techniques;
these interact with climate and soil conditions (e.g. texture, etc)
&
also depends on the gross income of the population in the area and nation.
The ability to indicate site-specific SOC management strategies also rely on
availability of data of SOC and its ancillary variables

6. Aim of the study
Here we used legacy data of a reference semiarid area (Sicily, Italy) to estimate the
importance of land use and soil erosion potential on SOC variation in time and
space at varying soil type and aridity of the environment.
- A total of 25,286 km2, 60% of which cultivated.
- A total of ca. 2700 geo-referenced (more than 1 point each 10 km2) observation of SOC
and 1049 of bulk density;
- mean annual temperatures of 1.8 °C to 15.0 °C and mean annual precipitation from 350 to
1300 mm;
- Several soil orders. Dominant soils (World Reference Base) are Regosols, Calcisols,
Vertisols, Andosols, Leptosols, Phaeozems and Cambisols;
Sicily has great potential as an open laboratory for studies about ecological issues and
anthropic pressure on the agro-ecosystems thanks to the variability of its traits and deep
knowledge of its soils.

7. Materials and Methods
Legacy dataset provided by the Regional Bureau for Agriculture, Rural Development and
Mediterranean Fishery, the Department of Agriculture, and Service 7 UOS7.03
• 2700 soil profiles with SOC observations + texture + actual land use
• 1049 of bulk density

8. Materials and Methods
Predictors of SOC:
• Climatic data from Worldclim (1-km resolution): mean annual temperature and rainfall;
• Land covers from CORINE;
• Remote sensing-derived predictors consisted of the LANDSAT 5 spectral bands and the
Normalized Difference Vegetation Index (NDVI)
• Shuttle Radar Topography Mission digital elevation model (Sept. 2014, 1-arcsec spatial
resolution) for the morphometric spatial predictors. Eleven terrain attributes:
• 1) slope,
• 2) catchment area,
• 3) aspect,
• 4) plan curvature,
• 5) profile curvature,
• 6) length-slope factor,
7) channel network base level,
8) convergence index,
9) valley depth,
10) topographic wetness index,
11) landform classification.

9. Materials and Methods
• Application of 2 Regression Trees modelling for spatialization and handling of not
Gaussian data and have a powerful ecological/anthropic insight on SOC space-time
variation:
• Boosted Regression Trees (BRT; Elith et al., 2008) for C concentration and space-time
change (from 1993 to 2008);
• Stochastic Gradient Treeboost (SGT; Friedman, 2002) for C stock after application of a
pedotransfer function (Pellegrini et al., 2007) for missing bulk density points.
• Dissection of the variations per land use groups:
• ARA: arable land, mostly cropped with cereals, grain and forage legumes;
• VFO: vineyards, fruit trees and berry plantations, and olive groves;
• CCP: annual crops associated with permanent crops, complex cultivation patterns,
land principally occupied by agriculture, with significant areas of natural vegetation.

10. Results - Carbon Stock map
Our map
ISRIC map
GSOC map
Heiderer & Kocky 2012
Soilgrid.com

11. Results - Predictors importance for Carbon Stock
• 71.4% of points predicted in the range of
±50% than observed (light green point)
• SGT R2 = 0.470
• High land use importance (orange bar)
SOC tha-1
>

12. Results – C concentration
Change from 1993 to 2008
1993 – 785 observations 2008 – 337 observations

13. Results – SOC predictors
High land use and texture
importance
Measures related to erosion
Remote sensed
predictors reduced
variability of models

14. Results – SOC variation from 1993 to 2008
Change in SOC from 1993 to 2008 (in g C kg-1 soil)
R2=0.63-0.69
SOC reduced in high
SOC soils and increased
in low SOC soil

15. Results – SOC variation from 1993 to 2008
SOC change map
matched that of
Erosion

16. Results – SOC variation from 1993 to 2008
…but also depended
on land use

17. Results – SOC variation from 1993 to 2008
SOC increased, but its rate was far from the 4 per mille initiative

18. Results – SOC variation from 1993 to 2008
with no interaction
with soil texture
SOC decresed by
65.3±8.4 mg C per 1%
point of Clay increase
in all Land use
ARABLES (ARA) y = -0.0061x + 1.4717
R² = 0.0439
TREE CROPS (VFO) y = -0.0063x + 1.5605
R² = 0.0438
NATURAL(NAT) y = -0.0063x + 1.505
R² = 0.0539
ALL DATAPOINTS y = -0.0065x + 1.5084
R² = 0.0556
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0 15 30 45 60 75
SOC%
CLAY %
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0 15 30 45 60 75
SOC%
CLAY %
SOC (%) at varying clay content (%)
Conf. Int. 90%
Pred. Int. 90%
data points

19. Summary
- SOC reduced in high SOC soils and increased in low SOC soil;
- Land use, texture, rainfall and measurements related to erosion and
deposition were strong predictors of SOC;
- SOC increased in arables (ARA) and tree-crops (VFO) more than
natural and semi natural environments (NAT);
- Map of SOC variation matched that of soil erosion (Fantappiè et al.,
2015) and temperature and rainfall trends in the last 25 years
(Cannarozzo et al., 2006; Viola et al., 2014, not shown).

20. Conclusions & Future prospects
- Need of using highly performing models to address decision making
on soil at the sub- regional level
- Focusing on land use management in agricultural areas is a valuable
tool to increase SOC
- To directly model variation of SOC and other soil properties
- To study the relationship of computed and modelled SOC
variation with measured and prospected variation of SOC predictors
in climate change scenario

21. Thanks for the attention
I wish to thanks all the authors contributing to this work
sergio.saia@crea.gov.it