The fourth edition of the international soil classification system World Reference Base for Soil Resources (WRB) was released in 2022. It maintains the 32 Reference Soil Groups at the first ...classification level. Most qualifiers (second level) and most diagnostic horizons, properties and materials were maintained but some were abolished and new ones introduced. The main part of the fourth edition is followed by six annexes, most of them are new. For the first time, the WRB has a Field Guide (Annex 1) to facilitate field survey and to assure that all field characteristics required in the classification are reported. The fourth edition also provides designations for horizons and layers (Annex 3), which was not the case in the second and the third edition. The wordings of the definitions were harmonized, and the same features are worded in the same way throughout the text (including the annexes). Ambiguities have been corrected and many definitions written in a more concise and a more didactical way. The WRB has a long history. Four editions have been published: 1998, 2006 (with update 2007), 2014 (with update 2015) and 2022. Editor is the Working Group WRB of the International Union of Soil Sciences. The WRB followed the Legend and the Revised Legend of the Soil Map of the World. This map was edited by FAO (Food and Agriculture Organization of the United Nations) and UNESCO, and the system is known as the FAO Soil Classification System. In addition, WRB incorporated ideas from the former Working Group International Reference Base for Soil Classification that existed from 1982 to 1994.
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•A deep-learning model was developed for identifying and delineating soil horizons.•Data augmentation was used to increase the diversity of the profile image dataset.•Results of the ...proposed model compared well with manually delineated horizons.•An Android smartphone application was developed as a digital soil description tool.
Soil horizons are the manifestation of pedogenesis and contain the basic morphologic indicators of soil formation. Accurate and quantitative tools for delineating soil horizons in-situ can assist soil scientists towards rapid and dynamic soil survey information. The objective of this study was to develop a deep-learning-based, soil-profile-imaging method for identifying and delineating soil master horizons to assist in digital soil descriptions. A total of 160 soil profile images from four soil orders (Alfisols, Entisols, Inceptisols, and Mollisols) were collected from north China in the Inner Mongolia and Liaoning regions. The 160 profile images were amplified to 2400 individual images for model building using data-augmentation procedures. The augmented profile image dataset was divided into training (70%), validation (15%), and test (15%) datasets. The training and validation datasets were imported into a nested, U-net network for model building. The proposed deep-learning (DL) model classified soil profiles into A, B, and C horizons. The mean pixel accuracy of the DL model was 0.86 with the training dataset, 0.82 with the validation dataset, and 0.83 for the test dataset. Results showed that the DL model was judged to be accurate enough for identifying and delineating soil master horizons from profile images in practice. Based on the proposed DL model, a smartphone application was subsequently developed to digitalize the soil profile and assist field evaluation of soil profile horizonation. The smartphone application, for the Android operating system (version 5.0 and greater), featured a response time of < 5 s. This study demonstrated that the proposed DL model and smartphone application could be a simple, fast, and digital tool for quickly identifying and delineating in-situ soil horizons. These tools allow for rapid data collection, which can be used for future artificial intelligence development and application in soil science towards digital soil profile description and dynamic soil survey.
Saxifraga hirculus is a postglacial relict in Central Europe, whose populations suffered a dramatic decrease in the 19th and 20th centuries. However, few researchers have been interested in its ...ecological requirements in Central Europe. This article synthesizes previous knowledge supplemented by original data from the last large population (Switzerland).
S. hirculus is a weak competitor which needs precise ecological conditions. It grows on bryophyte carpets in neutral to slightly acid wetlands, with stable water table close to the soil surface (optimum between 8 and 14
cm) but does not stand long flooding. However, it requires a good oxygen supply, with roots 2–3
cm under the soil surface, generally not reached by water, with running, cold water through loose, fibric peat. Its optimal conditions are in spring fens, but it grows in other types of wetlands as well. However, overgrowing by shrubs, sedges or
Sphagnum in natural successions may threaten the species with extinction, as did drainage and peat extraction previously. Now, its survival in Central Europe depends on an adequate management of the ecosystems. Moderate grazing (cattle or sheep) or mowing help to limit competition with taller
Carex species. Reintroduction of disappeared populations or creation of new ones from cultivation in botanical garden is possible, but appropriate sites are rare. In some cases, substrate management could improve the conditions in somewhat inadequate situations. This management in four directions can be flexibly applied in different situations to progress to optimal conditions for the conservation of this valuable species.
Fox, C. A., Tarnocai, C., Broll, G., Joschko, M., Kroetsch, D. and Kenney, E. 2014. Enhanced A Horizon Framework and Field Form for detailed field scale monitoring of dynamic soil properties. Can. J. ...Soil Sci. 94: 189â208. Taxonomic protocols for A horizon description are limited when detailed monitoring of soil change in dynamic soil properties is required for determining the effectiveness of best management practices, remediation efforts, and assessing subtle impacts on soil properties from environmental and anthropogenic stressors. The A Horizon Framework was designed by consolidating protocols from national and international description systems and expert opinion to optimize descriptive capability through use of additional enhanced lowercase designators. The Framework defines new protocols and syntax resulting in a unique soil fingerprint code. Five levels of enhanced lowercase A horizon designators are defined: Level 1, Soil processes and environmental context; Level 2, Soil structure-bulk density; Level 3, Organic carbon; Level 4, pH and electrical conductivity; and, Level 5, Soil and landscape context (i.e., soil texture, surface conditions, current land use, slope character). An electronic Field Form based on the new Framework syntax automatically records the soil fingerprint code in an enhanced (all Levels included) and a minimum detail mode focused on the key dynamic properties. The soil fingerprint codes become a powerful tool by which to identify trends of soil change and small alterations in the dynamic soil properties. Examples of soil fingerprint codes from selected Canada and Germany long-term experimental studies are presented.
