Effect of Savanna windrow wood burning on the spatial variability of soil properties

2021 ◽  
Vol 51 ◽  
Author(s):  
Diogo Neia Eberhardt ◽  
Robélio Leandro Marchão ◽  
Pedro Rodolfo Siqueira Vendrame ◽  
Marc Corbeels ◽  
Osvaldo Guedes Filho ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Spatial Dependence ◽  
Chemical Properties ◽  
Spatial Arrangement ◽  
Nugget Effect ◽  
Tropical Savannas ◽  
Geostatistical Methods ◽  
Exchangeable Ca ◽  
Spherical Models

ABSTRACT Tropical Savannas cover an area of approximately 1.9 billion hectares around the word and are subject to regular fires every 1 to 4 years. This study aimed to evaluate the influence of burning windrow wood from Cerrado (Brazilian Savanna) deforestation on the spatial variability of soil chemical properties, in the field. The data were analysed by using geostatistical methods. The semivariograms for pH(H2O), pH(CaCl2), Ca, Mg and K were calculated according to spherical models, whereas the phosphorus showed a nugget effect. The cross semi-variograms showed correlations between pH(H2O) and pH(CaCl2) with other variables with spatial dependence (exchangeable Ca and Mg and available K). The spatial variability maps for the pH(H2O), pH(CaCl2), Ca, Mg and K concentrations also showed similar patterns of spatial variability, indicating that burning the vegetation after deforestation caused a well-defined spatial arrangement. Even after 20 years of use with agriculture, the spatial distribution of pH(H2O), pH(CaCl2), Ca, Mg and available K was affected by the wood windrow burning that took place during the initial deforestation.

scholarly journals Spatial variability of soil chemical properties after coffee tree removal

2009 ◽  
Vol 33 (5) ◽  
pp. 1507-1514 ◽  
Author(s):  
Sidney Rosa Vieira ◽  
Osvaldo Guedes Filho ◽  
Márcio Koiti Chiba ◽  
Heitor Cantarella
Keyword(s):  
Spatial Variability ◽  
Spatial Dependence ◽  
Crop Yields ◽  
Management Strategies ◽  
Chemical Properties ◽  
Spherical Model ◽  
Soil Chemical Properties ◽  
Kriging Interpolation ◽  
Geostatistical Methods ◽  
Plant Removal

Assessing the spatial variability of soil chemical properties has become an important aspect of soil management strategies with a view to higher crop yields with minimal environmental degradation. This study was carried out at the Centro Experimental of the Instituto Agronomico, in Campinas, São Paulo, Brazil. The aim was to characterize the spatial variability of chemical properties of a Rhodic Hapludox on a recently bulldozer-cleaned area after over 30 years of coffee cultivation. Soil samples were collected in a 20 x 20 m grid with 36 sampling points across a 1 ha area in the layers 0.0-0.2 and 0.2-0.4 m to measure the following chemical properties: pH, organic matter, K+, P, Ca2+, Mg2+, potential acidity, NH4-N, and NO3-N. Descriptive statistics were applied to assess the central tendency and dispersion moments. Geostatistical methods were applied to evaluate and to model the spatial variability of variables by calculating semivariograms and kriging interpolation. Spatial dependence patterns defined by spherical model adjusted semivariograms were made for all cited soil properties. Moderate to strong degrees of spatial dependence were found between 31 and 60 m. It was still possible to map soil spatial variability properties in the layers 0-20 cm and 20-40 cm after plant removal with bulldozers.

scholarly journals Spatial variability of Soil Nutrients Using Geospatial Techniques: A case study in soils of Sanwer Tehsil of Indore district of Madhya Pradesh

2014 ◽  
Vol XL-8 ◽  
pp. 1353-1363 ◽  
Author(s):  
G. S. Tagore ◽  
G. D. Bairagi ◽  
R. Sharma ◽  
P. K. Verma
Keyword(s):  
Spatial Variability ◽  
Soil Nutrients ◽  
Spatial Dependence ◽  
Chemical Properties ◽  
Sampling Strategy ◽  
Spatial Prediction ◽  
Accurate Estimation ◽  
Suitable Alternative ◽  
Available N ◽  
Physico Chemical

A study was conducted to explore the spatial variability of major soil nutrients in a soybean grown region of Malwa plateau. From the study area, one hundred sixty two surface soil samples were collected by a random sampling strategy using GPS. Then soil physico-chemical properties i.e., pH, EC, organic carbon, soil available nutrients (N, P, K, S and Zn) were measured in laboratory. After data normalization, classical and geo-statistical analyses were used to describe soil properties and spatial correlation of soil characteristics. Spatial variability of soil physico-chemical properties was quantified through semi-variogram analysis and the respective surface maps were prepared through ordinary Kriging. Exponential model fits well with experimental semi-variogram of pH, EC, OC, available N, P, K, S and Zn. pH, EC, OC, N, P, and K has displayed moderate spatial dependence whereas S and Zn showed weak spatial dependence. Cross validation of kriged map shows that spatial prediction of soil nutrients using semi-variogram parameters is better than assuming mean of observed value for any un-sampled location. Therefore it is a suitable alternative method for accurate estimation of chemical properties of soil in un-sampled positions as compared to direct measurement which has time and costs concerned.

