A simple device for sampling of volumetric forest soil cores

Summary

Variation in soil organic carbon and thickness of soil horizons within a boreal forest stand - effect of trees and implications for sampling

Summary

N2O emissions from a cultivated mollisol: optimal time of day for sampling and the role of soil temperature

The correct use of closed field chambers to determine N2O emissions requires defining the time of day that best represents the daily mean N2O flux. A short-term field experiment was carried out on a Mollisol soil, on which annual crops were grown under no-till management in the Pampa Ondulada of Argentina. The N2O emission rates were measured every 3 h for three consecutive days. Fluxes ranged from 62.58 to 145.99 ∝g N-N2O m-2 h-1 (average of five field chambers) and were negatively related (R² = 0.34, p < 0.01) to topsoil temperature (14 - 20 ºC). N2O emission rates measured between 9:00 and 12:00 am presented a high relationship to daily mean N2O flux (R² = 0.87, p < 0.01), showing that, in the study region, sampling in the mornings is preferable for GHG.

Sampling Position under No-Tillage System Affects the Results of Soil Physical Properties

ABSTRACT Understanding the spatial behavior of soil physical properties under no-tillage system (NT) is required for the adoption and maintenance of a sustainable soil management system. The aims of this study were to quantify soil bulk density (BD), porosity in the soil macropore domain (PORp) and in the soil matrix domain (PORm), air capacity in the soil matrix (ACm), field capacity (FC), and soil water storage capacity (FC/TP) in the row (R), interrow (IR), and intermediate position between R and IR (designated IP) in the 0.0-0.10 and 0.10-0.20 m soil layers under NT; and to verify if these soil properties have systematic variation in sampling positions related to rows and interrows of corn. Soil sampling was carried out in transect perpendicular to the corn rows in which 40 sampling points were selected at each position (R, IR, IP) and in each soil layer, obtaining undisturbed samples to determine the aforementioned soil physical properties. The influence of sampling position on systematic variation of soil physical properties was evaluated by spectral analysis. In the 0.0-0.1 m layer, tilling the crop rows at the time of planting led to differences in BD, PORp, ACm, FC and FC/TP only in the R position. In the R position, the FC/TP ratio was considered close to ideal (0.66), indicating good water and air availability at this sampling position. The R position also showed BD values lower than the critical bulk density that restricts root growth, suggesting good soil physical conditions for seed germination and plant establishment. Spectral analysis indicated that there was systematic variation in soil physical properties evaluated in the 0.0-0.1 m layer, except for PORm. These results indicated that the soil physical properties evaluated in the 0.0-0.1 m layer were associated with soil position in the rows and interrows of corn. Thus, proper assessment of soil physical properties under NT must take into consideration the sampling positions and previous location of crop rows and interrows.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

Variograms of ancillary data to aid sampling for soil surveys

To provide reliable estimates for mapping soil properties for precision agriculture requires intensive sampling and costly laboratory analyses. If the spatial structure of ancillary data, such as yield, digital information from aerial photographs, and soil electrical conductivity (EC) measurements, relates to that of soil properties they could be used to guide the sampling intensity for soil surveys. Variograins of permanent soil properties at two study sites on different parent materials were compared with each other and with those for ancillary data. The ranges of spatial dependence identified by the variograms of both sets of properties are of similar orders of magnitude for each study site, Maps of the ancillary data appear to show similar patterns of variation and these seem to relate to those of the permanent properties of the soil. Correlation analysis has confirmed these relations. Maps of kriged estimates from sub-sampled data and the original variograrns showed that the main patterns of variation were preserved when a sampling interval of less than half the average variogram range of ancillary data was used. Digital data from aerial photographs for different years and EC appear to show a more consistent relation with the soil properties than does yield. Aerial photographs, in particular those of bare soil, seem to be the most useful ancillary data and they are often cheaper to obtain than yield and EC data.

