Pure Nugget Effect Research Articles

Spatio-temporal analysis of the red ring pathosystem in Oil palm in the Eastern Amazon

The objective was to evaluate the spatial and temporal distribution of the Red Ring and R. Palmarum in conventional oil palm plantation in the municipality of Thailand, state of Pará, in the production area of the AGROPAR Farm, belonging to the AGROPALMA SA Company, through of data obtained monthly from a Historical series from 2014 to 2018, using Geostatistics as a tool. To evaluate the dispersion of the Red Ring and R. Palmarum, sequential sampling was used. In this way, semivariograms were generated and the theoretical models were tested: Spherical, Gaussian, exponential and linear (pure nugget effect). The obtained semivariograms were submitted to the Krigagem estimator to make the dispersion maps of the Patosystem. Through the semivariograms it was observed that the model that best fit the spatial distribution of the red ring was the Gaussian, with range values for the experimental area ranging from 690 m to 870 m. As for the distribution of R. Palmarum, the models that best fit were the spherical and exponential, with values ranging from 860 m to 4990 m and that the R. palmarum infestation is preferably located on the periphery of the courts.

Spatial correlation of soybean yield with the chemical attributes of an Oxisol

Soybean is currently the most cultivated oilseed in the world. The objective of this study was to analyze the chemical attributes of Oxisol correlated with soybean productivity. The attributes evaluated were grain productivity, soil properties of organic matter contents, phosphorous, pH, potassium, calcium, magnesium, hydrogen + aluminum, aluminum, sum of bases, cation exchange capacity (CEC), base saturation, liming requirement; penetration resistance at 0.0-0.10 m, 0.10-0.20 m, 0.20-0.30 m, and 0.30-0.40 m. Soil chemical attributes were submitted to a descriptive classic analysis with the help of the RBio software. In the semivariogram analysis, the attributes calcium, magnesium, aluminum, sum of bases, base saturation, liming requirement, and penetration resistance at 0.30-0.40 m showed a pure nugget effect, meaning no spatial dependence. In conclusion, CEC was the attribute that best described the soybean yield data in dystrophic Red Latosols. Attributes of grain productivity, soil organic matter, phosphorus, pH, potassium, hydrogen + aluminum, CEC, penetration resistance at 0.00 to 0.30 m showed spatial dependence.

Analysis on the Characteristics and Geological Significance of Variation Function in Mineral Geological Modeling

Variation function is a basic tool used in geostatistics. Modern geostatistics using variation function as a tool for the result of the qualitative geology to quantitative geology development. Variation function has not only been widely used in the calculation of modern geological and mineral resources reserves, but also extended to the description of environmental pollution and the spatial migration of elementions. Variogram is a set of deterministic and statistical theoretical tools for understanding and simulating spatial variables. Taking the variogram as a tool which is in the most commonly used in modern geostatistics, the variogram model can be divided into three categories according to the value of the base station or not, the first is the base-station value, which is divided into spherical model, exponential model, Gauss model and pure nugget effect model; The second is the base-free model, which is divided into linear model, power function model, logarithmic function model and cubic model, and the third is hole effect model. Based on the modern geostatistics is most commonly used for variational function tool, analyses the spatial structure change and the variational function of geological body composition variables between the mathematical characteristics, types and its related geological significance, combined with solid mineral, oil and gas resources in the field of practical application examples of analysis of the variation function application problems of stability, etc, and gives his own understanding. It is considered that variation function is a meaningful tool for geological quantitative analysis and visual display of composition in the modeling of mineral geological features when the data amount meets certain sufficient conditions and the research object is applied.

