WRB Reference Soil Groups Research Articles

CONSTRUCTION OF A DIAGNOSTIC ALGORITHM FOR SOIL IDENTIFICATION ACCORDING TO THE INTERNATIONAL SOIL CLASSIFICATION SYSTEM WRB

Topicality. In this article discusses the identification of soils according to the international soil classification World Reference Base for Soil Resources system (WRB). The World Reference Base for Soil Resources was developed to identify soils and use the obtained data in different areas of everyday life: agriculture, forestry, animal husbandry, etc. The purpose of the work Note that the WRB, developed by a group of soil scientists, is not meant to replace national classification systems. Besides this classification system, there are also different soil classifications designed by national soil science schools. The difference in the structures of these classifications necessitated the development of a diagnostic algorithm to correlate them with each other. Results Three options for determining whether a soil belongs to reference soil groups are considered, depending either on soil parameters only, or on a combination of diagnostic horizons and soil parameters, or only on diagnostic horizons. A group of scientists headed by M. Babayev also developed a national soil classification system for Azerbaijan. In order to compare these two systems, this study proposes a soil data structure, as well as an algorithm for soil identification according to the WRB classification on the basis of the proposed structure. Conclusion A soil diagnostic algorithm is developed, which will allow identifying any soil type with the corresponding WRB Reference Soil Group. Three variants of allocating soils to WRB Reference Soil Groups based only on soil parameters, or on the combination of diagnostic horizons and soil parameters, or only on diagnostic horizons are considered.

Evaluation of organic carbon stocks in mineral and organic soils in Lithuania

AbstractSoil organic carbon (SOC) stocks at national level were estimated to provide more accurate estimates on SOC for the Lithuanian GHG inventory. The SOC stocks in the forest floor, grassland litter, and in mineral or organic topsoil (0–30 cm) of forest land, grasslands, and croplands were estimated. The assessment was based on forest floor and peat topsoil mass, mineral topsoil bulk density, and carbon concentration in 754 permanent observation plots on 9 × 9 km grid of the National Forest Inventory in Lithuania. The SOC stocks were obtained for eight WRB Reference Soil Groups to provide the estimates for land use, land‐use change, and forestry reporting. The SOC stocks in the forest floor, topsoil of mineral, and peat layers were identified for soils under different land uses. The mean SOC concentrations in the 0–10 and 10–30 cm topsoil of most soil groups, especially fertile forest soils (Cambisols, Luvisols +Retisols) were higher for forest land and grasslands, and lower for croplands. The total averaged SOC stock in the forest floor in mineral and organic soils was 6.97 t ha−1, whereas in the litter of grasslands it was 0.54 t ha−1. The averaged SOC stock in topsoil varied from 56 t ha−1 (Arenosols) to 118 t ha−1 (Cambisols) in mineral forest soils and was 150 t ha−1 (Histosols) in organic forest soils. The total averaged SOC stock in mineral topsoil of forest land, grassland, and cropland was 80, 74, and 72 t ha−1, respectively.

Harmonization of a large-scale national soil database with the World Reference Base for Soil Resources 2014

Legacy soil data currently represents an irreplaceable source of data for many national and international applications. Their full use at the international level largely depends on adequate harmonization. In this study, we adopted different methods of taxonomic distance and reclassification of soil properties to convert a large-scale database originating from an extensive national mapping campaign of agricultural soils in Czechoslovakia (1961–1971), according to the criteria of the World Reference Base for Soil Resources (WRB), version 2014. The harmonization was effectuated at two levels of detail represented by two different types of soil mapping units [soil type and general soil representative (GSR)] and resulted in the conversion of original soil units into their counterparts in the WRB (Reference Soil Groups). The results showed a good potential of the adopted methods for soil data harmonization. The conceptual differences of the two harmonised classifications decreased the applicability of the taxonomic distance in the case of broadly defined and less developed soil classes lacking specific diagnostic features. The replacement of a simple conversion by soil association was a relevant approach, especially at the soil type level, where the simple one-to-one conversion showed only poor accuracy (39.5%). The accuracy at the GSR level was satisfactory (reaching ca 60%) and increased with soil association (72%). The conversion accuracy of different soil classes significantly differed from very high (e.g. 92% in Luvisols) to completely mismatched (Technosols and Histosols). The latter can be attributed to a questionable determination of soil classes in legacy maps. The study showed the potential of taxonomic distance methods in soil data harmonization and the limits of historical databases resulting from the way data were collected and recorded.

