Stable Soil Properties Research Articles

Analysis of macro and micro freezing characteristics of gravelly soil

To investigate the mechanism of effect of different gravel contents on freezing characteristics of gravelly soil, macroscopic and microscopic experiments were combined. Unidirectional freezing experiment and NMR experiment were conducted on gravelly soil, with gravel contents of 0%, 10%, 20%, 30%, 40% and 50%. In unidirectional freezing experiment, final temperature, stratified moisture content and frost swelling of the samples showed a parabolic pattern with an upward opening about the gravel admixture. Among that, it was at the lowest point of 30% content with the closest space between gravel and soil grains, the least consumption of heat conduction, the largest compression of water migration, making the slowest development of frost-heaving and water supply. NMR experiment results showed that freezing characteristic curve was divided into four stages of subcooling-fast-slow-stable freezing, and gravel content was proportional to the subcooling temperature and value of sudden drop of unfrozen water. Combined with the T2 spectrum, it could be seen that larger pore structure of 30% content was relatively stable with well-distributed water migration during freezing process, and order of water freezing was free water went ahead of bound water, leading to a reduction rate of water migration was from fast to slow, with a consistent pattern of the evolution rate of macro parameters. In summary, the addition of a reasonable gravel proportion in engineering applications of cold zone could ensure relatively well-distributed and stable soil properties and pore structure, and relative low difference in temperature, moisture pooling, and frost swelling. Ultimately improving the safety and reliability of the overall operation of the project.

Spatial variability of saturated hydraulic conductivity and its links with other soil properties at the regional scale

Saturated hydraulic conductivity (K) is a key property for evaluating soil water movement and quality. Most studies on spatial variability of K have been performed soil at a field or smaller scale. Therefore, the aim of this work was to assess (quantify) the spatial distribution of K at the larger regional scale in south-eastern Poland and its relationship with other soil properties, including intrinsic sand, silt, and clay contents, relatively stable organic carbon, cation exchange capacity (CEC) and temporally variable water content (WC), total porosity (FI), and dry bulk density (BD) in the surface layer (0–20 cm). The spatial relationships were assessed using a semivariogram and a cross-semivariogram. The studied region (140 km2) with predominantly permeable sandy soils with low fertility and productivity is located in the south-eastern part of Poland (Podlasie region). The mean sand and organic carbon contents are 74 and 0.86 and their ranges (in %) are 45–95 and 0.002–3.75, respectively. The number of individual samples varied from 216 to 228 (for K, WC, BD, FI) to 691 for the other soil properties. The best fitting models were adjusted to the empirical semivariogram (exponential) and the cross-semivariogram (exponential, Gaussian, or linear) used to draw maps with kriging. The results showed that, among the soil properties studied, K was most variable (coefficient of variation 77.3%) and significantly (p < 0.05) positively correlated with total porosity (r = 0.300) and negatively correlated with soil bulk density (r = – 0.283). The normal or close to the normal distribution was obtained by natural logarithmic and root square transformations. The mean K was 2.597 m day−1 and ranged from 0.01 up to 11.54 m day−1. The spatial autocorrelation (range) of K in the single (direct) semivariograms was 0.081° (8.1 km), while it favourably increased up to 0.149°–0.81° (14.9–81 km) in the cross-semivariograms using the OC contents, textural fractions, and CEC as auxiliary variables. The generated spatial maps allowed outlining two sub-areas with predominantly high K above 3.0 m day−1 in the northern sandier (sand content > 74%) and less silty (silt content < 22%) part and, with lower K in the southern part of the study region. Generally, the spatial distribution of the K values in the study region depended on the share of individual intrinsic textural fractions. On the other hand, the ranges of the spatial relationship between K and the intrinsic and relatively stable soil properties were much larger (from ~ 15 to 81 km) than between K and the temporally variable soil properties (0.3–0.9 km). This knowledge is supportive for making decisions related to land management aimed at alteration of hydraulic conductivity to improve soil water resources and crop productivity and reduce chemical leaching.