Spatial characterization of factors inherent in the microendemism of the dwarf pequi tree (Caryocar brasiliense subsp. intermedium (Wittm.) PRANCE & M. F. Silva)

The dwarf pequi tree, Caryocar brasiliense subsp. intermedium, is extremely restricted to ecological niches in the Cerrado biome. Thus, understanding the conditioning factors of the micro-endemism of this sub-species through its spatial distribution and the physical-chemical attributes of the soil was the objective of this research. The research was carried out in a fragment of rupestrian field. The area was divided into quadrants in which the number of pequi trees was quantified and the physicochemical characteristics of the soil were determined. The modeling of semivariograms was performed using semivariances, and ordinary kriging was used for spatial interpolation of variables with spatial dependence. The number of pequi trees, the altitude, the remaining phosphorus and the humidity showed a strong degree of spatial dependence, unlike the pH, the calcium and the magnesium, all of which had a pure nugget effect. The other variables showed a moderate degree of spatial dependence. The greater availability of bases (SB > 0.1 cmolc dm-3) and phosphorus (> 1.05 mg dm-3), the reduced percentage of moisture (< 5%) and low potential acidity (< 4.0 cmolc dm-3) were the factors positively related to the establishment and development of the dwarf pequi tree in the area.

Evaluation and Spatial Variability of Cryogenic Soil Properties (Yamal-Nenets Autonomous District, Russia)

Agricultural development in northern polar areas has potential as a result of global warming. Such expansion requires modern soil surveys and large-scale maps. In this study, the abandoned arable experimental field founded by I.G. Eichfeld one century ago in Salekhard city (Russian Arctic), located in the polar circle, was investigated. Our aims were to assess the nutritional soil properties and their spatial variability. For spatial assessment and mapping, ordinary kriging (OK) and inverse distance-weighted (IDW) methods were employed. We found that due to long-term agriculture use, the soil cover was represented by a unique Plaggic Podzol (Turbic) that is not typical of the region. The soil was characterized by relatively low soil organic carbon (SOC) content, high acidity and a high content of plant-available forms of phosphorus in the humus-accumulative horizon. The results showed that some properties (pH H2O, pH CaCl2) were characterized by large-scale heterogeneity and showed clear spatial dependence. However, some properties (ammonium and nitrate nitrogen, basal respiration) showed a pure-nugget effect, presumably due to experimentation with fertilizer over a long period of time.

Relações de escala de artrópodes do solo e a estrutura da vegetação de fitofisionomias de Cerrado

ABSTRACT The objective of this study was to assess the scale relationships of soil arthropods and the vegetation structure of Cerrado phytophysiognomies. The experimental plots were set in areas with dense Cerrado (T1), typical Cerrado (T2), and sparse Cerrado (T3). The edaphic fauna was collected at 128 points through pitfall traps, and the vegetation was evaluated in subplots of 9 m2. The data were evaluated using descriptive statistics, geostatistics, multifractal analysis, and joint multifractal analysis. The soil arthropods and vegetation structure were adjusted to a geostatistical model, except for arborescent plants (T1) and arthropod abundance and arboreal plants (T2), which showed a pure nugget effect. The studied variables showed different degrees of multifractality. The graphs of joint multifractal dimension showed circular lines with high values of joint correlation for the pairs of arthropod richness versus the abundance of plant strata (r = -0.498), arthropod richness versus herbaceous plants (r = 0.323), and arthropod richness versus arboreal plants (r = 0.451) at T1. The soil fauna was influenced by the composition of the plant strata. The plots with dense Cerrado (T1) and sparse Cerrado (T3) showed the greatest spatial dependence between the samples. The multifractal analysis showed that the plot with sparse Cerrado (T3) had the greatest heterogeneity of measurement along the geometric support. In contrast, the greatest asymmetry of the singularity spectrum was described for the plot with dense Cerrado (T1). The use of geostatistical and multifractal analysis tools enabled us to characterize the scale relationships between the variables.

Mechanical sowing alters slope-scale spatial variability of saturated hydraulic conductivity in the black soil region of Northeast China

