Spatial variability of the stability of cohesive soil aggregates under conservation practices / Variabilidade espacial da estabilidade dos agregados de solo coeso sob práticas conservacionistas

The knowledge and characterization of aggregate stability are relevant to select adequate management and to avoidits degradation. Thus, this studyaimed to characterize the spatial variability of aggregate stability in cohesive soilsunder crop conservation systems. The experiment was performed intwo different areas of soybean production: no-tillage System (NTS) and livestock farming integration system (LFI), In each production area, a sampling mesh composed of 50 collection points, with a regular spacing of 40 m, at 0.00-0.20 mdepth, wascarried out. The results were expressed as a percentage of aggregates retained in sieves 2; 1; 0.5 and 0.25 mm, the values obtained were used to calculate the Mean Geometric Diameter (MGD) and Mean Weight Diameter (MWD). In the LFI system, which had a strong degree of spatial dependence (DSD), the attributes showed a moderate DSD, except for MWD. Generally, the reachedvalues of the attributes in the LFI system were lower than those found in the NTS system, showing less variability in the management system with no-tillage. Spatial distribution of the kriging maps demonstrated the LFI system leading to the formation of larger aggregates in the soil when compared to ones to the same attributes in the NTS. All attributes showed a strong to moderatespatial dependence. The soil managed with the LFI system revealed greater aggregate stability when compared to the NTS, which in turn presented less spatial variability than the LFI system and shows a more homogeneous soil.(AU)

O conhecimento e a caracterização da estabilidade dos agregados são relevantes para selecionar um manejo adequado e evitar sua degradação. Portanto, este estudoteve como objetivo caracterizar a variabilidade espacial da estabilidade de agregados em solos coesos sob sistemas de conservação de culturas. O experimento foi conduzido em duas áreas distintas de produção de soja: sistema de plantio direto (NTS) e sistema de integração pecuária (LFI). Foi realizada uma amostragem de 50 pontos de coleta, com espaçamento regular de 40 m, na profundidade de 0,00-0,20 m, em cada área de produção.Os resultados foram expressos como porcentagem de agregados retidos nas peneiras 2; 1; 0,5 e 0,25 mm, os valores obtidos foram utilizados para calcular o Diâmetro Médio Geométrico (DMM) e o Diâmetro Peso Médio (DMM). No sistema LFI, que possuía alto grau de dependência espacial (DDS), os atributos apresentaram um DSD moderado, exceto para MWD. De maneira geral, os valores de escopo dos atributos no sistema LFI foram inferiores aos encontrados no sistema NTS, apresentando menor variabilidade no sistema de manejo do plantio direto. A distribuição espacial dos mapas de krigagem mostrou que o sistema LFI leva à formação de agregados maiores no solo em comparação com outros com os mesmos atributos no NTS. Todos os atributos apresentaram dependência espacial de forte a moderada. O solo manejado com o sistema LFI revelou maior estabilidade dos agregados em relação ao NTS, que por sua vez apresentou menor variabilidade espacial do que o sistema LFI e apresenta um solo mais homogêneo.(AU)

Ovipositional Reproduction of the Dengue Vector for Identifying High-Risk Urban Areas.

Identification and classification of high-risk areas for the presence of Aedes aegypti is not an easy task. To develop suitable methods to identify this areas is an essential task that will increase the efficiency and effectiveness of control measures and to optimize the use of resources. The objectives of this study were to identify high- risk areas for the presence of Ae. aegypti using mosquito traps and household visits to identify breeding sites; to identify and validate aspects of the remote sensing images that could characterize these areas; to evaluate the relationship between this spatial risk classification and the occurrence of Ae. aegypti; and provide a methodology to the health and control vector services and prioritize these areas for development of control measure. Information about the geographical coordinates of these traps will enable us to apply the kriging spatial analysis tool to generate maps with the predicted numbers of Ae. aegypti. Satellite images were used to identify the characteristic features the four areas, so that other areas could also be classified using only the sensing remote images. The developed methodology enables the identification of high-risk areas for Ae. aegypti and for the occurrence of Dengue, as well as Zika fever and Chikungunya fever using only sensing remote images. These results allow health and vector control services to prioritize these areas for developing surveillance and control measures. The use of the available resources can be optimized and potentially promote a decrease in the expected incidences of these diseases, particularly Dengue.