A modelling framework for pedogenon mapping

Soil entities are generally defined based on soil properties, using morphological, genetic, or utilitarian criteria. Alternatively, soil entities could be characterized by groupings of homogeneous soil-forming factors under the assumption that the dominant soil-forming processes occurring over a time period within each group are similar, and therefore develop unique soil entities with similar soil properties. We define the pedogenon as a conceptual soil taxon defined from a set of quantitative state variables that represent the soil-forming factors for a given reference time. The objective of this study was to develop a methodology for mapping pedogenon classes at the time of the European settlement in New South Wales (Australia). This period was chosen as reference because from 1788 onwards the intensification of land use has accelerated the rate of change of soil properties. We implemented a two-step modelling approach with a set of environmental covariates representing the soil-forming factors, including the estimated natural vegetation at 1750. The k-means algorithm was applied to generate pedogenon classes suitable for local management. Then, hierarchical clustering was applied to identify the organization of pedogenons into families or “branches” of higher level taxa. We tested the ability of the pedogenon classes for explaining the variance of stable soil properties (particle size fractions) in the subsoil (30–60 cm depth) with redundancy analysis (RDA). The results indicated that between 800 and 1000 pedogenon classes provide the desired level of detail for both local and regional management across New South Wales. The influence of the pre-1750 vegetation types (e.g. Acacia open woodlands and shrublands, Callitris forests and woodlands) was apparent in the distribution of some pedogenon branches. Pedogenon classes differed in their characteristics (median area ≈750 km2), but overall showed meaningful spatial patterns at local scale and formed regional assemblages. The RDA models indicated that pedogenon classes explained about 30% of the variance of silt and clay content. This flexible modelling framework allows the creation of pedogenon maps over large areas at high resolution (90 m) and is applicable at different scales. Potential applications of pedogenon maps include the quantitative assessment of soil change and designing soil monitoring surveys.

Typical Signs and Properties of Agricultural-Podzolic Soils of Northern Forest-Steppe

Based on the results of soil and agrochemical surveys, the state of soil fertility of agro-podzolic soils of the northern forest-steppe under conditions of intensive farming has been studied. The generalization of the soil properties of individual indicators in an amount of 44-148 values characterizing the given territory was carried out by methods of mathematical statistics. The features of the analyzed soils are discussed by dividing into two groups - fundamental and stable. The first group includes a combination of genetic horizons of the soil profile. This group also included the content of clay fraction and physical clay, the pH of the salt extract. The group of stable soil properties includes the humus content, the sum of absorbed bases and hydrolytic acidity. The results of typical soil characteristics and properties, depending on the duration and intensity of the impact of agricultural processing, their indicators are a criterion for assessing and optimizing soil conditions for crops. In this case, the actual data processed by the statistical method is more informative than the specific measurements.

Optimal placement of proximal sensors for precision irrigation in tree crops

Soil water or plant water status-based precision irrigation has the potential to improve water productivity. In this study, the question of number as well as placement of proximal sensors called leaf monitors that provide plant water status information has been addressed, to assist in implementation of precision irrigation. To accomplish this task, an algorithm based on the Fuzzy C-Means logic that utilized spatial variability in soil and plant attributes was developed. First, stable soil properties such as soil texture, digital elevation and apparent soil electrical conductivity data were used to create management zones (MZ). Following the creation of MZ, stem water potential data from an almond orchard and a vineyard located in California were used to determine number as well as the placement location of sensors within each MZ. The methodology and algorithm developed successfully indicated the number of sensors that need to be used and the location of the trees where the sensors should be installed.

Use of the farmer’s experience variable in the generation of management zones

In the spatial variability management of fields, the approach based on management zones (MZs) divides the area into sub-regions, which have spatially homogeneous topography and soil conditions. Such MZs should lead to the same potential yields. Farmers understand which areas of a field have high and low yields, and use of this knowledge may allow the identification of MZs in a field based on production history. The objective of the present study was to evaluate the application of farmer's experience to determine MZs. The study was conducted in three agricultural fields located in the west of the Paraná State in Brazil, and the MZs were generated considering three cases: a) without the use of the farmer’s experience variable; b) with the variable of farmer’s experience and the stable soil properties selected at the variable selection stage; and c) only with the farmer’s experience variable. The generated MZs were evaluated using the Variance Reduction (VR) index, Fuzziness Performance Index (FPI), Modified Partition Entropy (MPE), Smooth Index (SI), and Analysis of Variance (ANOVA). The study showed that the use of farmer’s experience to set MZs could be an efficient and simple tool, that it could reduce costs for the processes of setting MZs, compared to the traditional method of using stable soil variables and relief.