Saturated hydraulic conductivity (Ks) and its spatial variability are essential for the simulation of water and solute transport in the vadose zone. Mechanical operations have been increasingly employed in agricultural systems during recent decades to improve crop establishment, but their impact on Ks spatial variability has rarely been evaluated. The objectives were to characterize the slope-scale variability of Ks and to identify the primary controls dominating Ks distributions before and after mechanical sowing. Along a 900 m slope transect in the black soil region of Northeast China, soil samples were collected in an interval of 20 m, and Ks, bulk density (BD), particle-size distribution, wet-aggregate stability (WAS), soil organic carbon content (SOC) and land surface roughness (SR) were investigated before and after mechanical sowing in the spring. The results show that sowing significantly decreased Ks along the transect (p < 0.01). Partly due to the strong comparisons among three different sections with respect to soil erosion, i.e., original, erosive and deposited sections, large Ks spatial variability was detected both before and after sowing. According to the semivariogram analysis, nevertheless, sowing decreased the semivariances of Ks overall and altered its spatial structure, i.e., from an exponential semivariogram possessing a sill of 0.72 mm2 min−2 and exhibiting a moderate spatial dependency before sowing to a pure nugget effect value of 0.27 mm2 min−2 corresponding to random distribution after sowing. Using the state-space approach, BD, CLAY and SR were identified as the main factors regulating Ks spatial distributions, whether before or after sowing. These findings demonstrate the remarkable impact of mechanical sowing on Ks and its spatial variability, and hold important implications for hydrological modeling and agricultural management in the black soil region of Northeast China.

Spatial Distribution of Tibraca limbativentris (Heteroptera: Pentatomidae) in Babassou Palms

The babassou plant (Attalea speciosa Mart. Ex. Spreng, Arecaceae) is an important palm tree in the state of Maranhão, northeastern Brazil. This plant is the main arboreal component in extensive geographical areas including agricultural areas. However, limited research studies exist on its role as an alternative pest host in this region. This study investigated the occurrence of Tibraca limbativentris Stal (1860) in young babassou palm trees, the effect of abiotic factors (temperature, solar radiation and rainfall) on the number of T. limbativentris adults and postures, and this insect’s spatial arrangement during the rice crop off-season. The research team inspected young babassou plants on a monthly basis in 2012 and 2013 to collect and quantify postures and adults. They collected a total of 1418 live adults, 13 dead and ten postures of T. limbativentris. There was a significant difference between the first and the other collections of live adults carried out in 2012 and 2013. Abiotic factors including rainfall, temperature and solar radiation, had no influence on the number of adults (alive and dead) and postures. The semivariogram adjusted to the Gaussian model showed that in 2013, the spatial distribution of living adults, that had an aggregate pattern, was highly dependent on the season. However, in 2012 there was a pure nugget effect. These results imply that young babassou plants are alternative T. limbativentris hosts.

Linear and spatial variability of eucalyptus dendrometric attributes correlated with the properties of a Typic Haplustox soil (Oxisol) in the Brazilian savannah

Effects of soil attributes using the geostatistical tool improves the interpretation of specific soil management. Thus, this study aimed to evaluate the physical, chemical, and microbiological properties of a Typical Haplustox (Oxisol), identifying those with the best linear and spatial correlation with eucalyptus (Eucalyptus spp.) vegetative growth. The experiment was conducted at the Teaching, Research, and Extension Farm (FEPE) of the Universidade Estadual Paulista (UNESP), Campus of Ilha Solteira. Thirty-five points spaced 13 meters apart were demarcated for analysis, which were distributed in 5 rows of 7 points each. From each point, 2 soil samples were collected from the 0-10 cm depth layer. The physical, chemical, and microbiological soil properties evaluated were: sand, silt, and clay contents; penetration resistance (PR), gravimetric moisture (GM), real density (RD), microbial biomass carbon (MBC), respirometry (CO2-C), metabolic quotient (qCO2), organic matter content (OM), and hydrogenionic potential (pH). The eucalyptus attributes assessed were: plant height (PH) and circumference at breast height (CBH). Each attribute was analyzed by descriptive statistics using the SAS software. Data frequency distribution was verified by the Shapiro Wilk method, and geospatial changes were analyzed by the GS+ software. The soil property that best explained the variability in eucalyptus dendrometric attributes was real density (RD). Except for RD, all properties did not show spatial dependence (i.e., pure nugget effect), which significantly represents eucalyptus vegetative performance.