Spatio-temporal groundwater arsenic distribution in Central Mexico: implications in accumulation of arsenic in barley (Hordeum vulgare L.) agrosystem.

In the present work, a spatio-temporal study of arsenic (As) concentration in groundwater and its impact in barley uptake is presented. The impact of As on barley is studied through the determination of its bioaccumulation in the soil-plant system, As uptake, as well as a correlation between As concentration in water and its temperature in the groundwater. For the groundwater, spatial and temporal variability of As concentration in central Mexico was determined through a geostatistical analysis using ordinary kriging. The results show that the variability of As in the ground water is correlated with its temperature (R2 > 0.83). The As accumulation in the structures of plant follows the order root > leaf > ear in concentration. The bioaccumulation factor BAFT suggests that As is mobilized to the aerial parts of the barely for both As concentrations used in the irrigation water. However, for As concentration lower than 25 µg L-1, the BAFT is lower than 0.57, suggesting that the amount of As in root is the same as that contained in the aerial parts; whereas, for higher As concentrations (from 170 to 250 µg L-1), the BAFT is around 0.92, indicating that the As is mainly contained in root. The spatial distribution of As concentration trend in groundwaters along the time is the same, which means high As concentration areas remain in the same groundwaters and these areas are presenting the highest water temperature. These results shall contribute to understand the bioaccumulation of As in barley and the As spatial variability in central Mexico.

Geostatistical modeling of "lethal coconut palm crown atrophy", a new disease in the State of Pará / Modelagem geoestatística da "Atrofia Letal da Coroa Coqueiro", uma nova doença no Estado do 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 nonsampled 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.(AU)

A 'Atrofia Letal da Coroa do Coqueiro' (ALCC) é uma doença de rápida disseminação no Brasil, capaz de matar os coqueiros rapidamente e ameaçar a exploração comercial da planta. O objetivo deste trabalho foi caracterizar o padrão de distribuição espacial e temporal de ALCC em áreas de plantio comercial de coco anão verde, localizadas no município de Santa Izabel, mesorregião do Nordeste do Pará, Brasil. As pesquisas foram realizadas em intervalos mensais entre janeiro de 2014 e dezembro de 2018, verificando se havia plantas com sintomas característicos da ALCC. A geoestatística foi aplicada para realizar estimativas espaço-temporais de doenças com base na modelagem de semivariogramas e na preparação de mapas de krigagem comuns. Essas estimativas espaciais são realizadas por meio de interpolações que caracterizam a variabilidade dos dados na área. O modelo esférico apresentou o melhor ajuste à distribuição espacial da doença, pois apresentou o melhor coeficiente de determinação (R²), com amplitude variando entre 14m e 45m. O Índice de Dependência Espacial (SDI) foi moderado nas avaliações realizadas entre 2014 e 2017 (na faixa de 0,26-0,64), mas não em 2018, quando era forte (0,23). Os valores da intensidade de agrupamento de plantas sintomáticas ALCC foram estimados em pontos não amostrados. O modelo de ajuste esférico dos dados indica um padrão de distribuição agregado, mostrado por manchas de agregação na plantação, graduadas por valores de intensidade de disseminação. Os mapas de krigagem permitiram observar que a doença se expande entre plantas na mesma linha, sugerindo a possibilidade da presença de um vetor de curto alcance.(AU)

Spatial Distribution of Frankliniella schultzei (Thysanoptera: Thripidae) in Open-Field Yellow Melon, With Emphasis on the Role of Surrounding Vegetation as a Source of Initial Infestation.