Effectiveness of a soil mapping geomatic approach to predict the spatial distribution of soil types and their properties

A soil map (1:50,000 scale) was recently produced in Sardinia (Italy) using a cost-effective GIS approach. In this study we aimed to verify, in two pilot areas and by means of statistical analysis, the effectiveness of the adopted methodology in representing and predicting the spatial distribution of soil types and properties. We focused on evaluation of 1) the influence of landforms and parent materials on soil types (WRB Reference Soil Groups) and selected soil properties and 2) the suitability of the adopted methodology for calibrating a model to predict land unit composition in terms of different soil types.Leptosols, Regosols and Cambisols were prevalent on slopes, with Leptosols being more frequent on convex slopes and Regosols and Cambisols on concave slopes. In flat areas, soil types mainly depended on the type and age of parent material, with Regosols and Cambisols prevailing on Holocene deposits and highly developed soils (mainly Luvisols) largely prevailing on Pleistocene deposits. On hard rock, Leptosols were very frequent on terrigenous metamorphic rock and frequent on granite. Besides Leptosols, Regosols occurred more frequently than Cambisols on both parent materials. Landforms strongly influenced soil depth and available water capacity. Soils on plains were deeper than those on slopes, where convex forms had shallower soils than concave forms. A similar trend applied to the available water capacity. The parent material had a significant effect on topsoil properties (thickness, texture, pH and organic carbon content) of soils belonging to the same WRB Reference Soil Group (analysis done on the most relevant WRB Reference Soil Groups, i.e. Leptosols, Regosols and Cambisols).We calibrated and tested stepwise multiple linear regressions (MLR) and general linear models (GLM) to predict the composition of map units in terms of different WRB Reference Soil Groups. The two models gave very similar results, with distinct distribution patterns that were coherent with the relationships observed between soil groups and specific combination of terrain attributes and parent materials. Results showed that both models were more reliable in predicting the absence rather than presence of a given soil type.

Comparing Uganda's indigenous soil classification system with World Reference Base and USDA Soil Taxonomy to predict soil productivity

This study examines three soil classification systems - Buganda, World Reference Base, and US Soil Taxonomy - in order to evaluate their relative strengths and feasibility for making linkages between them. Nine field sites and 16 pedons were considered across the soil landscapes of the Buganda catena. Each identified field pedon diagnostic horizons and characteristics were described and their soils analyzed using standard pedological techniques and measurements. To document the indigenous use of the Buganda classification system, interviews and discussions were held with farmer groups and local extension specialists. Using this local expertise, five local soil units were identified. We also identified two landscape toposequences with pedons that classified into six WRB Reference Soil Groups and five US Soil Taxonomic Suborders. While four local soil classes each mismatched with international systems' groups, Liddugavu (black) soil corresponded to Phaeozem (WRB) and Udolls (US Soil Taxonomy) and is consistently viewed as the most productive soil due to faster weed growth, diversity of crops it supports and its stable landscape location. Statistical comparisons indicated that the Buganda classes were more homogeneous and effective at separating variability of different soil properties than those of either the WRB Reference Soil Groups or US Soil Taxonomy Suborders. Integrating soil texture, pH and bases information in indigenous system methods could locally complement international classifications and linking the best of both systems would be ideal for the generation of a hybrid system. Our findings show that using the toposequence framework assists in comparing these systems in a way that is useful for scientists and local farmers.

Characteristics of Rendzina soils in Serbia and their WRB classification

According to the Serbian official soil classification system, Rendzina is a soil type with an A-AC-C-R profile, developed on parent rock containing more than 20% of calcareous material (except soils with an A-R profile on hard pure limestone or dolomite). Previous investigations have shown that 29 Rendzina soil profiles from Serbia belong to the reference soil groups (RSGs) of Leptosols, Regosols and Phaeozems according to the World Reference Base for Soil Resources (WRB 2015). The present study addresses the correlations among three WRB RSGs in terms of soil texture, mean weight diameter (MWD), total N content, and humus fractional composition using Principal Component Analysis (PCA). The objective is to better understand the mutual relationship between the classification soil units used in Serbia and the international WRB system. The results show that PCA cannot unequivocally distinguish between these three RSGs. Leptosols and Regosols are highly incoherent groups while the group of Phaeozems is highly coherent, leading to the conclusion that the physical and chemical properties of the soil profiles of Phaoeozems are specific. It is obvious that soil depth and color, which are the overriding factors in the differentiation of Rendzina soils into three WRB RSGs, had no significant effect on these properties. The results further show that soil properties such as texture, MWD, humus fractional composition, etc. cannot be used to correlate Rendzina soils from Serbia with WRB. Instead, careful correlation of individual soil profiles is needed based on quantitative soil data analysis as required by WRB.