SPATIAL VARIABILITY OF RESISTANCE TO PENETRATION IN SOIL UNDER SUGARCANE CROPS WITH DIFFERENT HARVEST METHODS

ABSTRACT The objective of this work was to evaluate the spatial variability of resistance to penetration in soil under sugarcane crops subjected to different harvest methods in the North Coast microregion of the state of Paraiba, Brazil. The study was conducted in a Typic Hapludult under sugarcane crops, at the farms Santa Emília-II and Maria da Luz-I of the company Miriri Food and Bioenergy S/A, in the municipalities of Rio Tinto and Capim, respectively, state of Paraíba, Brazil. Three sugarcane areas with different harvest methods (manual, mechanized, and manual/mechanized) were selected. The sampling was done in plots of 100 × 100 m, using a grid of 20 × 20 m, covering planting rows and interrows; each intersection point of the grid was georeferenced, and the soil mechanic resistance to penetration was evaluated with the aid of an impact penetrometer (IAA/Planalsucar-Stolf) up to the depth of 0-0.6 m. Soil disturbed and undisturbed samples from the 0.0-0.1 and 0.1-0.2 m layers were collected for analyses of soil moisture, texture, clay dispersed in water, flocculation degree. A pure nugget effect was found in the 0.0-0.1 and 0.4-0.5 m soil layers in the rows of the areas with manual/mechanized harvest. The spherical model was found for most conditions evaluated. The results for the areas were similar, with amplitude of 25-49 m, indicating that the harvest management had no effect on the soil resistance to penetration. No compacted areas were found, and the spatial dependency of the resistance to penetration was characterized as moderate to strong.

Mapping impact of intense rainfall on a high-severity burned area using principal component analysis

High-severity wildfires have a major impact on soil properties. Moreover, recently burned areas are highly sensitive to intense rainfall events. However, little is known about the impact of extreme rainfall on the relationship between soil properties and their spatial distribution. The objective of this study is to examine the effects of an intense rainfall event on soil properties and their spatial distribution in a small area using principal component analysis (PCA). The variables studied were aggregate stability (AS), total nitrogen (TN), soil organic matter (SOM), inorganic carbon (IC), C/N ratio, calcium carbonates (CaCO3), pH, electrical conductivity (EC), available phosphorus (P), extractable calcium (Ca), extractable magnesium (Mg), extractable sodium (Na) and extractable potassium (K). Each PCA (before and after intense rainfall event) allowed us to extract five factors. Factor 1 in the pre-intense rainfall event PCA explained the variance of EC, available P, extractable Mg and K; factor 2 accounted for TN, SOM (high loadings), IC and CaCO3 (low loadings); factor 3 explained AS, extractable Ca and Na; and, factors 4 and 5 accounted for C/N and pH, respectively. Factor 1 in the after intense rainfall event PCA explained the variance of TN, SOM, EC, available P, extractable Mg and K (high loadings) and pH (low loading); factor 2 accounted for IC and CaCO3; factor 3 explained extractable Ca and Na; factor 4 accounted for AS; and, factor 5 for C/N. The results showed that the intense rainfall event changed the relationship between the variables, strengthening the correlation between them, especially in the case of TN, SOM, EC, available P, extractable Mg and extractable Ca with AS. In the case of the pre-intense rainfall event PCA, the best- fit variogram models were: factors 1 and 2 – the linear model; factors 3 and 4 – the pure nugget effect; and, factor 5 – the spherical model. In the case of the factors after intense rainfall event PCA, with the exception of factor 5 (spherical model), the best fit model was the linear model. The PCA score maps illustrated a marked change in the spatial distribution of the variables before and after the intense rainfall event. Important differences were detected in AS, pH, C/N IC, CaCO3, extractable Ca and Na.