Frankliniella schultzei (Trybom) is a serious pest of melon crops and is commonly found in the main producing areas of melon in Brazil (North and Northeast regions). This pest causes significant losses, damaging plants through feeding and tospovirus vectoring. Thus, the proper management of F. schultzei is crucial to prevent economic losses, and knowledge of the within-field distribution patterns of F. schultzei can be used to improve this pest management. This study aimed to determine the within-field distribution (through semivariogram modeling and kriging interpolation) and the factors associated with F. schultzei abundance in open-field yellow melon crops. We surveyed four yellow melon fields located in Formoso do Araguaia (Tocantins state, North Brazil) for thrips abundance in various crop stages (vegetative, flowering, and fruiting) in 2015 and 2016. Twelve models were fitted and it was determined that F. schultzei counts were strongly aggregated. The median spatial dependence was 4.79 m (range 3.55 to 8.02 m). The surface maps generated by kriging depicted an edge effect in fields 3 and 4. In addition, correlation analyses indicated that air temperature and presence of surrounding cucurbits are positively associated with F. schultzei abundance in yellow melon fields. Altogether, these insights can be combined for spatially based pest management, especially when the conditions (cucurbits in the surroundings and warmer periods) are favorable to F. schultzei.

Distribución espacial de antracnosis (Colletotrichum gloeosporioides Penz) en aguacate en el Estado de México, México / Spatial distribution of anthracnose (Colletotrichum gloeosporioides Penz) in avocado in the State of Mexico, Mexico

Resumen El aguacate (Persea americana) es una especie cuyo cultivo es de gran importancia nutricional y económica para México; sin embargo, como cualquier otro cultivo, a menudo se ve afectado por plagas y enfermedades que limitan su comercialización a nivel mundial. El hongo fitopatógeno Colletotrichum gloeosporioides es el agente causal de la antracnosis en el aguacate y se manifiesta en las etapas tempranas del desarrollo del fruto, así como en poscosecha y durante el almacenamiento, en condiciones de alta humedad relativa (80%) y temperaturas desde los 20 ◦C. Las pérdidas económicas a causa de este hongo pueden ser de hasta el 20% de la producción. En el presente estudio se aplicaron métodos geoestadísticos para definir la distribución espacial de antracnosis en frutos de aguacate cultivar Hass en cuatro municipios del Estado de México, durante el periodo de enero a junio de 2017. La distribución de la antracnosis se ajustó a modelos gaussianos y exponenciales en la mayoría de los casos. Los mapas de infestación realizados mediante krigeado muestran más de un centro de agregación de la enfermedad. Este análisis permitió estimar la superficie infestada: se encontró una infestación de más del 50% en los primeros muestreos y de hasta un 98% en los muestreos de junio en todas las zonas estudiadas. © 2019 Publicado por Elsevier Espana, S.L.U. en nombre de Asociacion Argentina de Microbiologıa. Este es un art´ıculo Open Access bajo la licencia CC BY-NC-ND (http://creativecommons. org/licenses/by-nc-nd/4.0/).

Abstract Persea americana is a species of great nutritional and economic importance for Mexico, however, like any other agricultural crop, it is affected by pests and diseases that limit its worldwide commercialization. The phytopathogenic fungus Colletotrichum gloeosporioides is the causative agent of anthracnose in avocado and manifests itself in the early stages of fruit development as well as in post-harvest and storage, under conditions of high relative humidity (80%) and at temperatures from 20°C, causing losses economic up to 20% of production. Applying geostatistical methods the present study aims to define the spatial distribution of anthracnose in Hass avocado fruits in four municipalities of the State of Mexico during the period from January to June 2017. The results show that the distribution of anthracnose was adjusted to gaussian and exponential models in most, the infestation maps made through the kriging show more than one centerof aggregation of the disease, based on it the infested surface was estimated, finding an infestation of more than 50% in the first samples and up to 98% in the samplings belonging to the month of June in all the areas studied. © 2019 Published by Elsevier Espana, S.L.U. on behalf of Asociación Argentina de Microbiología. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/ licenses/by-nc-nd/4.0/).

[Spatial distribution of anthracnose (Colletotrichum gloeosporioides Penz) in avocado in the State of Mexico, Mexico]. / Distribución espacial de antracnosis (Colletotrichum gloeosporioides Penz) en aguacate en el Estado de México, México.