Accuracy assessment of different soil databases concerning WRB reference soil groups

As a result of international cooperation, the conditions of data access and data usage have been significantly improved during the last two decades. Also, the establishment of web-based geoinformatic infrastructure allowed researchers to share their results with the scientific community more efficiently on the international level. The aim of this study is to investigate the accuracy of databases with different spatial resolutions, using the reference profiles of LUCAS topsoil database. In our study, we investigated the accuracy of World Reference Base for Soil Resources (WRB) Reference Soil Groups (RSG) groups stored in freely accessible soil databases (European Soil Database (ESDB), International Soil Reference and Information Centre (ISRIC)) in Hungary. The study concluded that the continental scale database tends to be more accurate. We used the Kappa Index of Agreement (KIA) statistical index to evaluate accuracy. The European and the international databases showed a value of 0.9643 and 0.3968, respectively. Considering the results, we can conclude that the spatial resolution has a relevant impact on the accuracy of databases, however, the study should be extended to the national level and the indices should be assessed together.

Benchmark values for forest soil carbon stocks in Europe: Results from a large scale forest soil survey

Soil organic carbon (SOC) stocks in forest floors and in mineral and peat forest soils were estimated at the European scale. The assessment was based on measured C concentration, bulk density, coarse fragments and effective soil depth data originating from 4914 plots in 22 EU countries belonging to the UN/ECE ICP Forests 16×16km Level I network. Plots were sampled and analysed according to harmonized methods during the 2nd European Forest Soil Condition Survey. Using continuous carbon density depth functions, we estimated SOC stocks to 30-cm and 1-m depth, and stratified these stocks according to 22 WRB Reference Soil Groups (RSGs) and 8 humus forms to provide European scale benchmark values. Average SOC stocks amounted to 22.1tCha−1 in forest floors, 108tCha−1 in mineral soils and 578tCha−1 in peat soils, to 1m depth. Relative to 1-m stocks, the vertical SOC distribution confirmed global patterns reported for forest soils: ~50% of SOC was stored in the upper 20cm, and ~55–65% in the upper 30cm of soil. Assuming 163Mha of European forest cover and by using various scaling up procedures, we estimated total stocks at 3.50–3.94Gt C in forest floors and 21.4–22.7Gt C in mineral and peat soils down to 1-m, which is ~40% more than commonly published. The most useful predictors and stratifiers for C stocks were humus form and tree species for the forest floor, RSG for mineral soils and parent material for peat soils.This dataset will be further explored, predominantly for validation of soil C models, resampling and comparison with legacy and future forest SOC inventories.

Comparing data mining and deterministic pedology to assess the frequency of WRB reference soil groups in the legend of small scale maps

The assessment of class frequency in soil map legends is affected by uncertainty, especially at small scales where generalization is greater. The aim of this study was to test the hypothesis that data mining techniques provide better estimation of class frequency than traditional deterministic pedology in a national soil map.In the 1:5,000,000 map of Italian soil regions, the soil classes are the WRB reference soil groups (RSGs). Different data mining techniques, namely neural networks, random forests, boosted tree, classification and regression tree, and supported vector machine (SVM), were tested and the last one gave the best RSG predictions using selected auxiliary variables and 22,015 classified soil profiles. The five most frequent RSGs resulting from the two approaches were compared. The outcomes were validated with a Bayesian approach applied to a subset of 10% of geographically representative profiles, which were kept out before data processing. The validation provided the values of both positive and negative prediction abilities.The most frequent classes were equally predicted by the two methods, which differed however from the forecast of the other classes. The Bayesian validation indicated that the SVM method was more reliable than the deterministic pedological approach and that both approaches were more confident in predicting the absence rather than the presence of a soil type.

Modeling soil genesis at pedon and landscape scales: Achievements and problems

Modeling soil evolution is an important step towards understanding the complexity of the soil system and its interaction with the other systems. The major challenge confronted by pedologists until now is the ability to develop models capable of describing the complete complexity of the soil system. This paper presents the state of art overview of such a soil evolution model, SoilGen, its applications and limitations. In addition, the paper gives an overview of how the SoilGen model may be linked to landscape evolution models to model soilscape development. SoilGen is a mechanistic pedogenetic model in which soil forming processes such as clay migration, decalcification, carbon cycling, bioturbation, physical and chemical weathering coupled with water flow are simulated at multi-millennium time scale. The model has been calibrated and undergone extensive field testing, giving reasonable results at both pedon and landscape scales. However discrepancies between observed and simulated soil properties such as base saturation (BS), cation exchange capacity (CEC) and pH have been reported. These have been attributed partly to simplification of soil forming processes particularly in the weathering and chemical systems. There is therefore a need to extend the description of chemical and weathering systems in the SoilGen model. These extensions will not only improve model performance but will also enlarge its application range in simulating the genesis of typical features of more than half of the WRB-Reference Soil Groups. We also note here that although landscape evolution models have been successfully applied to model soil production and distribution, simplified and/or incomplete description of soil forming processes remain major limitations. We therefore add to the voices in scientific literature calling for integration of pedon and landscape scale models. In addition there is critical need for high quality chronosequence, climosequence, and toposequence profile datasets to enhance calibration and validation of soil evolution models.