Nonlinear disjunctive kriging for the estimating and modeling of a vein copper deposit

Estimation of mineral resources and reserves with low values of error is essential in mineral exploration. The aim of this study is to estimate and model a vein type deposit using disjunctive kriging method. Disjunctive Kriging (DK) as an appropriate nonlinear estimation method has been used for estimation of Cu values. For estimation of Cu values and modeling of the distribution of Cu in Chelkureh, samples have been taken from 48 drill holes in Chelkureh, and the values of Cu have been analyzed. Resulting data from analyzing Cu values were converted to standard normal values using Hermite polynomials. Variography has been done in the Chelkureh deposit. After studying variograms in different directions, it was found out that the ore deposit has a mild anisotropy. The best-fitted variogram model was considered for disjunctive kriging estimation. The model consists of a pure nugget effect with 0.46 amplitude plus a spherical scheme with sill 1.20 and range 140 m. Consequently, a three-dimensional model of estimated value and error estimated value was provided by disjunctive kriging to divide the ore into an economic and uneconomic part. The models based on the estimate of the DK method in the study area exhibited an increasing trend of concentration from the center to North. Finally, validation between the disjunctive kriging carried out by using cross-validation. The result showed that the correlation of estimated values and real values was strong (63.4%).

Development of HUMGEOSTAT: A New Geological Tool for Geostatistical Analysis of Mineral Deposit: A Case Study at Sin Quyen Mine (Northern Vietnam)

ABSTRACT This paper presents the results of the design and implementation of a new geological tool, named as HUMGEOSTAT, for advanced geostatistical analysis of mineral deposit, a case study at the Sin Quyen, one of the important mines for the Vietnam mining industry in Vietnam. The tool is developed based on the Stanford Geostatistical Modeling Software (SgeMS) platform, which is an open-source computer package for solving problems involving spatially related variables. The tool is capable of supporting users in reducing uncertainty and improving the quality of mining exploration tasks. The tool has all the functions needed to solve a complete geostatistical issues i.e. Variogram models (such as Spherical, Exponential, Gausian, Linear and Pure nugget effect); and four commonly used Kriging methods (Ordinary Kriging, Simple Kriging, Indicator Kriging, Co-Kriging). The tool was applied to test various types of input data and particularly for complex copper ore bodies of Sin Quyen mine. The results of analysis of orebody spatial structure has found that Cu content has non-uniform change, regional anisotropy in north-south (0±22.5°) direction, and anisotropic index is around 1.3. The mineral reserves are estimated according to sub-blocks and points in the orebody-space. The results indicate that the Ordinary Kriging (OK) has reliable results, variance estimation is small; the predicted result gained from OK have strong correlation (K=0.905) with ore samples. HUMGEOSTAT was applied at the Sin Quyen mine and various coal mines, the results were adapted with reality of mines.

Within-field variability and spatial analysis of white mould and soybean crop attributes in southern Brazil

White mould (Sclerotinia sclerotiorum) is a damaging disease of soybean crops in Brazil. Within-field spatial analyses of white mould disease and inoculum, as well as yield components at the field level may provide insights into their relationship, but this information is lacking in the country. During three years, spatially explicit within-field data on white mould and soybean stand and yield were measured at three fields, with sizes ranging from 4 to 12 ha, located in the Campos Gerais region of Parana State, Brazil and all naturally infested with sclerotia. Crop stand, white mould incidence and severity, soybean yield and sclerotia collected at harvest were assessed in quadrats of 7.2 m2 distant from each other by 8 to 50 m. Soilborne sclerotia were counted in four quadrats (0.25 m2 and 0.05 m depth) at each sampling point. The semivariograms fitted the pure nugget effect, linear, spherical, and exponential models. The pure nugget model best fitted sclerotia data, suggesting a random distribution. Significant and positive associations were found between disease incidence and sclerotia amount at harvest, which were both negative associated with yield.

Spatial and temporal variability of the soil microbiological properties in two soils with a different pedogenesis cropped to winter rape (Brassica napus L.)