Use of the farmer’s experience variable in the generation of management zones

In the spatial variability management of fields, the approach based on management zones (MZs) divides the area into sub-regions, which have spatially homogeneous topography and soil conditions. Such MZs should lead to the same potential yields. Farmers understand which areas of a field have high and low yields, and use of this knowledge may allow the identification of MZs in a field based on production history. The objective of the present study was to evaluate the application of farmer's experience to determine MZs. The study was conducted in three agricultural fields located in the west of the Paraná State in Brazil, and the MZs were generated considering three cases: a) without the use of the farmer’s experience variable; b) with the variable of farmer’s experience and the stable soil properties selected at the variable selection stage; and c) only with the farmer’s experience variable. The generated MZs were evaluated using the Variance Reduction (VR) index, Fuzziness Performance Index (FPI), Modified Partition Entropy (MPE), Smooth Index (SI), and Analysis of Variance (ANOVA). The study showed that the use of farmer’s experience to set MZs could be an efficient and simple tool, that it could reduce costs for the processes of setting MZs, compared to the traditional method of using stable soil variables and relief.

On the combined effect of soil fertility and topography on tree growth in subtropical forest ecosystems—a study from SE China

Aims The aim of our research was to understand small-scale effects of topography and soil fertility on tree growth in a forest biodiversity and ecosystem functioning (BEF) experiment in subtropical SE China. Methods Geomorphometric terrain analyses were carried out at a spatial resolution of 5×5 m. Soil samples of different depth increments and data on tree height were collected from a total of 566 plots (667 m2 each). The soils were analyzed for carbon (soil organic carbon [SOC]), nitrogen, acidity, cation exchange capacity (CEC), exchangeable cations and base saturation as soil fertility attributes. All plots were classified into geomorphological units. Analyses of variance and linear regressions were applied to all terrain, soil fertility and tree growth attributes. Important Findings In general, young and shallow soils and relatively small differences in stable soil properties suggest that soil erosion has truncated the soils to a large extent over the whole area of the experiment. This explains the concurrently increasing CEC and SOC stocks downslope, in hollows and in valleys. However, colluvial, carbon-rich sediments are missing widely due to the convexity of the footslopes caused by uplift and removal of eroded sediments by adjacent waterways. The results showed that soil fertility is mainly influenced by topography. Monte–Carlo flow accumulation (MCCA), curvature, slope and aspect significantly affected soil fertility. Furthermore, soil fertility was affected by the different geomorphological positions on the experimental sites with ridge and spur positions showing lower exchangeable base cation contents, especially potassium (K), due to leaching. This geomorphological effect of soil fertility is most pronounced in the topsoil and decreases when considering the subsoil down to 50cm depth. Few soil fertility attributes affect tree height after 1–2 years of growth, among which C stocks proved to be most important while pHKCl and CEC only played minor roles. Nevertheless, soil acidity and a high proportion of Al on the exchange complex affected tree height even after only 1–2 years growth. Hence, our study showed that forest nutrition is coupled to a recycling of litter nutrients, and does not only depend on subsequent supply of nutrients from the mineral soil. Besides soil fertility, topography affected tree height. We found that especially MCCA as indicator of water availability affected tree growth at small-scale, as well as aspect. Overall, our synthesis on the interrelation between fertility, topography and tree growth in a subtropical forest ecosystem in SE China showed that topographic heterogeneity lead to ecological gradients across geomorphological positions. In this respect, small-scale soil–plant interactions in a young forest can serve as a driver for the future development of vegetation and biodiversity control on soil fertility. In addition, it shows that terrain attributes should be accounted for in ecological research.

Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

Abstract. Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ, with particular focus on the temporal variability of the spatial patterns of ECa and θ. To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ, and (iii) the ECa–θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ, and the use of EMI-based ECa data with respect to hydrological applications.

Decadal sustainability of spatial distribution of soil properties in a paddy field as a fingerprint reflecting soil-forming factors and field management