Persea americana is a species of great nutritional and economic importance for Mexico, however, like any other agricultural crop, it is affected by pests and diseases that limit its worldwide commercialization. The phytopathogenic fungus Colletotrichum gloeosporioides is the causative agent of anthracnose in avocado and manifests itself in the early stages of fruit development as well as in post-harvest and storage, under conditions of high relative humidity (80%) and at temperatures from 20°C, causing losses economic up to 20% of production. Applying geostatistical methods the present study aims to define the spatial distribution of anthracnose in Hass avocado fruits in four municipalities of the State of Mexico during the period from January to June 2017. The results show that the distribution of anthracnose was adjusted to gaussian and exponential models in most, the infestation maps made through the kriging show more than one center of aggregation of the disease, based on it the infested surface was estimated, finding an infestation of more than 50% in the first samples and up to 98% in the samplings belonging to the month of June in all the areas studied.

Bacterial and archaeal spatial distribution and its environmental drivers in an extremely haloalkaline soil at the landscape scale.

BACKGROUND: A great number of studies have shown that the distribution of microorganisms in the soil is not random, but that their abundance changes along environmental gradients (spatial patterns). The present study examined the spatial variability of the physicochemical characteristics of an extreme alkaline saline soil and how they controlled the archaeal and bacterial communities so as to determine the main spatial community drivers. METHODS: The archaeal and bacterial community structure, and soil characteristics were determined at 13 points along a 211 m transect in the former lake Texcoco. Geostatistical techniques were used to describe spatial patterns of the microbial community and soil characteristics and determine soil properties that defined the prokaryotic community structure. RESULTS: A high variability in electrolytic conductivity (EC) and water content (WC) was found. Euryarchaeota dominated Archaea, except when the EC was low. Proteobacteria, Bacteroidetes and Actinobacteria were the dominant bacterial phyla independent of large variations in certain soil characteristics. Multivariate analysis showed that soil WC affected the archaeal community structure and a geostatistical analysis found that variation in the relative abundance of Euryarchaeota was controlled by EC. The bacterial alpha diversity was less controlled by soil characteristics at the scale of this study than the archaeal alpha diversity. DISCUSSION: Results indicated that WC and EC played a major role in driving the microbial communities distribution and scale and sampling strategies were important to define spatial patterns.

Spatial dependency and correlation of properties of soil cultivated with oil palm, Elaeis guineensis, in agroforestry systems in the eastern Brazilian Amazon / Dependência espacial e correlação das propriedades do solo cultivado com dendezeiro, Elaeis guineensis, em sistemas agroflorestais na Amazônia Oriental

Geostatistics is a tool that can be used to produce maps with the distribution of nutrients essential for the development of plants. Therefore, the present study aimed to analyze the spatial variation in chemical attributes of soils under oil palm cultivation in agroforestry systems in the eastern Brazilian Amazon, and their spatial dependence pattern. Sixty spatially standardized and georeferenced soil samples were collected at each of three sampling sites (DU1, DU2, and DU3) at 0-20 cm depth. Evaluated soil chemical attributes were pH, Al3+, H+Al, K+, Ca2+, Mg2+, cation exchange capacity (CEC), P, and organic matter (OM). The spatial dependence of these variables was evaluated with a semivariogram analysis, adjusting three theoretical models (spherical, exponential, and Gaussian). Following analysis for spatial dependence structure, ordinary kriging was used to estimate the value of each attribute at non-sampled sites. Spatial correlation among the attributes was tested using cokriging of data spatial distribution. All variables showed spatial dependence, with the exception of pH, in one sampling site (DU3). Highest K+, Ca2+, Mg2+, and OM levels were found in the lower region of two sampling sites (DU1 and DU2). Highest levels of Al3+ and H+Al levels were observed in the lower region of sampling site DU3. Some variables were correlated, therefore cokriging proved to be efficient in estimating primary variables as a function of secondary variables. The evaluated attributes showed spatial dependence and correlation, indicating that geostatistics may contribute to the effective management of agroforestry systems with oil palm in the Amazon region.(AU)

