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The delineation of management zones (MZs) is an important strategy for implementing precision agriculture. However, it is a complex process that requires further study. The objective of this study is to delineate MZs and validate them with respect to soil characteristics as well as corn and soybean yield in a 97-ha land cultivated under a no-till farming system. Samples were collected for physio-chemical analysis of soils and apparent electrical conductivity (EC). Moreover, data on the altitude and yield of soybean and corn were obtained. The data were initially analyzed descriptively and using Pearson correlation. Data interpolation and the elaboration of spatial variability maps for each characteristic were then performed. Furthermore, MZ thematic maps were developed. The ideal number of MZs for each combination or strategy studied was determined by the lowest value of the fuzziness performance index and normalized classification entropy. For MZ validation, Fuzzy K-means algorithm and Kappa index were used. The delineation of MZ was possible with the use of the soil characteristics with a higher temporal stability, such as the combined use of EC, soil organic matter, and clay, enabling the validation of differences in corn and soybean yield using Fuzzy algorithm and Kappa index. Data collected in different sample density did not interfere in the definition and validation of the MZ. No correlation was found between the soil EC and other chemical characteristics and yield. Furthermore, the correspondence of soil chemical properties for each MZ was not be feasible in areas with built-up soil fertility.

North African forest areas play several roles and functions and represent a heritage of great economic and ecological importance. As a result of global changes, that act independently or synergistically, these areas are currently undergoing a pronounced degradation and their productivity is decreasing due to several factors. This work aims to characterize spatio-temporal dynamics of vegetation within the Maamora forest. This forest is considered as the most extensive cork oak woodland in the world and is divided, from west to east, into five cantons A, B, C, D and E. The data, extracted between 2000–2021 from MODIS NDVI/EVI images of 250 m, were analyzed using statistical parameters with the Pettitt homogeneity and the Mann-Kendall trend tests, with their seasonal and spatial components, in order to better consider the vegetation distribution of this forest. Results show a clear temporal and spatial (inter-canton) variability of vegetation intensity, unrelated to the continental gradient. In fact, recorded mean values in cantons C and E are significantly higher than those of cantons B and D respectively. This is confirmed by both regressive and progressive trends, which were identified respectively from the months of March 2012 and October 2008, in the data series of cantons B and E successively. Spatially, the regressive dynamic remains generalized and affects more than 26.7% of the Maamora’s total area with extreme rates (46.1% and 14.0%) recorded respectively by the two aforementioned cantons. Similarly, all the stand types in canton B show the highest regressive rates, especially the cork oak regeneration strata (75.4%) and the bare lands (86.1%), which may explain the positive tendencies identified by the related series during the fall season. However, the cantons C and E record the lowest rates, respectively, for natural stands of cork oak and artificial plantations. These results highlight also the absence of a causal relationship between the contrasting vegetation dynamics of the Maamora and the climatic conditions, expressed here by the continental gradient. However, they do highlight the effects of other factors, particularly those of a technical nature.

Tibraca limbativentris is considered one of the main species of insect pests in irrigated rice. This species can be found in plants in the vegetative and reproductive stages. This study aimed to select semivariogram models to estimate rice stem bug population densities by ordinary kriging. Two fields were used to survey the T. limbativentris population in Oryza sativa. A grid of 30 x 30 m was drawn, which generated 143 and 385 sample units for the first and second fields, respectively. Seven evaluations of two hundred plants per sampling unit were performed during cultivation. From the insect counts, the results were input into circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, cardinal sine, K-Bessel, J-Bessel, and stable semivariogram models via ordinary kriging interpolation and the best model was selected via cross-validation. Each assessment had a particular spatial structure and semivariogram model that best fit the experimental data.

The spatial behavior of the environmental variables involved in rose production is one of the factors of greatest current interest in the Colombian ornamental sector. The aim of this work consisted in the evaluation of a passive greenhouse through an experimental approach that included the capture and recording of data through a grid of 40 sensors homogeneously distributed inside the greenhouse. The data processing was carried out through the application of geostatistical techniques that allowed to obtain contour plots for 5 levels of radiation intensity. The results of the exploratory analysis showed that the behavior of temperature, relative humidity and vapour pressure deficit are not the most suitable for rose production, mainly for the conditions of the night period where the temperature exhibited values below 12.5 °C, the relative humidity was above 90% and the vapour pressure deficit was below 0.1 kPa. On the other hand in the structural analysis the circular model of theoretical semivariogram was the one that better degree of adjustment presented in comparison with the experimental data finding that a strong spatial dependency exists for the studied variables, the prediction of the not sampled points was made by means of the method of ordinary kriging finding that horizontal gradients of temperature and relative humidity exist inside the greenhouse that increases in magnitude according to the level of radiation arriving to reach values of 6.1 °C and 30.4%.