Spatiotemporal variations of soil properties were measured in a Japanese paddy field in order to evaluate how they were created and sustained through various field managements. The field was subjected to land consolidation during 1960s, heterogeneous application of manure in the late 1970s and land leveling in 1986, 1987 and 2003. Surface soils were collected from throughout the field in 2002 and 2012, and the physicochemical properties were analyzed. Additional analyses were carried out for relative altitude in 1986, 1999 and 2012, and soil hardness in 2012. In the field examined, the distribution of field attributes reflected past field managements. The heterogeneous distribution of relative altitude was partly explained by the passage of agricultural machinery, whereas the heterogeneous distribution of soil organic matter was partly explained by both past and recent applications of animal dung manure. In general, the measured soil properties were maintained from 2002 to 2012, and the pattern of spatial distribution did not change significantly for many of the properties. The correlation coefficient of the distribution patterns between 2002 and 2012 was highest for yellowness (0.95), followed by sand (0.90), acid-oxalate extractable iron (Fe; 0.88), available phosphorus (P; 0.87), redness (0.82), lightness (0.77), sand-size organic matter (0.74) and total nitrogen (N; 0.72). Land leveling carried out in 2003 barely influenced the distribution of these properties. Among these properties, soil color parameters and sand content can be measured rapidly without reagents and will be useful for characterizing paddy fields according to the distribution of stable soil properties. The analysis of the natural abundance of 15N in soil was also effective to suggest the contribution of the application of animal dung manure to the accumulation of soil organic matter at a within-field scale. It can be concluded, as a general rule, that each paddy field has its own fingerprint which is unveiled by precise soil sampling and analyses of stable properties.

Testing the performance of spatial interpolation techniques for mapping soil properties

In this paper, we implement and compare the accuracy of ordinary kriging, lognormal ordinary kriging, inverse distance weighting (IDW) and splines for interpolating seasonally stable soil properties (pH, electric conductivity and organic matter) that have been demonstrated to affect yield production. The choice of the exponent value for IDW and splines as well as the number of the closest neighbours to include was decided from the root mean squared error (RMSE) statistic, obtained from a cross-validation procedure. Experimental variograms were fitted with the exponential, spherical, Gaussian and linear models using weighted least squares. The model with the smallest residual sum of squares (RSS) was further interrogated to find the number of neighbours that returned the best cross-validation result. Overall, all of the methods gave similar RMSE values. On this experimental field, ordinary kriging performed best for pH in the topsoil and lognormal ordinary kriging gave the best results when applied to electrical conductivity in the topsoil. IDW interpolated subsoil pH with the greatest accuracy and splines surpassed kriging and IDW for interpolating organic matter. In all uses of IDW, the power of one was the best choice, which may due to the low skewness of the soil properties interpolated. In all cases, a value of three was found to be the best power for splines. Lognormal kriging performed well when the dataset had a coefficient of skewness larger than one. No other summary statistics offered insight into the choice of the interpolation procedure or its parameters. We conclude that many parameters would be better identified from the RMSE statistic obtained from cross-validation after an exhaustive testing.

TEMPORAL STABILITY OF SOIL ELECTRICAL CONDUCTIVITY IN IRRIGATED SANDY FIELDS IN COLORADO

The utility of apparent soil electrical conductivity (ECa) remains elusive because of its complex interactions withsoil properties. Nonetheless, a significant interest is emerging to utilize the spatial variability in ECa to guide direct soilsampling and develop varying site-specific management. While the spatial variability of ECa is of significant importance,understanding its temporal variability is equally important. That is particularly true if delineated ECa zones are to be usedto manage agricultural inputs across the field for multiple years. We present multi-year (1998 to 2002) measurements ofshallow (top 0.3 m of soil) and deep (top 0.9 m of soil) ECa from three irrigated sandy fields in eastern Colorado and quantifytheir degree of temporal change. During the study period, the fields were managed uniformly, including all farm operationsand the applied inputs. For each field, soil ECa values were highly correlated between measurement days (for periods of afew days to four years between measurements) with coefficients ranging between 0.71 and 0.92 for shallow and 0.87 and 0.96for deep ECa, but significant deviations from the 1:1 line (indicative of temporal variability) were exhibited by shallow ECa.In these non-saline and sandy fields, delineating spatial patterns of ECa into low, medium, and high zones was highly stableover time, mainly because they reflect the stable soil properties. Grid-by-grid comparison of the low, medium, and high ECapatterns from different measurement days showed mean matching percentages of 87, 74, and 78 for shallow and 93, 85, and89 for deep ECa patterns, respectively, for the three fields. When salt concentration and buildup are low (as was the caseherein), results suggest that single ECa mapping should suffice to delineate stable low, medium, and high ECa zones withouta need for remapping.