Application of Inverse Distance Weighting in Mapping Some of Soil Chemical Properties in Ayn Hizam, Qaryat Batth and Taknis

2020 ◽  
Vol 2 (1) ◽  
pp. 1-18
Author(s):  
Mukhtar Mahmud Elaalem ◽  
Younes Daw Ezlit ◽  
Asma Ali Elgmati
Keyword(s):  
Electrical Conductivity ◽  
Spatial Variability ◽  
Soil Ph ◽  
Chemical Properties ◽  
Spatial Prediction ◽  
Ecological Modelling ◽  
Soil Profiles ◽  
Geostatistical Methods ◽  
Gis Environment ◽  
Inverse Distance

Determining variabilities of soil properties is important for ecological modelling, environmental predictions, precise agriculture, and management of natural resources. This study was aimed to examine Inverse distance weight (IDW) to predict the spatial variability of Exchangeable Sodium Percentage (ESP), Calcium Carbonate Percentage (% CaCO3) soil pH, Electrical conductivity and % Gypsum . The study area selected for this work consists of Ayn Hizam, Qaryat- Batth and Taknis. Data for 220 randomly distributed representing soil profiles were encoded in spreadsheets, 198 of them were used for predicting the spatial variability in the GIS environment for ESP, % CaCO3, soil pH, Electrical conductivity and % Gypsum. The rest of Data (i.e. 22 representative soil profiles) were utilized to evaluate the maps produced using Kriging or IDW methods. The results showed that using IDW method was trustable because the values of RMSE and R2 for all the IDW maps were within the acceptable range. The study suggested adopting the Geostatistical methods for studying spatial prediction for different soil proprieties. In addition, the study recommended updating soil data for the study area.

Spatial variability of soil organic carbon in the West Liao River Basin

2018 ◽  
Vol 64 (1-4) ◽  
pp. 25-34
Author(s):  
Yong-hua Zhu ◽  
Sheng Zhang ◽  
Biao Sun ◽  
Xiao-kang Xi ◽  
Yu Liu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spatial Variability ◽  
Soil Depth ◽  
Soil Layer ◽  
Kriging Interpolation ◽  
Spherical Models ◽  
Basin Edge ◽  
Depth Increase

Quantification of the pattern and spatial distribution of soil organic carbon (SOC) is essential to comprehending many eco-hydrological processes. To obtain a better understanding of the spatial variability of SOC in a typical farming-pastoral zone, 270 soil samples were collected at 45 sampling sites from every 20 cm soil layer. Semi-variance function theory and ordinary Kriging interpolation were applied to identify the spatial variability of SOC. The results showed that SOC in the area was relatively low and decreased with depth and from the basin edge to the centre with a measured mean content of 0.07–0.65 g/kg. The strongest variability in the zone in the top soil layer (0–40 cm) was in the centre part of the zone, which was supposed to be the most concentrated area of human activities in the zone. As soil depth increase, the degree of variation of SOC decreased. Gaussian, exponential, and spherical models were suggested to successfully simulate SOC in different soil depth zones. The spatial distribution of SOC showed strong variability in the same soil depth zone, with a nugget to sill ratio of less than 14% and a range of 30–160 km.

scholarly journals Multivariate analysis and geostatistics of the fertility of a humic rhodic hapludox under coffee cultivation

2012 ◽  
Vol 36 (2) ◽  
pp. 467-474 ◽  
Author(s):  
Samuel de Assis Silva ◽  
Julião Soares de Souza Lima
Keyword(s):  
Principal Component Analysis ◽  
Spatial Variability ◽  
Spatial Dependence ◽  
Saturation Index ◽  
Great Influence ◽  
Chemical Properties ◽  
Principal Component ◽  
Component Analysis ◽  
Information Loss ◽  
Coffee Cultivation

The spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 - 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K+, Ca2+, Mg2+, Na+, S, Al3+, pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI), remaining phosphorus (P-rem), and micronutrients (Zn, Fe, Mn, Cu and B). The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characteristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.

