Geostatistical modeling of “lethal coconut palm crown atrophy”, a new disease in the State of Pará

’Lethal Coconut Palm Crown Atrophy’ (LCCA) is a rapidly spreading disease in Brazil, capable of quickly killing coconut trees and threatening the commercial exploration of this plant. The objective of this work was to characterize the spatial and temporal distribution pattern of LCCA in green dwarf coconut commercial plantation areas, located the municipality of Santa Izabel, mesoregion of Northeastern Pará, Brazil. Surveys were carried out at monthly intervals between January 2014 and December 2018, checking for plants with LCCA-characteristic symptoms. Geostatistics was applied to perform spatial-temporal disease estimates based on semivariogram modeling and preparation of ordinary kriging maps. These spatial estimates are conducted through interpolations that characterize data variability in the area. The spherical model yielded the best fit to the spatial distribution of the disease, as it presented the best coefficient of determination (R²), with the range varying between 14m and 45m. The Spatial Dependence Index (SDI) was moderate in the evaluations carried out between 2014 and 2017 (in the 0.26-0.64 range), but not in 2018, when it was strong (0.23). The values of the clustering intensity of LCCA-symptomatic plants were estimated in non-sampled points. The spherical fit model of the data indicates an aggregated distribution pattern, shown by aggregation patches in the plantation, graded by values of dissemination intensity. The kriging maps allowed the observation that the disease expands between plants in the same line, suggesting the possibility of the presence of a short-range vector.

Spatial variability in soybean associated with soil fertility variations in a no-tillage system

Understanding the spatial variability of soil fertility is necessary for preventing nutrient losses or excessive agricultural inputs. The aim of this research was to evaluate the spatial variability of the chemical characteristics of a Typic Hapludox cultivated with soybean for 110 days at different depths and the impacts of these characteristics on crop yield. Soil samples were collected at a total of 80 points in an area of 5000 m2 . The contents of P, Ca, Mg, S, Cu, Fe, Zn and Mn were analyzed, in addition to pH and H+Al. The data were evaluated through descriptive statistics and geostatistical tools, and kriging maps were made based on semivariogram adjustments. Most of the soil fertility variables showed moderate or strong spatial dependence. The statistical moments obtained for the distributions showed that the symmetry of the distributions allowed the use of geostatistics techniques. In general, the greater the soil depth was, the lower the nutrient levels were. The soybean yield range (29.5 m) was similar to the P range in the 0.0-0.20 m soil layer (29.2 m). P influenced the soybean yield the most, as expressed by the similarity between the two kriging maps. In regions with more phosphorus at deeper soil layers, higher soybean yields were obtained.

Spatial variability of air temperature in a free-stall in the Northeastern semi-arid region of Brazil

ABSTRACT The knowledge on the spatial variability of climatic attributes and the building of Kriging maps can assist in the design and management of confined animal facilities, by allowing a spatial visualization that is helpful for the planning and control of information from the production environment. The study aimed to characterize the spatial variability of air temperature in a free-stall barn used for dairy cattle confinement located in Petrolina-PE, Brazil, in different seasons and at different times. The variable air temperature was recorded at 136 points distributed in the areas under the shed and the shade cloth for the study of spatial variability and the construction of maps by Kriging. Air temperature data was collected in the winter and in the summer, in the months of July and August (2013) and January and February (2014), at different times (9 and 15 h). According to the results, the use of geostatistics enabled to define areas with different spatial variabilities in air temperature and specific areas in the free-stall with values higher than the recommended levels for thermal comfort. In addition, the central part of the facility is the region with the lowest values of air temperatures, due to the presence of a ridge vent.

Sampling grid density and lime recommendation in an Oxisol

The objective of this study was to evaluate the influence of different sampling grids density in the lime requirements in an Oxisol. The experiment was conducted at a rural property located in Sidrolândia city, Mato Grosso do Sul state, in the Brazilian ‘Cerrado’. In the soil attributes mapping, regular sampling grid was used consisting of 99 points, spread over an area of 90 ha. Other two grids (51 and 27 points) were derived by deleting lines or lines and points from the original one. Based on the results of soil analysis, the lime requirement at each sample point was calculated. Using geostatistical techniques the spatial variability of lime requirement was studied and grid configuration for each sample was tested. By kriging, maps were made. By reducing the number of sampling points, 11% of the experimental area showed an overestimation and 8% underestimation comparing with the lime requirement made using the highest sampling grid density.

Indicator variables for a robust estimation of an acoustic index of abundance

In North West Africa, pelagic fisheries are an essential economic sector. However, the scientific community fails to perform satisfactory assessments of key pelagic species like sardinella, owing to a lack of relevant indices of abundance to tune the model. This paper provides an alternative acoustic index based on a semiquantitative modelisation of acoustic densities. Acoustic energy is split into binomial variables coding for null, low, medium, large, and very large densities. A multivariate geostatistical approach allows (i) mapping the spatial distribution of classes of densities and (ii) computing a new acoustic index of abundance for Sardinella aurita and Sardinella maderensis. We used the surveys of RV Fridtjof Nansen (1995–2006) and RV Al-Awam (2007–2010). Our results indicated that empirical spatial structures were highly stable over time for both between areas and surveys. Co-kriging maps also showed that sardinella had stable hot spots of distribution. The indices of abundance developed in the present study were tested in an assessment procedure and outperformed all the indices used routinely by the FAO–CECAF (Fishery Committee for the Eastern Central Atlantic) assessment working group.