Vulnerability of subsoils in Europe to compaction: a preliminary analysis

Identifying the vulnerability of subsoils to compaction damage is an increasingly important issue both in the planning and execution of farming operations and in planning environmental protection measures. Ideally, subsoil vulnerability to compaction should be assessed by direct measurement of soil bearing capacity but currently no direct practical tests are available. Similarly, soil mechanics principles are not suitably far enough advanced to allow extrapolation of likely compaction damage from experimental sites to situations in general. This paper, therefore, proposes a simple classification system for subsoil vulnerability to compaction based for field use on local soil and wetness data at the time of critical trafficking, and, at European level, on related soil and climatic information. Soil data are readily available ‘in Country’ or from the European Soil Database and climatic data are stored in the agrometeorological database of the MARS Project. The vulnerability to compaction is assessed using a two-stage process. First, the inherent susceptibility of the soil to compaction is estimated on the basis of the relatively stable soil properties of texture and packing density. Second, the susceptibility class is then converted into a vulnerability class through consideration of the likely soil moisture status at the time of critical loadings. For use at local level, adjustments are suggested to take account of possible differences in the support strength of the topsoil and specific subsoil structural conditions. The vulnerability classes proposed are based on profile pit observations, on a wide range of soils examined mainly in intensively farmed areas where large-scale field equipment is employed. A map of soil susceptibility to compaction in Europe has been produced, as the first stage in developing a more rigorous quantitative approach to assessing overall vulnerability than has been possible hitherto.

A Comparison of Inverse Distance Weighting and Ordinary Kriging for Characterising within-paddock Spatial Variability of Soil Properties in Western Australia

Site-specific crop management requires matching resource application and agronomic practices with soil and crop requirements, as they vary in space and time within a field. As such, information on the composition of soils at either farm or paddock scale is essential. Soil composition over an entire paddock might not be uniform. For instance, it may not be efficient to fertilise an entire paddock if only the northeast corner show deficiencies. Furthermore, it is not possible to sample every centimetre of the paddock, as this would be a very time consuming and costly procedure. Ideally, we should be able to collect enough sample points so that continuos maps of soil properties can be accurately produced using spatial interpolation techniques, and good judgements can be made about the soil composition of an entire paddock. Two spatial interpolators, namely kriging and inverse distance weighting (IDW) are compared in this paper, evaluating their accuracy in the prediction of seasonally stable soil properties at paddock level. Organic matter content and soil reaction (pH) are the soil properties selected for this investigation, as previous research by Yule et al. (1996) and Brady and Weil (1999) has found these properties to be correlated to cropping potential. The selected spatial interpolators are tested on an existing data set (e.g. 100 soil samples) collected using a stratified random approach over a 60 ha paddock, located in the southwest of Western Australia. The research approach consists of three main steps. Firstly, basic descriptive statistical techniques are applied to identify the presence of outliers. Secondly, selected interpolators are applied to generate continuous maps of the soil properties, and finally the mean root mean square error (RMSE) is used as the validation index, and to select the best spatial interpolator for the soil properties selected. Therefore, for each soil property, every fourth sample is removed from the main data set and put aside to validate the result of the interpolation method. Likewise, the map of uncertainty generated by using the kriging interpolation method is used as an additional source for evaluating the quality of the prediction maps. The RMSE results show IDW to perform slightly better than kriging for pH (e.g. 0.38 vs 0.39) and organic matter (1.25 vs 1.34)

Structures et relations spatiales entre les images aériennes multi-spectrales, les propriétés du sol et les rendements de grandes cultures

Aerial numerical images captured under critical soil conditions and crop stages are promising tools for crop and soil zone management if (1) images reflect the spatial structure of stable soil properties and crop yield potential and (2) spatial scales of variability of soil properties and crop yield potential are manageable. To asses the potential of numeric aerial images to support soil and crop zone management, spatial integration and geostatistical analysis in time and frequency domains of yield, topography, physico-chemical soil properties and aerial multi-spectral images, captured in spring and summer, have been supported for four fields from the Bois-Francs region, in Québec, and 2 years of production. Early summer images predicted monitored yield for experimental sites demonstrating significant spatial structure in crop productivity. Early spring images captured over harrowed soils and numerical elevation models revealed spatial structures of soil physico-chemical properties. Scales of spatial variability are generally compatible with soil and crop zone management.