Comparing sampling needs for variograms of soil properties computed by the method of moments and residual maximum likelihood

It has been generally accepted that the method of moments (MoM) variogram, which has been widely applied in soil science, requires about 100 sites at an appropriate interval apart to describe the variation adequately. This sample size is often larger than can be afforded for soil surveys of agricultural fields or contaminated sites. Furthermore, it might be a much larger sample size than is needed where the scale of variation is large. A possible alternative in such situations is the residual maximum likelihood (REML) variogram because fewer data appear to be required. The REML method is parametric and is considered reliable where there is trend in the data because it is based on generalized increments that filter trend out and only the covariance parameters are estimated. Previous research has suggested that fewer data are needed to compute a reliable variogram using a maximum likelihood approach such as REML, however, the results can vary according to the nature of the spatial variation. There remain issues to examine: how many fewer data can be used, how should the sampling sites be distributed over the site of interest, and how do different degrees of spatial variation affect the data requirements? The soil of four field sites of different size, physiography, parent material and soil type was sampled intensively, and MoM and REML variograms were calculated for clay content. The data were then sub-sampled to give different sample sizes and distributions of sites and the variograms were computed again. The model parameters for the sets of variograms for each site were used for cross-validation. Predictions based on REML variograms were generally more accurate than those from MoM variograms with fewer than 100 sampling sites. A sample size of around 50 sites at an appropriate distance apart, possibly determined from variograms of ancillary data, appears adequate to compute REML variograms for kriging soil properties for precision agriculture and contaminated sites. (C) 2007 Elsevier B.V. All rights reserved.

Sampling the soil in long-term forest plots: The implications of spatial variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.

Spatial variability of soil penetration resistance influenced by season of sampling

O objetivo deste trabalho foi analizar a distribuição espacial da compactação do solo e a influência da umidade do solo na resistência à penetração. Esta última variável foi descrita pelo índice de cone. O solo estudado foi Nitossolo e os dados de índice de cone foram obtidos usando um penetrômetro. A resistência do solo foi avaliada a 5 profundidades diferentes, 0-10 cm, 10-20 cm, 20-30 cm, 30-40 cm e mais de 40 cm, porém o conteúdo de umidade do solo foi medido a 0-20 cm e 20-40 cm. As condições hídricas do solo variaram nas diferentes amostragems. Os coeficientes de variação para o índice de cone foram 16,5% a 45,8% e os do conteúdo de umidade do solo variaram entre 8,96% e 21,38%. Os resultados sugeriram elevada correlação entre a resistência do solo, estimada pelo índice de cone e a profundidade do solo. Sem embargo, a relação esperada com a umidade do solo não foi apreciada. Observou-se dependência espacial em 31 de 35 séries de dados de índice de cone e umidade do solo. Esta dependência foi ajustada por modelos exponenciais com efeito pepita variável de 0 a 90% o valor do patamar. em séries de dados o comportamento foi aleatório. Portanto, a técnica das distâncias inversas foi utilizada para cartografar a distribuição das variáveis que não tiveram estrutura espacial. Na krigagem constatou-se uma suavização dos mapas comparados com esses das distâncias inversas. A krigagem indicadora foi utilizada para cartografar a variabilidade espacial do índice de cone e recomendar melhor manejo do solo.

Digital soil mapping: evaluation of sampling systems for soil surveys and refinement of soil maps at lower cost using legacy data

In soil surveys, several sampling systems can be used to define the most representative sites for sample collection and description of soil profiles. In recent years, the conditioned Latin hypercube sampling system has gained prominence for soil surveys. In Brazil, most of the soil maps are at small scales and in paper format, which hinders their refinement. The objectives of this work include: (i) to compare two sampling systems by conditioned Latin hypercube to map soil classes and soil properties; (II) to retrieve information from a detailed scale soil map of a pilot watershed for its refinement, comparing two data mining tools, and validation of the new soil map; and (III) to create and validate a soil map of a much larger and similar area from the extrapolation of information extracted from the existing soil map. Two sampling systems were created by conditioned Latin hypercube and by the cost-constrained conditioned Latin hypercube. At each prospection place, soil classification and measurement of the A horizon thickness were performed. Maps were generated and validated for each sampling system, comparing the efficiency of these methods. The conditioned Latin hypercube captured greater variability of soils and properties than the cost-constrained conditioned Latin hypercube, despite the former provided greater difficulty in field work. The conditioned Latin hypercube can capture greater soil variability and the cost-constrained conditioned Latin hypercube presents great potential for use in soil surveys, especially in areas of difficult access. From an existing detailed scale soil map of a pilot watershed, topographical information for each soil class was extracted from a Digital Elevation Model and its derivatives, by two data mining tools. Maps were generated using each tool. The more accurate of these tools was used for extrapolation of soil information for a much larger and similar area and the generated map was validated. It was possible to retrieve the existing soil map information and apply it on a larger area containing similar soil forming factors, at much low financial cost. The KnowledgeMiner tool for data mining, and ArcSIE, used to create the soil map, presented better results and enabled the use of existing soil map to extract soil information and its application in similar larger areas at reduced costs, which is especially important in development countries with limited financial resources for such activities, such as Brazil.