Understanding the spatio-temporal variability of the microbial properties in soil with a different pedogenesis is crucial in evaluating their structure-function relationship and their influence on the functions of an ecosystem. The aims of the study were to determine the spatio-temporal variations in the selected microbial properties at the surface horizon in a conventionally managed arable field. The area selected for the research, which was mainly covered with typical Luvisols and Phaeozems, was a uniformly managed system that was considered to be homogenous in relation to texture. Winter rape was cultivated after winter wheat as the forecrop. A grid soil sampling (10 m × 10 m) was used to assess the spatial heterogeneity of the soil properties across a 0.4 ha field. Soil samples were collected from the upper 20 cm of both soils at 50 points in April and August 2008. The colony-forming units (CFUs) of bacteria, fungi and actinomycetes, soil basal respiration (BR), microbial biomass carbon (CMIC) as well as enzymatic activity were analyzed. The data were evaluated using classical statistical and geostatistical methods. In both soils, fungal CFUs were significantly lower than the bacterial CFUs with a B/F (bacteria/fungi) ratio of 68.4 in the Luvisols and 192.4 in the Phaeozems, while CFUs of the actinomycetes was similar in both soil types. Most of the studied properties were significantly higher in April than in August, while there was an opposite trend for dehydrogenase activity (DHA). In turn, fluorescein diacetate hydrolysis (FDAH) and CMIC did not show significant differences between the sampling months. Only some of the microbial properties had a significant spatial autocorrelation (Moran's I) and these were spatially dependent at the scale of the sampling grid. Most of the spatially correlated properties were in moderate and strong variability class, while the fungal CFUs in Luvisols (April), Phaeosems (August) and FDAH in Phaeosems (April) were in the weak variability class (a nugget effect >75%). Only the bacterial CFUs in Luvisols had a pure nugget effect. Most of the microbial-related properties did not exhibit a spatial structure at the examined scale, thus suggesting that changes in these properties would be detectable at a distance shorter than ten meters. More frequent seasonal sampling must be included in the sampling strategy in order to better understand whether the studied properties have any permanent spatial patterns in soil over time or whether they are more randomized.

SPATIAL CONTINUITY OF ELECTRICAL CONDUCTIVITY, SOIL WATER CONTENT AND TEXTURE ON A CULTIVATED AREA WITH CANE SUGAR

ABSTRACT Spatial variability of soil attributes affects crop development. Thus, information on its variability assists in soil and plant integrated management systems. The objective of this study was to assess the spatial variability of the soil apparent electrical conductivity (ECa), electrical conductivity of the saturation extract (ECse), water content in the soil (θ) and soil texture (clay, silt and sand) of a sugarcane crop area in the State of Pernambuco, Brazil. The study area had about 6.5 ha and its soil was classified as orthic Humiluvic Spodosol. Ninety soil samples were randomly collected and evaluated. The attributes assessed were soil apparent electrical conductivity (ECa) measured by electromagnetic induction with vertical dipole (ECa-V) in the soil layer 0.0.4 and horizontal dipole (ECa-H) in the soil layer 0.0-1.5 m; and ECse, θ and texture in the soil layers 0.0-0.2 m and 0.2-0.4 m. Spatial variability of the ECa was affected by the area relief, and had no direct correlation with the electrical conductivity of the saturation extract (ECse). The results showed overestimated mean frequency distribution, with means distant from the mode and median. The area relief affected the spatial variability maps of ECa-V, ECa-H, ECse and θ, however, the correlation matrix did not show a well-defined cause-and-effect relationship. Spatial variability of texture attributes (clay, site and sand) was high, presenting pure nugget effect.