scholarly journals Spatial variability of chlorophyll content in a Tifton 85 bermudagrass pasture in a tropical region

2021 ◽  
Vol 29 ◽  
pp. 254-262
Author(s):  
João Luiz Jacintho ◽  
Gabriel Araújo e Silva Ferraz ◽  
Brenon Diennevan Souza Barbosa ◽  
Patrícia Ferreira Ponciano Ferraz ◽  
Sthéfany Airane dos Santos
Keyword(s):  
Spatial Variability ◽  
Chlorophyll Content ◽  
Precision Agriculture ◽  
Spatial Dependence ◽  
Kriging Interpolation ◽  
Tropical Region ◽  
Kriging Method ◽  
Geostatistical Methods ◽  
Production Area ◽  
Best Fit

Precision Agriculture techniques, such as the management of spatial variability of crop attributes, have been studied for several crops. However, few studies have been performed on Tifton 85 bermudagrass. Thus, this work aimed to analyse the spatial variability of chlorophyll content in a Tifton 85 bermudagrass production area, located in Seropédica, Brazil. A georeferenced grid was created to measure the chlorophyll content in two periods using a portable chlorophyll metre. Different geostatistical methods and models were evaluated in order to identify which had the best fit to analyze the spatial dependence of the chlorophyll content.The atribute was mapped based on interpolation by the ordinary kriging method. Therefore, kriging interpolation was used to create isoline maps, which were used to observe the spatial variability of the chlorophyll content. The methodology and maps generated proved to be of great value to the Tifton 85 bermudagrass producers.

Spatial heterogeneity of soil physico-chemical properties in contrasting wetland soils in two agro-ecological zones of Lesotho

Soil Research ◽  
2012 ◽  
Vol 50 (7) ◽  
pp. 579 ◽  
Author(s):  
T. Nkheloane ◽  
A. O. Olaleye ◽  
R. Mating
Keyword(s):  
Spatial Variability ◽  
Spatial Heterogeneity ◽  
Soil Properties ◽  
Spatial Dependence ◽  
Chemical Properties ◽  
Stepwise Multiple Regression ◽  
Available Phosphorus ◽  
Ecological Zones ◽  
Physico Chemical ◽  
Agro Ecological Zones

Wetlands are complex ecosystems, often exhibiting considerable spatial variability, making the understanding of soil spatial relationships within them difficult. A study was conducted to evaluate spatial variability of soil physico-chemical properties in two contrasting wetlands in two agro-ecological zones (AEZs) of Lesotho. Soil samples were collected along two transects in mini-pits dug at different depths at 50-m intervals. The collected samples were analysed for particle size, pH, soil organic carbon (SOC), SOC pool, available phosphorus (Av-P), cation exchange capacity (CEC), and base cations. Results showed that within-site variability was very low for sand particles and pH (coefficient of variation <15% for both properties). Soil physical properties generally showed less spatial heterogeneity than chemical properties, which differed widely within and between the study sites. There was generally low correlation between soil properties, and SOC accounted for most of the variation observed at both sites, especially T’sakholo with partial R2 = 94%; at Thaba-Putsoa, partial R2 = 44%. Geostatistical analysis showed that all of the nugget to sill ratios (NSR) showed strong spatial dependence (i.e. NSR of 54–94%) except SOC (T’sakholo stream-bank) with no spatial dependence, with the nugget accounting for 23.43%. We therefore conclude that further wetland studies in Lesotho should attempt to quantify not only the soil properties or processes under investigation but also their spatial variability, because this spatial variability can provide insight into underlying ecosystem processes and may itself indicate wetland condition. In addition, results of stepwise multiple regression showed that SOC and texture could be used across these sites for the sustainable management of these wetlands.

scholarly journals Spatial variability of soil CO2 emission in different topographic positions

Bragantia ◽  
2010 ◽  
Vol 69 (suppl) ◽  
pp. 19-27 ◽  
Author(s):  
Liziane de Figueiredo Brito ◽  
José Marques Júnior ◽  
Gener Tadeu Pereira ◽  
Newton La Scala Junior
Keyword(s):  
Spatial Variability ◽  
Spatial Dependence ◽  
Co2 Emission ◽  
Mean Value ◽  
Soil Co2 ◽  
Distribution Maps ◽  
Soil Co2 Emission ◽  
Spherical Models ◽  
The Mean ◽  
Topographic Positions