Canopy tree-soil interactions within temperate forests: effects of soil elemental composition and texture on species distributions

We compared the distribution of adult trees and relatively stable soil properties as part of a study of feedbacks between canopy tree species and soils. In southern New England, soils under Fraxinus americanaL. (FRAM) and Acer rubrum L. (ACRU) had high contents of total CaO and MgO. Under Quercus rubra L. (QURU) and Fagus grandifoliaEhrh. (FAGR), contents of CaO and MgO were low. Sites with Acer saccharumMarsh. (ACSA) and Tsuga canadensis(L.) Carr. (TSCA) varied across a wide range of total CaO and MgO. However, below 0.8% CaO, ACSA was absent and FAGR, QURU, and TSCA were dominant. From 0.8 to 1.5% CaO, ACSA and FRAM increased with increasing CaO content, while the frequency of other species declined. Above 1.5% CaO, there was no relationship between CaO content and ACSA and FRAM abundance, but FAGR and QURU were largely absent. Canopy tree species also varied significantly with texture, which we attribute to the higher Ca and Mg contents of the more sandy soils, rather than to soil physical effects. Correlations between Ca availability and forest composition are well known for calcareous versus noncalcareous soils. Apparently, much subtler variations in supply of mineral nutrients also alter competitive interactions and impose patterning on the distribution of canopy trees within stands. Resume : La distribution d'arbres adultes et les proprietes relativement stables du sol on ete comparees au cours d'une etude des reactions reciproques entre les especes d'arbres de la voute et les sols. Dans le Sud de la Nouvelle-Angleterre, les sols sous Fraxinus americanaL. (FRAM) et Acer rubrum L. (ACRU) contenaient un fort taux de CaO et de MgO total. Sous Quercus rubra L. (QURU) et Fagus grandifolia Ehrh. (FAGR), le contenu en CaO et en MgO etait par contre bas. Les sites avec Acer saccharumMarsh. (ACSA) et Tsuga canadensis(L.) Carr. (TSCA) presentaient une grande variation du CaO et

How good is a reconnaissance soil map for agronomic purposes?

Abstract. Information about the soil fertility status in irrigated ricelands at regional scales (1:50 000–1:250 000) is commonly not contained in classical soil maps. To assess the agronomic suitability of two different reconnaissance soil maps, we conducted a detailed soil survey in the Nueva Ecija province, Philippines. Soil samples were collected from 384 farmers' fields, and soil properties were measured for topsoil and subsoil samples. For most soil properties, a soil map made in 1940 (1:125 000) had within‐map unit variances that were smaller than the total variance, whereas a new soil map of 1992 (1:50 000) did not significantly reduce the within‐class variance. In both soil maps, classification into mapping units accounted for 0–40% of the variance of 14 agronomically important soil properties and large within‐map unit variabilities were found. Underlying strategies of classical soil survey supported the partition of variance for relatively stable soil properties, such as soil texture, CEC, and organic matter. If reconnaissance soil maps are used in quantitative land evaluation studies, existing maps require upgrading by adding quantitative information about relevant soil properties and their within‐map unit variability The sampling demand for upgrading a reconnaissance soil map was large, but pedotransfer functions can be used as cost‐saving tools. Measures of soil nutrient status were highly variable within all mapping units and differences among farmers were much greater than the differences between soil types. Therefore, nutrient management in the study region should be based on individual field or farm recommendations rather than on soil‐map based recommendations.

Factors causing field variation of direct-seeded flooded rice

In 1989 a study was conducted on the variation of soil and plant properties within a race field of the Krasnodar region (Russia). Fairly stable soil properties (pH, soil texture, soil organic matter) had lower coefficients of variation (CV 10–16%) and were normally distributed. In contrast, soil properties that were strongly affected by management had CV's between 29 and 122%. The rice yield within the field ranged from 0.73 to 7.91 t DM ha −1. Factor analysis and multiple linear regression were used as principal techniques to explore the nature of variate interactions that may significantly affect crop-yield patterns and to classify and map the soil fertility status in the field. Five factors (soil fertility status, land preparation, nitrogen fertilizer application, seeding rate, and P-availability) were extracted. Regression models based on these factors explained 75% of the plant density and 56% of the rice yield variation. Soil pH, microrelief, weed growth, and the seeding rate were found to be the major yield factors for rice. A soil fertility map was produced using three fertility classes derived from the extracted soil fertility factor. Soil pH is proposed as a criterion for soil fertility mapping. Co-spatial soil and crop survey and application of multivariate statistics are suggested as suitable methods for exploration of complex soil-crop interactions.