Time stability of soil water storage measured by neutron probe and the effects of calibration procedures in a small watershed

The knowledge of soil water storage (SWS) of soil profiles is crucial for the adoption of vegetation restoration practices. With the aim of identifying representative sites to obtain the mean SWS of a watershed, a time stability analysis of neutron probe evaluations of SWS was performed by the means of relative differences and Spearman rank correlation coefficients. At the same time, the effects of different neutron probe calibration procedures were explored on time stability analysis. mean SWS estimation. and preservation of the spatial variability of SWS. The selected watershed, with deep gullies and undulating slopes which cover an area of 20 ha, is characterized by an Ust-Sandiic Entisol and an Aeolian sandy soil. The dominant vegetation species are bunge needlegrass (Stipa bungeana Trim) and korshinsk peashrub (Carugano Korshinskii kom.). From June 11, 2007 to July 23,2008, SWS of the top1 m soil layer was evaluated for 20 dates, based on neutron probe data of 12 sampling sites. Three calibration procedures were employed: type 1, most complete, with each site having its own linear calibration equation (TrE); type II. with TrE equations extended over the whole field: and type III, with one single linear calibration curve for the whole field (UnE) and also correcting its intercept based on site specific relative difference analysis (RdE) and on linear fitting of data (RcE), both maintaining the same slope. A strong time stability of SWS estimated by TrE equations was identified. Soil particle size and soil organic matter content were recognized as the influencing factors for spatial variability of SWS. Land use influenced neither the spatial variability nor the time stability of SWS. Time stability analysis identified one site to represent the mean SWS of the whole watershed with mean absolute percentage errors of less than 10%, therefore. this site can be used as a predictor for the mean SWS of the watershed. Some equations of type II were found to be unsatisfactory to yield reliable mean SWS values or in preserving the associated soil spatial variability. Hence, it is recommended to be cautious in extending calibration equations to other sites since they might not consider the field variability. For the equations with corrected intercept (type III), which consider the spatial variability of calibration in a different way in relation to TrE, it was found that they can yield satisfactory means and standard deviation of SWS, except for the RdE equations, which largely leveled off the SWS values in the watershed. Correlation analysis showed that the neutron probe calibration was linked to soil bulk density and to organic matter content. Therefore, spatial variability of soil properties should be taken into account during the process of neutron probe calibration. This study provides useful information on the mean SWS observation with a time stable site and on distinct neutron probe calibration procedures, and it should be extended to soil water management studies with neutron probes, e.g., the process of vegetation restoration in wider area and soil types of the Loess Plateau in China. (C) 2009 Elsevier B.V. All rights reserved.

A two-dimensional fuzzy random model of soil pore structure

A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.

Study on the changes of soil chemical characteristics as result of prescribed fire

Every year, particularly during the summer period, the Portuguese forests are devastated by forest fire that destroys their ecosystems. So in order to prevent these forest fires, public and private authorities frequently use methods for the reduction of combustible mass as the prescribed fire and the mechanical vegetation pruning. All of these methods of prevention of forest fires alter the vegetation layer and/or soil [1-2]. This work aimed the study of the variation of some chemical characteristics of soil that suffered prescribed fire. The studied an area was located in the Serra of Cabreira (Figure 1) with 54.6 ha. Twenty sampling points were randomly selected and samples were collected with a shovel before, just after the prescribed fire, and 125 and 196 days after that event. The parameters that were studied were: pH, soil moisture, organic matter and iron, magnesium and potassium total concentration. All the analysis followed International Standard Methodologies. This work allowed to conclude that: a) after the prescribed fire; i) the pH remained practically equal to the the initial value; ii) occurred a slight increase of the average of the organic matter contents and iron total contents; b) at the end of the sampling period compared to the initial values; i) the pH didn´t change significantly; ii) the average of the contents of organic matter decreased; and iii) the average of the total contents of Fe, Mg and K increased.

Impact of prescribed fire on the chemical properties of soil

Prescribed fire is a common forest management tool used in Portugal to reduce the fuel load availability and minimize the occurrence of wildfires. In addition, the use of this technique also causes an impact to ecosystems. In this presentation we propose to illustrate some results of our project in two forest sites, both located in Northwest Portugal, where the effect of prescribed fire on soil properties were recorded during a period of 6 months. Changes in soil moisture, organic matter, soil pH and iron, were examined by Principal Component Analysis multivariate statistics technique in order to determine impact of prescribed fire on these soil properties in these two different types of soils and determine the period of time that these forest soils need to recover to their pre-fire conditions, if they can indeed recover. Although the time allocated to this study does not allow for a widespread conclusion, the data analysis clearly indicates that the pH values are positively correlated with iron values at both sites. In addition, geomorphologic differences between both sampling sites, Gramelas and Anjos, are relevant as the soils’ properties considered have shown different performances in time. The use of prescribed fire produced a lower impact in soils originated from more amended bedrock and therefore with a ticker humus covering (Gramelas) than in more rocky soils with less litter covering (Anjos) after six months after the prescribed fire occurrence.