Soil taxonomic distance, a tool for correlation: As exemplified by the Hungarian Brown Forest Soils and related WRB Reference Soil Groups

This paper discusses the application of taxonomic distance calculations for the correlation of soil units from different soil classification systems.Conceptual and centroid-based methods were tested on the brown forest soil types of the Hungarian Soil Classification System, correlated with the Reference Soil Groups of the World Reference Base for Soil Resources. The results of the distance calculations were compared and evaluated with previous expert based correlation studies.Earlier studies to derive taxonomic distances between soil taxa based on their dominant identifiers were further developed with the introduction of finer coding, and the application for correlation purposes. For the centroid-based approach, values were calculated from legacy laboratory data of different soil properties of the studied soil classes to derive the taxonomic distances.The results of the three different approaches are concordant, but as each method studied has its own limitations, we recommend their joint application. Therefore the methods complement each other and provide a good tool to assist correlation tasks. We found this study very helpful in identifying the shortcomings of certain definitions and the conceptual conflicts within and between systems. The numerical approaches should be applied in the evaluation of current systems in the efforts toward a Universal Soil Classification System.

Availability and evaluation of European forest soil monitoring data in the study on the effects of air pollution on forests

In the study of air pollution effects on forest ecosystems, solid soil data such as cation exchange capacity, base saturation and other exchangeable cation fractions, soil texture, soil moisture, soil weathering rates, C/N ratio and other variables form an important information base for many air pollution impact models. This paper shows some of the possibilities and the limitations of the soil data that European countries collected on the systematic Level I and on the intensive and permanent Level II monitoring plots within the ICP Forests programme. The soil data date from a first inventory in the 1990s and from a second inventory more than 10 years later. Both surveys were conducted following a common manual on sampling and analysis of soil. An example of the changes in pH(CaCl2) and base saturation in the forest floor and mineral soil on more than 2000 plots till a depth of 80 cm between the two surveys is presented. In this period the pH(CaCl2) significantly increased in the very acid forest soils [with pH(CaCl2) below 4.0] but further decreased in forest soils with pH(CaCl2) above 4.0. Following the trend in pH, the base saturation increased in soils with a very low buffering capacity (soils with a base saturation below 20% in the first inventory) and decreased in forest soils with reference base saturation values above 20%. There is both a decrease of soil pH and base saturation in the forest floor of the Arenosols and Podzols. In the Podzols this decreasing trend could not be established in the mineral soil, though this decreasing trend persisted in a number of mineral soil layers of the Arenosols. The only consistent increasing trend of pH and base saturation when stratifying according to the WRB reference soil groups was seen in the forest floor of the Luvisols and Cambisols.

A gamma‐ray spectrometry approach to field separation of illuviation‐type WRB reference soil groups in northern Thailand

AbstractAccording to the World Reference Base for Soil Resources (IUSS Working Group WRB, 2006), the differentiation of Acrisols and Alisols is based on the cation‐exchange capacity of clay, which cannot be directly determined in the field, but needs expensive and time‐consuming soil‐chemical analyses. This is an unsatisfactory situation for pedologists, who urgently require a rapid field method to distinguish illuviation‐type reference soil groups (Alisols, Acrisols, Luvisols, Lixisols). In this study, we tested the ability of gamma‐ray spectrometry to separate major WRB reference soil groups in the field. The underlying hypothesis is that Alisols and Acrisols are distinguished by their clay mineral composition, which should be reflected by geochemistry and consequently gamma‐ray radiation (i.e., K‐containing illite vs. K‐free kaolinite).Highly significant differences in their gamma‐ray spectrum for K, Th, and U were found for limestone and its soils. Especially the K and Th signatures allowed a clear separation of Acrisols and Alisols. In general, the surface radiation was sufficient to separate these soils. Best results were revealed considering parent rock and the whole soil profile. This means by using a portable radiometer and a pH meter, all illuviation‐type reference soil groups could be distinguished in this case. If applicable at other sites, this approach could enormously reduce expenditures for soil‐chemical analysis needed to assist soil classification.

Taxonomic distance measurements applied for soil correlation

The development of the recent European and global initiatives resulted in an increasing demand for harmonized digital soil information. One of the major limitations of harmonization is the great variation of field and analytical methods and classification systems. Since 1998, the World Reference Base for Soil Resources (WRB) is the global correlation scheme for soil classification and international communication. The one to one correlation of units, however, is difficult, if not impossible. Another problem is that the correct correlation of national units to WRB units might have spatial consequences. If the original map units need to be maintained, it is important to express the extent to which certain national units match with the WRB units. Taxonomic distance measurements were applied successfully to express numerically the correlation between the brown forest soil types (BFS) of the Hungarian Soil Classification System (HSCS) and WRB Reference Soil Groups (RSGs).