The aim of this work was to study distribution of some heavy metals in different soil particle-size fractions and to assess their spatial distribution. The study was carried out in Kafe Moor (Kerman, Iran) where the Gol-Gohar Iron Mine is located. One hundred twenty composite soil samples were randomly collected and transferred to the laboratory in bags. After air-drying, the samples were fractionated into six classes including 2- 0.5, 0.5-0.25, 0.25-0.125, 0.125- 0.075, 0.075-0.05 and

Natural formation of soil deposits causes heterogeneity and anisotropy in their strength and stiffness properties. However, most soils in their natural states exhibit some anisotropy with respect to shear strength and heterogeneity with respect to the depth. In this paper, the standard Mohr- Coulomb constitutive law is generalized to anisotropic version in order to consider the effect of cohesion anisotropy of soil. Random field theory coupled with finite difference method was utilized in Monte Carlo simulations with considering the effect of auto-correlation and cross correlation between strength parameters of soil, in order to calculate the bearing capacity of shallow foundation in a strain controlled scheme. The results showed that the bearing capacity of shallow foundation decreases with increasing in variability of strength parameters and increases with increasing in anisotropy ratio.

The application of precision agriculture considers the values of non-sampled places by the interpolation of sample data. The accuracy with which the maps of spatial distribution of yield and the soil attributes are produced in the interpolation process influences their application and utilization. This paper aimed to compare three interpolation methods (inverse of the distance, inverse of the square distance, and ordinary kriging) in the construction of thematic maps of soybean yield and soil chemical attributes. A set of data referred to 55 sampling units for the construction maps of soybean yield and of eight soil chemical attributes, by different interpolation methods. The comparison was made based on the error matrix, by calculating the Kappa and Tau indices, beyond the relative deviation coefficient (RDC). It was noticed that the inverse of the square distance was the interpolator that less influenced the data behavior, and the best interpolation method dependent of the variability of the studied attribute. The kriging and the inverse of the square distance were considered the methods that presented the best results in the interpolation of data.

The crop yield potential is affected by the crop-weed competition and their control create a dependence on herbicide use who brings, as consequence, soil impacts. Knowing the weed’s spatial distribution on the field is a feasible alternative for improving the crop yield. The goal of this paper is the identification of the spatial variability on physical and chemical attributes of soil as well as the weed’s seedbank so that, when correlated, may find standards to help on field management. The experiment was conducted on Uberlandia Federal University premises at soybean no-till area. Using georeferenced soil samples, were analyzed the physical and chemical attributes as well as the weed’s seedbank. The weed population on controlled environment was quantify, sorting out broadleaf and grassy weeds species. The obtained data were analyzed by descriptive statistic and geostatistics for a semivariogram modeling, interpolation by the kriging methodology and the spatial variability maps achievement. The average value, coefficient of variation (CV%), asymmetry, kurtosis coefficient and the significant linear correlations interfered on data spatial variability which we concluded by the spatial dependences on the attributes that had a linear correlation between them. The semivariograms presented varied range between 202 to 752 meters. Using the maps, verified two different regions for the broadleaf and grassy weeds seedbank. For both situations there was influence by the soil attributes on infestation level, which makes it possible to target the herbicide management reducing costs and the environmental impact. From the analyzed data we conclude that there is a spatial dependence for the physical and chemical soil attributes and their spatial distribution explains the weed seedbank spatial variability.

Wang, Y.; Zhang, L., and Haimiti, Y., 2015. Study on spatial variability of soil nutrients in Ebinur lake wetlands in China. Three typical regions were selected in Ebinur Lake wetlands of Xinjiang in China, and the nutrient content of their soil was determined with analytical chemistry approaches. Based on the chemical information, the Geostatistics method was employed to analyze the space variability of the soil nutrients for each region. The results were that the comprehensive nutrients level of Region C (Aqikesu River) was higher than those of Region B (Jinghe and Bortala River) and Region A (Alashankou). There is a strong spatial autocorrelation for the soil nutrients studied. Soil organic matter, nitrogen, available phosphorus in every region showed moderate variability, and the variability of potassium depended on the region. The spatial variability of soil nutrients is assumedly caused by climate, topography, soil type, etc. The study is of great significance in understanding the forming process of soil, as well as in providing scientific reference for restoring of soil degradation and dust resistance of the regions studied. [ABSTRACT FROM AUTHOR]

The article examines the linkages among environmental gradients and three measures of ecosystem nitrogen (N) cycling collected during the 2003 growing season. With this, maps of canopy nitrogen obtained through analysis of high-resolution, hyperspectral, remotely sensed images offer a powerful means to make landscape-scale to regional-scale estimates of forest N cycling and net primary production. These linkages include, field survey of canopy N, field survey of soil C:N and canopy N measured through analysis of hyperion hyperspectral images.

