https://meetingorganizer.copernicus.org/EGU2014/EGU2014-2022.pdf

Digital soil mapping: A brief history and some lessons

There is a global demand for soil data and information for food security and global environmental management. There is also great interest in recognizing the soil system as a significant terrestrial sink of carbon. The reliable assessment of soil carbon (C) stocks is of key importance for soil conservation and in mitigation strategies for increased atmospheric carbon. In this article, we review and discuss the recent advances in digital mapping of soil C. The challenge to map carbon is demonstrated with the large variation of soil C concentration at a field, continental, and global scale. This article reviews recent studies in mapping soil C using digital soil mapping approaches. The general activities in digital soil mapping involve collection of a database of soil carbon observations over the area of interest; compilation of relevant covariates (scorpan factors) for the area; calibration or training of a spatial prediction function based on the observed dataset; interpolation and/or extrapolation of the prediction function over the whole area; and finally validation using existing or independent datasets. We discuss several relevant aspects in digital mapping: carbon concentration and carbon density, source of data, sampling density and resolution, depth of investigation, map validation, map uncertainty, and environmental covariates. We demonstrate harmonization of soil depths using the equal-area spline and the use of a material coordinate system to take into consideration the varying bulk density due to management practices. Soil C mapping has evolved from 2-D mapping of soil C stock at particular depth ranges to a semi-3-D soil map allowing the estimation of continuous soil C concentration or density with depth. This review then discusses the dynamics of soil C and the consequences for prediction and mapping of soil C change. Finally, we illustrate the prediction of soil carbon change using a semidynamic scorpan approach.

Digital mapping of soil carbon

Organic resource management: Impacts on soil aggregate stability and other soil physico-chemical properties

Properties and Management of Forest Soils

Global soil organic carbon assessment

The influence of climate change on the soil organic carbon content in Italy from 1961 to 2008

This study presents the main results and the methodology used in the creation of the atlas of the risk of desertification in Italy. A desertified area was defined as an unproductive area for agricultural or forestry use, due to soil degradation processes. An area at risk of desertification was a tract of the earth's surface which is vulnerable or sensitive to the processes of desertification. In a vulnerable land, environmental characteristics are close to that of a desertified area, but some factors (e.g. vegetation cover or irrigation), successfully mitigate the desertification process. On the other hand, sensitive land is a surface where the process leading to desertification is active, although the land is not yet unproductive.

The DPSIR (Driving force-Pressure-State-Impact-Response) framework has been adopted as a reference. Using the national soil information system and socio-economic layers, an atlas of indicators of desertification risks was created, which was organized into different soil degradation systems. 51.8 per cent of Italy was considered to be at potential risk of desertification. Some 21.3 per cent of Italy (41.1 per cent of the area at potential risk) featured land degradation phenomena. Specifically, 4.3 per cent of Italy is already unproductive; 4.7 per cent is sensitive and 12.3 per cent is vulnerable. In the territory at potential risk of desertification, unproductive lands, plus areas vulnerable or sensitive to soil erosion, are at least the 19 per cent. Areas affected by aridity also sum up to 19 per cent. Salt-affected soils in Italy are estimated to cover >1 million ha. Irrigation can mitigate soil aridity and salinization, nevertheless, only about 15 per cent of the sensitive and vulnerable lands of southern Italy are actually equipped with irrigation networks. Copyright © 2009 John Wiley & Sons, Ltd.

Rationale and methods for compiling an atlas of desertification in Italy.

Influence of land use on organic carbon pool and chemical properties of Vertic Cambisols in central and southern Italy