This paper describes natural resource factors in order to assist extension service with decision making and planning purposes in Lambani, a rural farming community in the Limpopo Province. The ...natural resource factors (soil, climate and rangeland) were described for implementation of Rainwater Harvesting and Conservation (RWH&C) techniques in Lambani. The long-term climate data was used to characterize the climate in the study area. An intensive-grid soil survey was conducted and the soils were described and classified according to South African Classification System. Climate results indicate that the low rainfall should be utilized effectively by making use of RWH&C techniques. The soil survey results showed that the area comprise of eight different (8) soil forms of which three (3) are not recommended for crop production. A soil map showing soils in this community was created and it is recommended that it should be used for land-use planning.
Digital soil mapping from conventional field soil observations Balkovic, J., International Inst. for Applied System Analysis, Laxenburg (Austria); Rampasekova, Z., Constantine the Philosopher Univ., Nitra (Slovak Republic). Faculty of Natural Sciences; Hutar, V., Soil Science and Conservation Research Inst., Bratislava (Slovak Republic) ...
Soil and Water Research (Czech Republic),
01/2013, Volume:
8, Issue:
1
Journal Article
Peer reviewed
Open access
We tested the performance of a formalized digital soil mapping (DSM) approach comprising fuzzy k-means (FKM) classification and regression-kriging to produce soil type maps from a fine-scale soil ...observation network in Risnovce, Slovakia. We examined whether the soil profile descriptions collected merely by field methods fit into the statistical DSM tools and if they provide pedologically meaningful results for an erosion-affected area. Soil texture, colour, carbonates, stoniness and genetic qualifiers were estimated for a total of 111 soil profiles using conventional field methods. The data were digitized along semi-quantitative scales in 10-cm depth intervals to express the relative differences, and afterwards classified by the FKM method into four classes A-D: (i) Luvic Phaeozems (Anthric), (ii) Haplic Phaeozems (Anthric, Calcaric, Pachic), (iii) Calcic Cutanic Luvisols, and (iv) Haplic Regosols (Calcaric). To parameterize regression-kriging, membership values (MVs) to the above A-D class centroids were regressed against PCA-transformed terrain variables using the multiple linear regression method (MLR). MLR yielded significant relationships with R2 ranging from 23% to 47% (P less than 0.001) for classes A, B and D, but only marginally significant for Luvisols of class C (R2 = 14%, P less than 0.05). Given the results, Luvisols were then mapped by ordinary kriging and the rest by regression-kriging. A "leave-one-out" cross-validation was calculated for the output maps yielding R2 of 33%, 56%, 22% and 42% for Luvic Phaeozems, Haplic Phaeozems, Luvisols and also Regosols, respectively (all P less than 0.001). Additionally, the pixel-mixture visualization technique was used to draw a synthetic digital soil map. We conclude that the DSM model represents a fully formalized alternative to classical soil mapping at very fine scales, even when soil profile descriptions were collected merely by field estimation methods. Additionally to conventional soil maps it allows to address the diffuse character in soil cover, both in taxonomic and geographical interpretations.
The long-term test area of Groß Kreutz is located in the northern area of the Glindower Plateau. This is a part of the landscape Mittelbrandenburgische Plateaus and Lowlands. Albeluvisols and Luvic ...cambisols dominate on loamy plateaus with partly sandy areas. In most cases sandy deposits overlay loamy till on plateaus. Lowlands are dominated by soils with high level of groundwater as gleysols on sandy deposits and histosols. The soil profile can be described as an Arenic Albeluvisol according to Bailly et al. (
1998
). The substratum consists of periglacial loamy sands overlaying glacial deposits. It is typical for most of the parts of Glindower Plateau with till on Weichsel Glacial Period. The translocation of clay from the topsoil to the depth can be found in kind of light-coloured horizon. A strong accumulation of clay can be identified up to a depth of 0.4 metres. Under the topsoil with low content of organic matter the dry bulk density is increased.
Twenty-one sites known to be highly productive pine mushroom (
Tricholoma magnivelare Peck Redhead) habitat were described in northwest British Columbia. Soils were well to very rapidly drained and ...generally coarse in texture, often with a high coarse fragment content and thin forest floor. Western hemlock (
Tsuga heterophylla Raf. Sarg.) was consistently the dominant tree species, and lodgepole pine (
Pinus contortavar.
latifolia Engelm) was frequently, though not always, present in the tree layer. Plant communities typically featured sparse herb and shrub layers, and a high coverage of mosses. Using the British Columbia biogeoclimatic system of ecosystem classification, all sites in the interior cedar hemlock forests were classified as the (01) Hw-step moss site series, submesic phase, and in the coastal western hemlock forests, as the (03) HwPl-feathermoss site series.
Four separate areas of interior cedar hemlock forests, encompassing approximately 60,000
ha were assessed using air photography for the described (01) Hw-step moss submesic habitat. The extent of the submesic habitat across study areas ranged from 4.3 to 21.5% of the hemlock forests. The relatively low areal extent of these valuable forests demonstrated the need to better protect and manage the pine mushroom resource.
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