Spatial Variability of Soil Fauna Under Different Land Use and Managements

Geostatistics allows the evaluation of the distribution pattern of data with high spatial variability in agricultural systems. This study aimed to evaluate the spatial variability of biological diversity indices of soil fauna under different land (agriculture and forest). Samples were collected in seven areas (millet, soybean, corn, eucalyptus, pasture crops, and preserved and disturbed Cerrado), in Maranhão state, Brazil. The soil fauna was caught trapped in pitfall traps, installed 3 m away from each other. In each area, 130 traps were maintained for seven days. After this period, they were removed and their content transferred to bottles and taken to the laboratory, where the insects were screened and identified at the level of orders and families. Eight indices were calculated, namely: individuals trap-1 day-1, Jackknife richness estimator, the Simpson, McIntosh, Shannon, and total diversity, and Simpson dominance, and Pielou equitability indices. The spatial variability was derived from the semivariograms fitted to Gaussian, spherical, and exponential geostatistical models. Statistical analysis showed medium values of the coefficient of variation for millet, except for the indices individuals trap-1 day-1 and McIntosh diversity, which were considered high. The values of the correlation matrix were negative for some indices, suggesting an inverse relationship. For millet, corn, eucalyptus, disturbed Cerrado, and pasture areas, the Shannon diversity index exhibited a pure nugget effect. For the areas of millet, corn, disturbed Cerrado and pasture, the total diversity index was adjusted to the Gaussian model. The degree of spatial dependence was considered high for the individuals trap-1 day-1 and Pielou equitability indices for millet. Only for soybean and pasture similarity in the scaled semivariograms was observed for the spatial variability of the indices, indicating similarity of performance. Soil management and land use affect the patterns of soil fauna abundance, richness, and diversity. The presence of groups such as Araneae, Diplura, and Poduromorpha are related to ecological equilibrium, quality, and sustainability of the agricultural systems studied.

Spatial variability of soil attributes in an experimental basin in the semi-arid region of Pernambuco, Brazil

ABSTRACT This study aimed to evaluate the spatial patterns of physical and chemical properties of a soil in an experimental basin with an area of 149 km2, located in the municipality of Pesqueira, in the semi-arid region of Pernambuco state (Brazil). Samples were taken in the layers of 0-0.10 and 0.10-0.20 m, at 35 monitoring points distributed in an irregular grid, encompassing the three soil classes present in the basin and commonly found in the semi-arid region. For the attributes of soil texture, organic carbon and bulk density in the layer of 0.10-0.20 m, spatial dependence from medium to strong was detected, ranging from 0.03 to 49.98%. Bulk density in the layer 0-0.10 m, as well as the electrical conductivity, in both layers, showed pure nugget effect, possibly due to insufficient sampling distance to capture spatial dependence. However, geostatistics represented well the spatial dynamics of soil attributes at points where the mapping is possible.

Geostatistical characterization of fruit damage caused by Anarsia lineatella (Lepidoptera: Gelechiidae) in organic fruit orchards and implications for its management

ABSTRACTThe peach twig borer Anarsia lineatella is the most common pest threat of peaches worldwide. This work studies for the first time, the fruit damage patterns inside organic peach orchards using geostatistical methods. A linear semivariogram model provides the best fit among candidates’ linear and non-linear models based on the RSS and r2. Moreover, the shape of the linear model approaches the pure nugget effect model, with a very low correlation between samples regardless of the distance of separation. This suggests either that the caused damage is to a high degree randomly or uniformly distributed, or, that autocorrelation may be present in distance lower than the measured distance of the study orchards. The linear model has been used for Kriging interpolation to simulate the spatial distribution of fruit damage and to indicate hot spots of high pest activity. According to the linear interpolation model, the simulated percentage of damage ranged from 12% to 28% during an observation period of three years. Moreover, slight border effects were observed during the first two years of observation suggesting possible entry of individuals from nearby orchards.

SPATIALIZATION OF FRACTIONS OF ORGANIC MATTER IN SOIL IN AN AGROFORESTRY SYSTEM IN THE ATLANTIC FOREST, BRAZIL

ABSTRACT This study aimed to spatialize fractions of organic matter of soil in an agroforestry system (AFS) located in the Atlantic Forest in Brazil. Thirty-one soil samples were collected at depths of 0-10, 10-20 and 20-40 cm from georeferenced collection points. We determined total organic carbon (TOC), particulate carbon (COp), carbon associated with clay and silt (COam), carbon content in the fulvic acid fraction (C-FAF), humic acid fraction (C-HAF) and humin fraction (C-HUM). Semivariogram analysis and model adjustment were carried out using ArcGIS 10.2 software. Subsequently, spatial interpolation was performed using Ordinary Kriging. We observed spatial dependence for all variables except for TOC and COp at the 0-10 cm depth, which presented a pure nugget effect. It was possible to observe modifications in the distribution of humic substances in the study area. The results from this study are similar to those of other studies conducted in naive areas in the Atlantic Forest, demonstrating the benefits of using the agroforestry system.