Data on the soil and vegetation properties at the small gully catchment area: Steppe region of Kalmykia Republic (South Russia)

In rural areas, research on the environment in native (untaught) soils is important to understand the rate of pedogenesis and to prevent the problems associated with hidden huger. In this article, original data on vegetation, chemical properties and elemental and mineralogical composition of Kastanozems (Protosalic, Siltic) and Hypersalic Solonetz (Siltic) of the small gully catchment (2 ha in total) located at the NE Ergeni Upland (Western Kalmykia, Russia) were presented. Vegetation was described and cut off (to characterize an aboveground biomass) at 13 key plots of 1 × 1 m. The list of species of the small gully catchment area amounts to 23 species (predominantly, perennial herbs) belonging to 13 families and 11 orders. The main dominants are Artemisia lerchiana, A. austriaca, Festuca valesiaca and Poa bulbosa. Soils were described and sampled in 11 cross-sections and two key plots (0 – 10 cm topsoil sampling). In soil water extracts (79 samples in total), electrical conductivity (EC) and pH were measured. In soil samples, particle size distribution, soil organic carbon and CaCO3 contents, total concentration of all the macro elements, some trace (Cl, Nb, Rb, Th, Y, Zr) and potentially toxic elements (As, Co, Cr, Cu, Ni, Pb, Sr, V, and Zn) were described. Moreover, the concentration of three mobile fractions of elements (Li, Be, B, Na, Mg, Al, Si, P, S, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Sr, Ba, Cd, Pb) measured using Inductively Coupled Plasma Atomic Emission Spectrometry (AES-ICP) was presented. Geochemical indexes of weathering (R – Silica/Alumina, CIW – Chemical Index of Weathering, CIA - Chemical Index of Alteration, WIP – Weathering Index of Parker, PWI –Product of Weathering Index, Vogt Ratio, PIA – Plagioclase Index of Alteration, STI – Silica-Titanium Index, B/A – Bases/Alumina, B/R – Bases/R2O3, Si/R - Silica/R2O3, Weathering indexes WI-1 and WI-2, Si/Ses – Silica/Sesquioxides, Si/Fe – Silica/Iron, a – Potassium/Sodium, ba-1 – (Potassium-Sodium)/Alumina, ba-2 – (Calcium-Magnesium)/Alumina, Ba – (Potassium-Sodium-Calcium)/Alumina) were calculated. In 12 bulk soil samples from Kastanozems and Solonetz, mineralogy (X-Ray diffractometry, the Rietveld full-pattern fitting method for quantitative analysis) was described. Data obtained can be used for more confident identification of pollution sources and pollutants’ migration routes, as well as for more effective land-use management, calculating the required doses of nutrients and for adaptation of land use.


Specifications
Environmental science (General) Specific subject area Environmental Chemistry, Earth Sciences, Biology, Soil Science, Botany, Mineralogy Type of data Table  Image Chart Graph Figure  How data were acquired Particle-size distribution was measured using an 'Analysette 22 Nano Tech' equipment (Germany). Data on pH-value of a 1:2.5 water extract was acquired using 'Expert-001' (Russia). Data on electrical conductivity of a 1:5 water extract was acquired using 'Expert-002' (Russia). Soil organic carbon content was measured by a dichromate method [1] . Total content of chemical elements was measured via an Axios X-Ray fluorescence spectrometer made by PANalytical (Netherlands). Data on elemental composition of acetate buffer and 1M nitric acid extracts was acquired using an atomic emission mass-spectrometer 'iCAP-6500' by Thermo Scientific (USA). Data on mineralogy was acquired using an ULTIMA-IV X-Ray diffractometer made by Rigaku (Japan) with Cu radiation and a DTex/Ultra semiconductor detector. Phylogenetic tree of species found at the key site was built on a basis of a phylogenetic tree using scripts and instructions from Qian and Jin (2016).
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Value of the Data
• Data could be used for the assessment of floristic richness variation in semi-arid ecosystems effected by climate change, as well as for mitigation of negative consequences resulted from soil salinity effects. • Data may be useful for i. farmers and practitioners to adapt and mitigate negative effects formed in semi-arid lands due to salinity and ground water level changes, as well as climate change, ii. for soil scientists to evaluate migration and transformation of substances (including a mineral soil matrix) in neutral and alkaline conditions and iii. for botanist to characterize the flora in steppe regions. • Data will be important for further estimation of co-evolution of soils and plants in semi-arid regions effected by climate change, human impact and fires.