A geoestatística é uma ferramenta utilizada para produzir mapas de distribuição de nutrientes essenciais para o desenvolvimento das plantas. O presente estudo teve como objetivo analisar a variação espacial dos atributos químicos do solo sob cultivo de dendê em sistemas agroflorestais na Amazônia Oriental brasileira, e seu padrão de dependência espacial. Sessenta amostras de solo espacialmente padronizadas e georreferenciadas foram coletadas em cada um de três locais de amostragem (UD1, UD2 e UD3), na profundidade de 0-20 cm. Os atributos químicos do solo avaliados foram: pH, Al3+, H+Al, K+, Ca2+, Mg2+, capacidade de troca catiônica do solo (CTC), P e matéria orgânica (MO). A dependência espacial dos atributos foi avaliada com análise semivariográfica, ajustando-se três modelos teóricos (esférico, exponencial e gaussiano). Após a análise de dependência espacial, a krigagem ordinária foi empregada para estimar os valores de cada atributo em locais não amostrados. A correlação espacial entre os atributos foi testada utilizando a cokrigagem para espacialização dos dados. Todas as variáveis mostraram dependência espacial, exceto pH em UD3. Os maiores teores de K+, Ca2+, Mg2+ e MO foram encontrados na região mais baixa da paisagem, em UD1 e UD2. Os maiores teores de Al3+ e H+Al foram observados na região mais baixa da paisagem, em UD3. Algumas variáveis foram correlacionadas, portanto a cokrigagem mostrou-se eficiente na estimativa das variáveis primárias em função das secundárias. Os atributos avaliados mostraram dependência e correlação espacial, indicando que a geoestatística pode contribuir para o manejo efetivo de sistemas agroflorestais com dendê na região amazônica.(AU)

Spatial dependency and correlation of properties of soil cultivated with oil palm, Elaeis guineensis, in agroforestry systems in the eastern Brazilian Amazon / Dependência espacial e correlação das propriedades do solo cultivado com dendezeiro, Elaeis guineensis, em sistemas agroflorestais na Amazônia Oriental

Geostatistics is a tool that can be used to produce maps with the distribution of nutrients essential for the development of plants. Therefore, the present study aimed to analyze the spatial variation in chemical attributes of soils under oil palm cultivation in agroforestry systems in the eastern Brazilian Amazon, and their spatial dependence pattern. Sixty spatially standardized and georeferenced soil samples were collected at each of three sampling sites (DU1, DU2, and DU3) at 0-20 cm depth. Evaluated soil chemical attributes were pH, Al3+, H+Al, K+, Ca2+, Mg2+, cation exchange capacity (CEC), P, and organic matter (OM). The spatial dependence of these variables was evaluated with a semivariogram analysis, adjusting three theoretical models (spherical, exponential, and Gaussian). Following analysis for spatial dependence structure, ordinary kriging was used to estimate the value of each attribute at non-sampled sites. Spatial correlation among the attributes was tested using cokriging of data spatial distribution. All variables showed spatial dependence, with the exception of pH, in one sampling site (DU3). Highest K+, Ca2+, Mg2+, and OM levels were found in the lower region of two sampling sites (DU1 and DU2). Highest levels of Al3+ and H+Al levels were observed in the lower region of sampling site DU3. Some variables were correlated, therefore cokriging proved to be efficient in estimating primary variables as a function of secondary variables. The evaluated attributes showed spatial dependence and correlation, indicating that geostatistics may contribute to the effective management of agroforestry systems with oil palm in the Amazon region.