Aflatoxin contamination in corn caused by Aspergillus flavus Link is a serious constraint on economical corn (Zea mays L.) production in the Mississippi Delta. The ecology of A. flavus was evaluated in a 3-year study assessing the spatial variability of soil populations of A. flavus in a Mississippi Delta field under different crops. A 1.07-ha section of the field was laid out in 126 9.2-m2 plots, and soil was sampled in May 2000, March 2001, and April 2002. Aspergillus flavus populations were determined by plating on selective media, and A. flavus colonization was assessed in corn during 2000. Aspergillus flavus populations in soil were significantly (P < 0.01 level) influenced by previous crop. The highest propagule density (794 cfu·g–1) was found following the corn crop in 2001 versus 251 cfu·g–1 soil in 2000 following cotton and 457 cfu·g–1 following wheat in 2002. Aspergillus flavus populations in 2001 and 2002 exhibited a moderate degree of spatial structure, described by spherical and exponential models, respectively, but populations in 2000 exhibited little spatial structure. Colonization of corn kernels by A. flavus in 2000 ranged from 0% to 100% (mean = 15% colonized kernels), and aflatoxin levels ranged from 0 to 1590 ppb (mean = 57 ppb). Aflatoxin levels were randomly distributed in the field and not correlated with A. flavus colonization. Aflatoxin production was found in 43% to 59% of A. flavus soil isolates with the highest incidence in soil populations following corn in 2001. However, 84% of A. flavus isolated from corn kernels produced aflatoxin. Results indicate that within a single field there was a wide range of A. flavus soil propagule densities varying in potential to produce aflatoxin.Key words:Aspergillus flavus, aflatoxins, soil, corn (Zea mays), cotton, wheat, spatial variability. [ABSTRACT FROM AUTHOR]

Fluxes of carbon dioxide, water and sensible heat were measured using three different eddy covariance systems above the forest floor of a closed deciduous forest (leaf area index approx 6). The primary objective was to examine the representativeness of a single eddy covariance system in estimating soil respiration for time scales ranging from one-half hour to more than one week. Experiments were conducted in which the eddy covariance sensors were in one of three configurations: i) collocated, ii) separated horizontally or iii) separated vertically. A measure of the variation between the three systems (CV',related to the coefficient of variation) for half-hour carbon dioxide fluxes was 0.14 (collocated systems), 0.34 (vertically separated systems at 1, 2 and 4 m above the surface), and 0.57 (systems horizontally separated by 30 m). A similar variation was found for other scalar fluxes (sensible and latent heat). Variability between systems decreased as the number of half-hour sampling periods used to obtain mean fluxes was increased. After forty-eight hours (means from ninety-six half-hour samples), CV' values for carbon dioxide fluxes were 0.07, 0.09 and 0.16 in the collocated, vertically separated and horizontally separated experiments, respectively. The time dependence of variability has implications on the appropriateness of using short-term measurements in modelling validation studies. There are also implications concerning the appropriate number of half-hour samples necessary to obtain reliable causal relationships between flux data and environmental parameters. Based on the longer-term measurements, we also discuss the representativeness of a single eddy covariance system in long-term monitoring of soil respiration and evaporation beneath forest canopies using the eddy covariance method. [ABSTRACT FROM AUTHOR]

ABSTRACT The South American fruit fly Anastrepha fraterculus (Wied., 1830) is one of the major insect pests of economic importance in vineyards of Southern Brazil. Understanding species behavior and knowing the moments when their population peaks occur can help producers and technicians to define management strategies. This work was carried out the spatial and temporal distribution of the A. fraterculus in two commercial vineyards of variety ‘Moscato Branco’ for two crop seasons. To evaluate the A. fraterculus distribution, we used the mass trapping system with handmade traps (transparent plastic bottles of polyethylene terephthalate - PET), baited with hydrolyzed protein CeraTrap™. The evaluations were performed every two weeks, counting the total number of adults found per trap in each vineyard. From the number of insects caught per trap, data analysis was performed using geostatistics, through semivariograms. The spatio-temporal fruit fly distribution was evaluated by thematic maps, using the inverse square distance interpolation. The semivariograms showed that most of the reviews were ‘pure nugget’ effect, indicating the absence of spatial data dependence. The spatio-temporal distribution maps allow us to assert that A. fraterculus shows invasive behavior in the vineyard, with its entry from the edges to the center, associated with the fruit ripening.