Evaluación de la degradación del suelo en agroecosistemas del centro-sur de Córdoba mediante indicadores e índices. Assessment of soil degradation in agroecosystems of central-southern Córdoba by means of indicators and indices

Las actividades agropecuarias ejercen diferentes presiones sobre los recursos naturales. Esto ha llevado, en algunas áreas, a un deterioro del suelo que provoca un impacto sobre la sustentabilidad en los sistemas agropecuarios. Para evaluar la degradación del suelo se han propuesto listas de indicadores, sin embargo, se carece de una herramienta metodológica robusta, adaptada a las condiciones edafoclimáticas regionales. Además, existe una demanda de productores e instituciones interesados en orientar acciones para preservar el suelo. El objetivo de este proyecto es evaluar la degradación física, química y biológica de los suelos en agroecosistemas del centro-sur de Córdoba. Por ello se propone desarrollar una herramienta metodológica que consiste en un set de indicadores físicos, químicos y biológicos, con valores umbrales, integrados en índices de degradación, que asistan a los agentes tomadores de decisiones y productores, en la toma de decisiones respecto de la degradación del suelo. El área de trabajo será una región agrícola del centro-sur de Córdoba con más de 100 años de agricultura. La metodología comienza con la caracterización del uso del territorio y sistemas de manejo, su clasificación y la obtención de mapas base de usos y manejos, mediante sensores remotos y encuestas. Se seleccionarán sitios de muestreo mediante una metodología semi-dirigida usando un SIG, asegurando un mínimo de un punto de muestreo por unidad de mapeo. Se elegirán sitios de referencia lo más cercano a una condición natural. Los indicadores a evaluar surgen de listas propuestas en trabajos previos del grupo, seleccionados en base a criterios internacionales y a adecuados a suelos de la región. Se usarán indicadores núcleo y complementarios. Para la obtención de umbrales, se usarán por un lado valores provenientes de la bibliografía y por otro, umbrales generados a partir de la distribución estadística del indicador en suelos de referencia. Para estandarizar cada indicador se definirá una función de transformación. Luego serán ponderarán mediante análisis estadísticos mulivariados e integrados en índices de degradación física, química y biológica, y un índice general de degradación. El abordaje concluirá con el desarrollo de dos instrumentos para la toma de decisiones: uno a escala regional, que consistirá en mapas de degradación en base a unidades cartográficas ambientales, de uso del territorio y de sistemas de manejo y otro a escala predial que informará sobre la degradación del suelo de un lote en particular, en comparación con suelos de referencia. Los actores interesados contarán con herramientas robustas para la toma de decisiones respecto de la degradación del suelo tanto a escala regional como local. Agricultural activities exert different pressures on natural resources. In some areas this has led to soil degradation and has an impact on agricultural sustainability. To assess soil degradation a robust methodological tool, adapted to regional soil and climatic conditions, is lacking. In addition, there is a demand from farmers and institutions interested in direct actions to preserve the soil. The objective of this project is to assess physical, chemical and biological soil degradation in agroecosystems of Córdoba. We propose to develop a tool that consists of a set of physical, chemical and biological indicators, with threshold values, integrated in soil degradation indices. The study area is a region with more than 100 years of agriculture. The methodology begins with the characterization of land use and management systems and the obtaining of base maps by means of remote sensing and survey. Sampling sites will be selected through a semi-directed methodology using GIS, ensuring at least one sampling point by mapping unit. Reference sites will be chosen as close to a natural condition. The proposed indicators emerge from previous works of the group, selected based on international standards and appropriate for the local soils. To obtain the thresholds, we will use, by one side, values from the literature, and by the other, values generated from the statistical distribution of the indicator in the reference soils. To standardize indicators transformation functions will be defined. Indicators will be weighted by mans of multivariate analysis and integrated in soil degradation indices. The approach concluded with the development of two instruments for decision making: a regional scale one, consisting in degradation maps based on environmental, land use and management systems mapping units; and an instrument at a plot level which will report on soil degradation of a particular plot compared to reference soils.