A geoestatística é uma ferramenta utilizada para produzir mapas de distribuição de nutrientes essenciais para o desenvolvimento das plantas. O presente estudo teve como objetivo analisar a variação espacial dos atributos químicos do solo sob cultivo de dendê em sistemas agroflorestais na Amazônia Oriental brasileira, e seu padrão de dependência espacial. Sessenta amostras de solo espacialmente padronizadas e georreferenciadas foram coletadas em cada um de três locais de amostragem (UD1, UD2 e UD3), na profundidade de 0-20 cm. Os atributos químicos do solo avaliados foram: pH, Al3+, H+Al, K+, Ca2+, Mg2+, capacidade de troca catiônica do solo (CTC), P e matéria orgânica (MO). A dependência espacial dos atributos foi avaliada com análise semivariográfica, ajustando-se três modelos teóricos (esférico, exponencial e gaussiano). Após a análise de dependência espacial, a krigagem ordinária foi empregada para estimar os valores de cada atributo em locais não amostrados. A correlação espacial entre os atributos foi testada utilizando a cokrigagem para espacialização dos dados. Todas as variáveis mostraram dependência espacial, exceto pH em UD3. Os maiores teores de K+, Ca2+, Mg2+ e MO foram encontrados na região mais baixa da paisagem, em UD1 e UD2. Os maiores teores de Al3+ e H+Al foram observados na região mais baixa da paisagem, em UD3. Algumas variáveis foram correlacionadas, portanto a cokrigagem mostrou-se eficiente na estimativa das variáveis primárias em função das secundárias. Os atributos avaliados mostraram dependência e correlação espacial, indicando que a geoestatística pode contribuir para o manejo efetivo de sistemas agroflorestais com dendê na região amazônica.

The use of Pedotransfer functions and the estimation of carbon stock in the Central Amazon region

Computer models have been used to assess soil organic carbon (SOC) stock change. Commonly, models require to determine soil bulk density (Db), a variable that is often lacking in soil data bases. To partly overcome this problem, pedotransfer functions (PTFs) are developed to estimate Db from other easily available soil properties. However, only a few studies have determined the accuracy of these functions and quantified their effects on the final quality of the spatial variability maps. In this context, the objectives of this study were: i) to develop one PTF to estimate Db in soils of the Brazilian Central Amazon region; ii) to compare the performance of PTFs generated with three other models generally used to estimate Db in soils of the Amazon region; and iii) to quantify the effect of applying these PTFs on the spatial variability maps of SOC stock. Using data from 96 soil profiles in the Urucu river basin in Brazil, a multiple linear regression model was generated to estimate Db using SOC, pH, sum of basic cations, aluminum (Al+3), and clay content. This model outperformed the three other PTFs published in the literature. The average estimation error of SOC stock using our model was 0.03 Mg C ha1, which is markedly lower than the other PTFs (1.06 and 1.23 Mg C ha1, or 15 % and 17 %, respectively). Thus, the application of a non-validated PTF to estimate Db can introduce an error that is large enough to skew the significant difference in soil carbon stock change.

The use of Pedotransfer functions and the estimation of carbon stock in the Central Amazon region

Computer models have been used to assess soil organic carbon (SOC) stock change. Commonly, models require to determine soil bulk density (Db), a variable that is often lacking in soil data bases. To partly overcome this problem, pedotransfer functions (PTFs) are developed to estimate Db from other easily available soil properties. However, only a few studies have determined the accuracy of these functions and quantified their effects on the final quality of the spatial variability maps. In this context, the objectives of this study were: i) to develop one PTF to estimate Db in soils of the Brazilian Central Amazon region; ii) to compare the performance of PTFs generated with three other models generally used to estimate Db in soils of the Amazon region; and iii) to quantify the effect of applying these PTFs on the spatial variability maps of SOC stock. Using data from 96 soil profiles in the Urucu river basin in Brazil, a multiple linear regression model was generated to estimate Db using SOC, pH, sum of basic cations, aluminum (Al+3), and clay content. This model outperformed the three other PTFs published in the literature. The average estimation error of SOC stock using our model was 0.03 Mg C ha1, which is markedly lower than the other PTFs (1.06 and 1.23 Mg C ha1, or 15 % and 17 %, respectively). Thus, the application of a non-validated PTF to estimate Db can introduce an error that is large enough to skew the significant difference in soil carbon stock change.(AU)