Spatial variability of air dry bulb temperature and black globe humidity index in a broiler house during the heating phase

The air dry-bulb temperature (t db),as well as the black globe humidity index (BGHI), exert great influence on the development of broiler chickens during their heating phase. Therefore, the aim of this study was to analyze the structure and the magnitude of the t db and BGHI spatial variability, using geostatistics tools such as semivariogram analysis and also producing kriging maps. The experiment was conducted in the west mesoregion of the states of Minas Gerais in 2010, in a commercial broiler house with heating system consisting of two furnaces that heat the air indirectly, in the firsts 14 days of the birds' life. The data were registered at intervals of five minutes in the period from 8 a.m. to 10 a.m. The variables were evaluated by variograms fitted by residual maximum likelihood (REML) testing the Spherical and Exponential models. Kriging maps were generated based on the best model used to fit the variogram. It was possible to characterize the variability of the t db and BGHI, which allowed observing the spatial dependence by using geostatistics techniques. In addition, the use of geostatistics and distribution maps made possible to identify problems in the heating system in regions inside the broiler house that may harm the development of chicks.

Spatial variability of noise level in agricultural machines

The knowledge of the spatial variability of noise levels and the build of kriging maps can help the evaluation of the salubrity of environments occupied by agricultural workers. Therefore, the objective of this research was to characterize the spatial variability of the noise level generated by four agricultural machines, using geostatistics, and to verify if the values are within the limits of human comfort. The evaluated machines were: harvester, chainsaw, brushcutter and tractor. The data were collected at the height of the operator's ear and at different distances. Through the results, it was possible to verify that the use of geostatistics, by kriging technique, made it possible to define areas with different levels for the data collected. With exception of the harvester, all of machines presented noise levels above than 85 dB (A) near to the operator, demanding the use of hearing protection.

Terrain forms and spatial variability of soil properties in an area cultivatedwith citrus

The technique of precision agriculture and soil-landscape allows delimiting areas for localized management, allowing a localized application of agricultural inputs and thereby may contribute to preservation of natural resources. Therefore, the objective of this work was to characterize the spatial variability of chemical properties and clay content in the context of soil-landscape relationship in a Latosol (Oxisol) under cultivation of citrus. Soil samples were collected at a depth of 0.0-0.2 m in an area of 83.5 ha planted with citrus, as a 50-m intervals grid, with 129 points in concave terrain and 206 points in flat terrain, totaling 335 points. Values for the variables that express the chemical characteristics and clay content of soil properties were analyzed with descriptive statistics and geostatistical modeling of semivariograms for making maps of kriging. The values of range and kriging maps indicated higher variability in the shape of concave topography (top segment) compared with the shape of flat topography (slope and hillside segments below). The identification of different forms of terrain proved to be efficient in understanding the spatial variability of chemical properties and clay content of soil under cultivation of citrus.

Geostical analysis of spatial dynamics of Citrus Variegated Chlorossis

The spatial dynamics of Citrus Variegated Chlorosis (CVC) was studied in a five-year old commercial orchard of 'Valencia' sweet orange (Citrus sp.) trees, located in the northern region of the state of São Paulo, Brazil. One thousand trees were assessed in 25 rows of 40 trees, planted at 8 x 5 m spacing. Disease incidence data were taken beginning in March 1994 and ending in January 1996, at intervals of four to five months. Disease aggregation was observed through the dispersion index analysis (Ib), which was calculated by dividing the area into quadrants. CVC spatial dynamics was examined using semivariogram analysis, which revealed that the disease was aggregated in the field forming foci of 10 to 14 m. For each well-fitted model, a kriging map was created to better visualize the distribution of the disease. The spherical model was the best fit for the data in this study. Kriging maps also revealed that the incidence of CVC increased in periods during which the trees underwent vegetative growth, coinciding with greater expected occurrence of insect vectors of the bacterium in the field.

Geostatistical analysis of heavy metals in a one-hectare plot under natural vegetation in a serpentine area

The objective of this study was to examine the spatial variability of selected heavy metals in a soil developed over serpentine. Both total and EDTA-extractable Fe, Mn, Cr, Ni, Cu, Zn and Co were determined in 53 samples, collected from the topsoil of a 1-ha forested plot. Naturally occurring soil Cr and Ni concentrations were much higher than critical limits for safety. Experimental semivariograms were computed and modelled by a nugget component plus a structure with autocorrelation ranges varying between 25 and 90 m. EDTA-extractable heavy metal contents exhibit a different spatial variation pattern from that of total contents, although Ni and Cu semivariograms present some similarities. The joint spatial variation for pairs of variables with significant correlation was also investigated. The nugget variances in the cross-semivariograms were not very different from those of individual semivariograms, suggesting heterogeneity within the shortest sampling interval. Semivariograms provided a clear description of the spatial structure of heavy metals and some insight into possible processes affecting their distribution. Kriging maps allowed the identification of small regions with distinct metal concentrations and confirmed the suitability of geostatistics for investigating processes controlling heavy metal variation. Isotopic cokriging performed better than kriging, but the gain for mapping purposes was limited. Key words: Serpentine, heavy metals, geostatistics, scaling, spatial variability