Data Description
Data were collected at the small gully catchment (2 ha in total) located at the NE Ergeni Upland (Western Kalmykia, Russia) ( Fig. 1 ).    In the small gully catchment, key plots were accomodated at the interfluve position ( Fig. 2 ) and at the gully bottom ( Fig. 3 ) to characterize plants grown on Kastanozems and Solonetz and (physico-)chemical and mineralogical composition of soils. In this paper, data on the geobotanical descriptions at the 13 key plots of 1 × 1 m (1 m 2 ; Table 1 , Fig. 4 ) and data on 79 soil samples collected from 11 cross-sections and 2 key plots where topsoil was sampled were presented. 23 species of vascular plants found at the small gully catchment area belong to 13 families and 11 orders ( Table 1 , Fig. 5 ).
Kastanozems and Solonetz are forming under dwarf semishrubs and herbs ( Table 3 ). At Solonetz, it is higher projective cover of vascular plants and above ground phytomass ( Fig. 10 ).

Experimental Design, Materials and Methods
Leveling survey was carried out along three profiles ( Fig. 11 ). Phylogenetic tree of species found at the gully catchment area was built on a basis of a phylogenetic tree using scripts and instructions from [2] . Two species absent in an initial tree [4] ( Artemisia lerchiana and Petrosimonia triandra ) named according to [3] ) were added to basal nodes of their families using scripts provided in [4] .   -     A total of 79 soil samples (50 0-70 0 g each) were collected from a depth 0 -130 cm (A, B and C soil horizons of Kastanozems and Solonetz). Plastic and steel tools were used for sampling. After air-drying and declumping the aggregates, the soil was sieved through a 1 mm mesh sieve. In soil samples, particle-size distribution, elemental composition (total concentration of 26 chemical elements), and total organic carbon content (dichromate digestion based on Walkley-Black method) were measured. The particle-size distribution was analyzed using a laser diffraction     technique and an 'Analysette 22' equipment (Germany) in samples pre-treated with 4% Na 4 P 2 O 7 . CaCO 3 concentration was analyzed by a manometric measurement of the CO 2 released following acid (HCl) dissolution [8] .The total content of chemical elements was measured using an X-Ray fluorescence technique and a PANalytical spectrometer (Netherlands) as described in details in [9 , 10] . A soil water extracts were prepared to measure pH value (1:2.5 soil:water ratio) and electrical conductivity (a 1:5 soil:water ratio).
Mobile fractions (F1-F3) were obtained according to the extraction procedure by [11] with the use of the following reagents: F1 (ChE1) -with NH 4 Ac (ammonium acetate buffer) and the soil:solution ratio of 1:5, F2 (ChE2) -with 1% EDTA (ethylenediaminetetraacetic acid) in NH 4 Ac and the soil:solution ratio of 1:5 and F3 (ChE3) -with 1M HNO 3 and the soil:solution ratio of a 1:10. Concentrations of the extracted ChEs in the filtrates were determined using an 'iCAP-6500' (Inductively Coupled Plasma Atomic Emission Spectrometer by 'Thermo Scientific', USA).
The ChE mobility (ChE_m , Table S1) was calculated as a ratio of its mobile fractions (F1 + F2 + F3) to its total content, multiplied by 100%.
At the MSU Faculty of Geology, soil mineralogical composition (phyllosilicates and other minerals; Table 4 ) was determined using an ULTIMA IV X-Ray diffractometer (made by Rigaku, Japan) operated at 40 kV, 40 mA, 3-65 °2 θ , with Cu radiation and a DTex/Ultra semiconductor detector. Minerals were identified by comparing experimental data with standard X-Ray patterns from the PDF-2 database with the use of the MDI Jade 6.5 software and methodological recommendations by [12][13][14] . A quantitative mineralogical analysis was carried out using the Rietveld full-pattern fitting method [15] and the BGMN software [16] .