Estatística descritiva e estacionaridade em variáveis geoquímicas ambientais / Descriptive statistics and stationarity in environmental geochemical variables

RESUMO O objetivo deste trabalho foi analisar os dados de atributos geoquímicos a fim de verificar sua estacionaridade e correlacionar a normalidade estatística com o uso da técnica de krigagem ordinária. A escolha da krigagem ordinária como método geoestatístico aplicado ao trabalho deve-se ao fato de essa ser aconselhada para a realização de estudos em áreas onde existam dados com variáveis que possam apresentar dependência espacial, como é o caso das variáveis geoquímicas, e por ser indicada para dados que apresentam estacionaridade. A metodologia utilizada para a realização desta pesquisa envolveu, além da revisão de literatura, a obtenção de dados dos metais-traço (Cu, Zn, Mn, Fe, Cr e Pb) extraídos parcialmente de amostras superficiais (0 a 10 cm) de solos e sedimentos coletados em campo. Também foram determinados os valores de pH, salinidade, nitrogênio total, fósforo, matéria orgânica e granulometria. Foram conduzidas análises estatísticas, construções de semivariogramas, aplicação da krigagem ordinária e, por fim, validação cruzada para medir a incerteza da medição prévia dos dados. Neste trabalho, por meio dos variogramas, comprovou-se que, apesar de os dados não serem normais, eles apresentaram estacionaridade. Além disso, o parâmetro da estatística descritiva que mais possui correlação direta com a krigagem ordinária é a variância.

ABSTRACT The aim of this work was to analyze geochemical data in order to check their stationarity and to correlate the statistical normality using the ordinary kriging technique. The ordinary kriging technique was chosen as the geostatistical method applied to work because such technique is advised for studies in areas where there are data with variables that might present spatial dependence, like the geochemical variables, and also because it is indicated for data presenting stationarity. The methodology used for this research involved, besides literature review, data collection of trace metals (Cu, Zn, Mn, Fe, Cr and Pb) that were partially extracted from surface samples (0 to 10 cm) of soils and sediments collected in the field. We also determined the values of pH, salinity, total nitrogen, phosphorus, organic matter and particle size. Statistical analyzes, semivariogram development, ordinary kriging use and, lastly, cross validation were performed to measure the uncertainty of the previous measurement of data. It was found, in this work, by means of the variograms that although data were ordinary, they showed stationarity. In addition, the parameter of descriptive statistics that mostly correlates directly with the ordinary kriging is variance.

Positioning of sensors for control of ventilation systems in broiler houses: a case study

Ventilation systems are incorporated at intensive poultry farms to control environment conditions and thermal comfort of broilers. The ventilation system operates based on environmental data, particularly measured by sensors of temperature and relative humidity. Sensors are placed at different positions of the facility. Quality, number and positioning of the sensors are critical factors to achieve an efficient performance of the system. For this reason, a strategic positioning of the sensors associated to controllers could support the maintenance and management of the microclimate inside the facility. This research aims to identify the three most representative points for the positioning of sensors in order to support the ventilation system during the critical period from 12h00 to 15h00 on summer days. Temperature, relative humidity and wind speed were measured in four different tunnel ventilated barns at the final stage of the production cycle. The descriptive analysis was performed on these data. The Temperature and Humidity Index (THI) was also calculated. Then, the geostatistical analysis of THI was performed by GS+ and the position of sensors was determined by ordinary kriging. The methodology was able to detect the most representative points for the positioning of sensors in a case study (southeastern Brazil). The results suggested that this strategic positioning would help controllers to obtain a better inference of the microclimate during the studied period (the hottest microclimate), considered critical in Brazil. In addition, these results allow developing a future road map for a decision support system based on 24 h monitoring of the ventilation systems in broiler houses.