The spatial variability of soil CO2 emission is controlled by several properties related to the production and transport of CO2 inside the soil. Considering that soil properties are also influenced by topography, the objective of this work was to investigate the spatial variability of soil CO2 emission in three different topographic positions in an area cultivated with sugarcane, just after mechanical harvest. One location was selected on a concave-shaped form and two others on linear-shaped form (in back-slope and foot-slope). Three grids were installed, one in each location, containing 69 points and measuring 90 x 90 m each. The spatial variability of soil CO2 emission was characterized by means of semivariance. Spatial variability models derived from soil CO2 emission were exponential in the concave location while spherical models fitted better in the linear shaped areas. The degree of spatial dependence was moderate in all cases and the range of spatial dependence for the CO2 emission in the concave area was 44.5 m, higher than the mean value obtained for the linear shaped areas (20.65 m). The spatial distribution maps of soil CO2 emission indicate a higher discontinuity of emission in the linear form when compared to the concave form.

scholarly journals Spatial and temporal variability of Eh and pH over a rice field as related to lime addition

Bragantia ◽  
2010 ◽  
Vol 69 (suppl) ◽  
pp. 67-76 ◽  
Author(s):  
Luis Alberto Morales ◽  
Jorge Paz-Ferreiro ◽  
Sidney Rosa Vieira ◽  
Eva Vidal Vázquez
Keyword(s):  
Spatial Variability ◽  
Soil Ph ◽  
Spatial Dependence ◽  
Temporal Stability ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Data Sets ◽  
Contour Maps ◽  
Semivariogram Analysis ◽  
Spherical Models

The aim of this study was to describe the effect of lime additions on the spatial variability of pH and Eh in a typic Plintacualf cultivated with rice, in Corrientes, Argentina. The 5.1 ha field was divided in three sub plots at which dolomitic lime additions were made at the rates zero, 625 kg ha-1 and 1250 kg ha-1. The soil was sampled at three stages: before sowing thus in aerobic conditions, and then two more times in anaerobiosis. Ninety-six samples per sub plot were taken on each of the three sampling stages on a grid of 11.9 x 20 m. Soil pH and Eh were measured by routine methods. The pH values increased, whereas Eh values decreased, following flooding. The coefficients of variation for pH was rather low during all the three studied periods. Conversely, the CV values for Eh were initially low but with a sharp increased in the second sampling date. The spatial variability of the studied soil properties was assessed using semivariogram analysis and examination of the maps constructed with values interpolated with kriging. Soil pH exhibited a rather strong spatial dependence, whereas soil Eh had a strong to moderate spatial dependence all over the three studied periods and for the three lime rates. Spherical models reaching a stable sill with low to moderate nugget effect were fitted to the experimental semivariograms for the 18 data sets (3 subplots, 3 liming rates and 2 properties) studied. Spatial variability of pH and Eh on rice fields was far from negligible both on aerobic and on anaerobic conditions. In general pH exhibited a stronger spatial dependence than Eh and also showed a tendency to present smaller ranges of spatial dependence. Contour maps clearly showed the presence of small scale variability for pH and Eh within each liming treatment and during each of the three sampling dates. Neither pH or Eh had temporal stability of the pattern of spatial distribution on field studied.

Spatial variability of some chemical properties of a Cambisol soil with cocoa (Theobroma cacao L.) cultivation

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Sergio Salgado García ◽  
Joana Acopa Colorado ◽  
Sergio Salgado-Velázquez ◽  
Samuel Córdova Sánchez ◽  
David Palma López ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Soil Properties ◽  
Spatial Dependence ◽  
Chemical Properties ◽  
Kriging Interpolation ◽  
Management Zones ◽  
Agronomic Management ◽  
Management Area ◽  
Theobroma Cacao L ◽  
Exchangeable P

Objective: To evaluate the spatial variability of some chemical properties of a Cambisolsoil, in order to establish specific agronomic management zones for cocoa cultivation.Methodology: A sampling of 42 georeferenced points equidistant at 40 m was carriedout. Geostatistical variability maps were made with the results of the chemical analysisof the soil properties, using the ordinary Kriging interpolation technique.Results: It was found that the percentage of saturation of acidity (PSA), acidity and H+showed high variability; P-Olsen and interchangeable K, Ca and Mg displayed mediumvariability, and pH, MO, CIC and Al presented low variability. Soil properties pH, PSA;Exchangeable P-Olsen, Ca and Mg showed high spatial dependence (&lt;25%) and OM,exchangeable K and CIC moderate spatial dependence (25-75%).Study limitations / Implications: The generated maps allowed the identification ofpartial areas with different variability, as well as the direction of greatest variability of theproperty as a function of distance.Conclusions: With the maps, it was possible to make recommendations for agronomicmanagement depending on each specific management area.

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