Statistics of the National soil test database of France

In France, farmers commission about 250,000 soil-testing analyses per year to assist them managing soil fertility. The number and diversity of origin of the samples make these analyses an interesting and original information source regarding cultivated topsoil variability. Moreover, these analyses relate to several parameters strongly influenced by human activity (macronutrient contents, pH...), for which existing cartographic information is not very relevant. Compiling the results of these analyses into a database makes it possible to re-use these data within both a national and temporal framework. A database compilation relating to data collected over the period 1990-2009 has been recently achieved. So far, commercial soil-testing laboratories approved by the Ministry of Agriculture have provided analytical results from more than 2,000,000 samples. After the initial quality control stage, analytical results from more than 1,900,000 samples were available in the database. The anonymity of the landholders seeking soil analyses is perfectly preserved, as the only identifying information stored is the location of the nearest administrative city to the sample site. We present in this dataset a set of statistical parameters of the spatial distributions for several agronomic soil properties. These statistical parameters are calculated for 4 different nested spatial entities (administrative areas: e.g. regions, departments, counties and agricultural areas) and for 4 time periods (1990-1994, 1995-1999, 2000-2004, 2005-2009). Two kinds of agronomic soil properties are available: the firs one correspond to the quantitative variables like the organic carbon content and the second one corresponds to the qualitative variables like the texture class. For each spatial unit and temporal period, we calculated the following statistics stets: the first set is calculated for the quantitative variables and corresponds to the number of samples, the mean, the standard deviation and, the 2-,4-,10-quantiles; the second set is calculated for the qualitative variables and corresponds to the number of samples, the value of the dominant class, the number of samples of the dominant class, the second dominant class, the number of samples of the second dominant class.

Soil characteristics and abundance of archaea in samples from the Ross Sea Region, Antarctica

The objective of this study was to examine the presence and diversity of Archaea within mineral and ornithogenic soils from 12 locations across the Ross Sea region. Archaea were not abundant but DNA sufficient for producing 16S rRNA gene clone libraries was extracted from 18 of 51 soil samples, from four locations. A total of 1452 clones were analysed by restriction fragment length polymorphism and assigned to 43 operational taxonomic units from which representatives were sequenced. Archaea were primarily restricted to coastal mineral soils which showed a predominance of Crenarchaeota belonging to group 1.1b (>99% of clones). These clones were assigned to six clusters (A through F), based on shared identity to sequences in the GenBank database. Ordination indicated that soil chemistry and water content determined archaeal community structure. This is the first comprehensive study of the archaeal community in Antarctic soils and as such provides a reference point for further investigation of microbial function in this environment.

Strontium isotope ratios of plant and soil samples from France

The dataset consists of 87Sr/86Sr isotope ratios of plant samples and soil leachates covering the major geologic regions of France. In addition to the isotope data it provides the spatial context for each sample, including background geology, field observations and soil descriptions. The dataset can be used to create Sr isoscapes for France, which can be applied in a wide range of fields including archaeology, ecology, soil, food, and forensic sciences.

ISRIC-WISE - Global Soil Profile Data (ver. 3.1)

Version 3.1 of the ISRIC-WISE database holds selected site and horizon data for some 10 250 soil profiles from 149 countries. Profile data were extracted from a wide range of sources and harmonized with respect to the original (1974) and revised (1988) Legend of the FAO-Unesco Soil Map of the World. Profiles have been described, sampled, and analysed according to methods and standards in use in the originating countries; analytical results for the same property cannot always be compared directly; as a result the amount of measured data available for modelling is sometimes much less than expected. WISE was specifically developed for land-related applications at continental and global scales.

Global assessment of soil phosphorus retention potential

Limited availability of P in soils to crops may be due to deficiency and/or severe P retention. Earlier studies that drew on large soil profile databases have indicated that it is not (yet) feasible to present meaningful values for "plant-available" soil P, obtained according to comparable analytical methods, that may be linked to soil geographical databases derived from 1:5 million scale FAO Digital Soil Map of the World, such as the 5 x 5 arc-minute version of the ISRIC-WISE database. Therefore, an alternative solution for studying possible crop responses to fertilizer-P applied to soils, at a broad scale, was sought. The approach described in this report considers the inherent capacity of soils to retain phosphorus (P retention), in various forms. Main controlling factors of P retention processes, at the broad scale under consideration, are considered to be pH, soil mineralogy, and clay content. First, derived values for these properties were used to rate the inferred capacity for P retention of the component soil units of each map unit (or grid cell) using four classes (i.e., Low, Moderate, High, and Very High). Subsequently, the overall soil phosphorus retention potential was assessed for each mapping unit, taking into account the P-ratings and relative proportion of each component soil unit. Each P retention class has been assigned to a likely fertilizer P recovery fraction, derived from the literature, thereby permitting spatially more detailed, integrated model-based studies of environmental sustainability and agricultural production at the global and continental level (< 1:5 million). Nonetheless, uncertainties remain high; the present analysis provides an approximation of world soil phosphorus retention potential.

Circumpolar dataset of Soil Organic Carbon north of treeline derived from ENVISAT ASAR GM, link to GeoTIFF

A new approach for the estimation of soil organic carbon (SOC) pools north of the tree line has been developed based on synthetic aperture radar (SAR; ENVISAT Advanced SAR Global Monitoring mode) data. SOC values are directly determined from backscatter values instead of upscaling using land cover or soil classes. The multi-mode capability of SAR allows application across scales. It can be shown that measurements in C band under frozen conditions represent vegetation and surface structure properties which relate to soil properties, specifically SOC. It is estimated that at least 29 Pg C is stored in the upper 30 cm of soils north of the tree line. This is approximately 25 % less than stocks derived from the soil-map-based Northern Circumpolar Soil Carbon Database (NCSCD). The total stored carbon is underestimated since the established empirical relationship is not valid for peatlands or strongly cryoturbated soils. The approach does, however, provide the first spatially consistent account of soil organic carbon across the Arctic. Furthermore, it could be shown that values obtained from 1 km resolution SAR correspond to accounts based on a high spatial resolution (2 m) land cover map over a study area of about 7 × 7 km in NE Siberia. The approach can be also potentially transferred to medium-resolution C-band SAR data such as ENVISAT ASAR Wide Swath with ~120 m resolution but it is in general limited to regions without woody vegetation. Global Monitoring-mode-derived SOC increases with unfrozen period length. This indicates the importance of this parameter for modelling of the spatial distribution of soil organic carbon storage.