Tidal freshwater marshes are critical buffers that exist at the interface between watersheds and estuaries. Little is known about the physical dynamics of tidal freshwater marsh evolution. Over a 21-mo period, July 1995 to March 1997, measurements were made of biweekly sediment deposition at 23 locations in a 3.8-ha tidal freshwater marsh in the Bush River subestuary of the upper Chesapeake Bay. Biweekly accumulation showed high spatial and temporal variability, ranging from -0.28 g cm-2 to 1.15 g cm-2. Spatial variability is accounted for by habitat differences including plant associations,elevation, and hydrology. Temporal variability is accounted for by interannual climate variability, the growth cycles of marsh plants, stream-marsh interactions, forest-marsh interactions, and animal activity. [ABSTRACT FROM AUTHOR]

In this first paper of two, a numerical simulation model capable of simulating the spatial variability of rainfall partitioning within a canopy is presented. The second paper details how the model is parameterized, and some testing of its capabilities The first stage of the model is to derive the mature canopy structure. This is achieved through simplified individual tree structures and a random placement routine based on a modified Poisson distribution. Following this the spatial discretization for throughfall is attained as a series of layers of triangles with a tree trunk at every apex. The number of layers isderived from the leaf area index through a modified Poisson distribution. Seasonal variation in the deciduous canopy is simulated througha time vector routine. The rainfall partitioning section of the model is based upon the Rutter model which has been modified to each individual triangle layer. The main feature of this model is that it offers a method of simulating rainfall partitioning at a scale that is a function of the size of the elementary physical components (tree and leaf scale). This can be used to investigate soil moisture variationsunder a canopy, or to study the variations within the forest hydrological processes themselves. [ABSTRACT FROM AUTHOR]

This paper gives details of how the spatially variable rainfall partitioning model, presented in Davie and Durocher, (1997) [Hydrol. Process., 11, 1509-1523], is parameterized, and the testing of its capabilities. A majority of the input parameters required for running the model can be derived from physical measurements. The remainder can be derived from previous forest interception studies. The measured values used in model testing were from a mixed oak and sweet chestnut plantation on the outskirts of Bristol, UK. A sensitivity analysis of themodel has been carried out. The importance to throughfall of potential evaporation rate, storage capacity and gap area within the canopy is highlighted. For stemflow the proportion of tree crown area generating stemflow is the most important parameter. This is largely a reflection of the model structure. The model has been tested with field data to evaluate its ability for predicting: total throughfall and stemflow for individual events; spatial variability in rainfall partitioning; and temporal dynamics of throughfall. The model was able reproduce these data sets; however the field data (from an intensive plot study) was not adequate to allow complete validation of the model. Thenovel feature of the model (spatial variability of rainfall partitioning) was shown to be quite well simulated. Suggestions are given forusing this type of model in future research. [ABSTRACT FROM AUTHOR]

Spatial monitoring campaigns of volatile organic compounds were carried out in two similarly sized urban industrial cities, Windsor and Sarnia, ON, Canada. For Windsor, data were obtained for all four seasons at approximately 50 sites in each season (winter, spring, summer, and fall) over a three-year period (2004, 2005, and 2006) for a total of 12 sampling sessions. Sampling in Sarnia took place at 37 monitoring sites in fall 2005. In both cities, passive sampling was done using 3M 3500 organic vapor samplers. This paper characterizes benzene, toluene, ethylbenzene, o, and (m + p)-xylene (BTEX) concentrations and relationships among BTEX species in the two cities during the fall sampling periods. BTEX concentration levels and rank order among the species were similar between the two cities. In Sarnia, the relationships between the BTEX species varied depending on location. Correlation analysis between land use and concentration ratios showed a strong influence from local industries. Use one of the ratios between the BTEX species to diagnose photochemical age may be biased due to point source emissions, for example, 53 tonnes of benzene and 86 tonnes of toluene in Sarnia. However, considering multiple ratios leads to better conclusions regarding photochemical aging. Ratios obtained in the sampling campaigns showed significant deviation from those obtained at central monitoring stations, with less difference in the (m + p)/E ratio but better overall agreement in Windsor than in Sarnia.