Climate has a potential strong influence on the soil forming processes of Italy. The elongated shape of the Italian peninsula, stretching along 11 parallels in the middle of the Mediterranean Sea, and the presence of two morphological barriers, the Alps and the Apennines, cause great local climatic variations. Actually, in Italy, authors recognized 14 of the 35 climatic regions occurring in Europe. Average climatic conditions are temperate, in particular, long-term mean annual air temperature (MAT) is 12.6 (°C) and total annual precipitation (MAP) 932.5 mm, but variations are much more important than means, in fact, they span about 30 °C and 1,800 mm. The degree of continentality, that is, the difference between summer and winter temperature is on average more than 15 °C, but it reaches more than 17 °C in the Po Plain. Seasonality of the precipitations, that is, the difference between the amount of long-term rainfall fallen in the most and in the least rainy months, proportioned to the total long-term annual rainfall, is on average 11 % and more pronounced in the southern regions. Mean long-term potential evapotranspiration is 1,002 mm, ranging from around 600 mm in the Alps and the Northern Apennines to more than 1,300 mm in some parts of Apulia, Sicily and Sardinia. As a result, climatic deficit dominates Italy. The ustic soil moisture regime is the relatively most widespread udometric regime, while the udic regime dominates the Alps and the Apennines chains, and xeric and dry xeric are well correlated with lands with the highest aridity. The mesic soil temperature regime dominates most part of the country, but the thermic regime dominates southern Italy. The frigid and cryic regimes are present in large areas of the Alps and the Apennines. A general climatic change occurred in Italy in the period 1961–2000, with a general reduction in mean total annual precipitation (MAP) and number of rainy days, and a general increase in mean air temperature (MAT). The climate change had a general low influence on soil organic carbon variations. Nevertheless, the relatively higher climatic influence occurred in meadows and in arable lands with a moderate or high MAP decrease ( 0.62 °C). The decreasing SOC content of lands with increasing hot and arid climate could be a soil indicator of the consequences of the extension of the Mediterranean subtropical climatic regions in Italy.

https://www.springer.com/cda/content/document/cda_downloaddocument/9789400756410-c2.pdf?SGWID=0-0-45-1387776-p174672064

Climate and Pedoclimate of Italy

Soils contain about three times the amount of carbon globally available in vegetation, and about twice the amount in the atmosphere. However, soil organic carbon (SOC) has been reduced in many areas, while an increase in atmospheric CO2 has been detected. Recent research works have shown that it is likely that past changes in land use history and land management were the main reasons for the loss of carbon rather than higher temperatures and changes of precipitation resulting from climate change. The primary scope of this work was to estimate soil organic carbon stock (CS) variations in Italy during the last three decades and to relate them to land use changes. The study was also aimed at finding relationships between SOC and factors of pedogenesis, namely pedoclimate, morphology, lithology, and land use, but also at verifying the possible bias on SOC estimation caused by the use of data coming from different sources and laboratories. The soil database of Italy was the main source of information in this study. In the national soil database is stored information for 20,702 georeferentiated and dated observations (soil profiles and minipits) analysed for routine soil parameters. Although the observations were collected from different sources, soil description and analysis were similar, because all the sources made reference to the Soil Taxonomy and WRB classification systems, and soil analyses followed the Italian official methods. Besides horizon description and analysis, soil observations had a set of site information including topography, lithology, and land use. The SOC and bulk density referred to the first 50 cm, thus CS was calculated on the basis of the weighted percentage of SOC, rock fragments volume, and bulk density. A set of geographic attributes were considered to spatialize point information, in particular, DEM (100 m) and derived SOTER morphological classification, soil regions (reference scale 1:5,000,000) and soil systems lithological groups (reference scale 1:500,000), soil moisture and temperature regimes (raster maps of 1 km pixel size), land cover (CORINE project, reference scale 1:100,000) at three reference dates: years 1990 and 2000, and an original update to 2008, obtained with field point observations. The interpolation methodology used a multiple linear regression (MLR). CS was the target variable, while predictive variables were the geographic attributes. Basic statistical analysis was performed first, to find the predictive variables statistically related to CS and to verify the bias caused by different laboratories and surveys. After excluding the biased datasets, the best predictors were selected using a step-wise regression method with Akaike Information Criterion (AIC) as selection and stop criterion. The obtained MLR model made use of the following categorical attributes: (i) decade, (ii) land use, (iii) SOTER morphological class, (iv) soil region, (v) soil temperature regime, (vi) soil moisture regime, (vii) soil system lithology, (viii) soil temperature, (ix) soil aridity index (dry days per year), and, (x) elevation. The interaction between decade and land use variables was also considered in the model. Results indicated that CS was highly correlated with the kind of main type of land use (forest, meadow, arable land), soil moisture and temperature regimes, lithology, as well as morphological classes, and decreased notably in the second decade but slightly increased in the third one, passing form 3.32 Pg, to 2.74 Pg and 2.93 Pg respectively. The bias caused by the variables like “laboratory” and “survey source” could be as large as the 190%.

/pdf/factors-influencing-soil-organic-carbon-stock-variations-in-4p01vj99ut.pdf

G. L'Abate

Papers

The influence of climate change on the soil organic carbon content in Italy from 1961 to 2008

Rationale and methods for compiling an atlas of desertification in Italy.

Influence of land use on organic carbon pool and chemical properties of Vertic Cambisols in central and southern Italy

Climate and Pedoclimate of Italy

Factors Influencing Soil Organic Carbon Stock Variations in Italy During the Last Three Decades