Positioning of sensors for control of ventilation systems in broiler houses: a case study

Ventilation systems are incorporated at intensive poultry farms to control environment conditions and thermal comfort of broilers. The ventilation system operates based on environmental data, particularly measured by sensors of temperature and relative humidity. Sensors are placed at different positions of the facility. Quality, number and positioning of the sensors are critical factors to achieve an efficient performance of the system. For this reason, a strategic positioning of the sensors associated to controllers could support the maintenance and management of the microclimate inside the facility. This research aims to identify the three most representative points for the positioning of sensors in order to support the ventilation system during the critical period from 12h00 to 15h00 on summer days. Temperature, relative humidity and wind speed were measured in four different tunnel ventilated barns at the final stage of the production cycle. The descriptive analysis was performed on these data. The Temperature and Humidity Index (THI) was also calculated. Then, the geostatistical analysis of THI was performed by GS+ and the position of sensors was determined by ordinary kriging. The methodology was able to detect the most representative points for the positioning of sensors in a case study (southeastern Brazil). The results suggested that this strategic positioning would help controllers to obtain a better inference of the microclimate during the studied period (the hottest microclimate), considered critical in Brazil. In addition, these results allow developing a future road map for a decision support system based on 24 h monitoring of the ventilation systems in broiler houses.(AU)

Spatial prediction of soil properties in two contrasting physiographic regions in Brazil

This study compared the performance of ordinary kriging (OK) and regression kriging (RK) to predict soil physical-chemical properties in topsoil (0-15 cm). Mean prediction of error and root mean square of prediction error were used to assess the prediction methods. Two watersheds with contrasting soil-landscape features were studied, for which the prediction methods were performed differently. A multiple linear stepwise regression model was performed with RK using digital terrain models (DTMs) and remote sensing images in order to choose the best auxiliary covariates. Different pedogenic factors and land uses control soil property distributions in each watershed, and soil properties often display contrasting scales of variability. Environmental covariables and predictive methods can be useful in one site study, but inappropriate in another one. A better linear correlation was found at Lavrinha Creek Watershed, suggesting a relationship between contemporaneous landforms and soil properties, and RK outperformed OK. In most cases, RK did not outperform OK at the Marcela Creek Watershed due to lack of linear correlation between covariates and soil properties. Since alternatives of simple OK have been sought, other prediction methods should also be tested, considering not only the linear relationships between covariate and soil properties, but also the systematic pattern of soil property distributions over that landscape.

Spatial prediction of soil properties in two contrasting physiographic regions in Brazil

This study compared the performance of ordinary kriging (OK) and regression kriging (RK) to predict soil physical-chemical properties in topsoil (0-15 cm). Mean prediction of error and root mean square of prediction error were used to assess the prediction methods. Two watersheds with contrasting soil-landscape features were studied, for which the prediction methods were performed differently. A multiple linear stepwise regression model was performed with RK using digital terrain models (DTMs) and remote sensing images in order to choose the best auxiliary covariates. Different pedogenic factors and land uses control soil property distributions in each watershed, and soil properties often display contrasting scales of variability. Environmental covariables and predictive methods can be useful in one site study, but inappropriate in another one. A better linear correlation was found at Lavrinha Creek Watershed, suggesting a relationship between contemporaneous landforms and soil properties, and RK outperformed OK. In most cases, RK did not outperform OK at the Marcela Creek Watershed due to lack of linear correlation between covariates and soil properties. Since alternatives of simple OK have been sought, other prediction methods should also be tested, considering not only the linear relationships between covariate and soil properties, but also the systematic pattern of soil property distributions over that landscape.(AU)

Spatial variation and area definition of nutrient extraction by Marandu grass biomass / Variação espacial e definição de zonas de extração de nutrientes pela fitomassa do capim-Marandu

O objetivo foi quantificar, descrever e identificar zonas de extração de nutrientes pela fitomassa da Brachiaria brazantha cv. Marandu em sistemas de integração floresta-pasto em região de transição Cerrado-Amazônia sobre Neossolo Quartzarênico Órtico típico, por meio de técnicas de geoestatística, de análise de componentes principais e da lógica de agrupamento não hierárquica de fuzzy k-médias. As avaliações foram realizadas em dois sistemas de integração floresta-pasto originários da associação de Brachiaria brizantha cv. Marandu e vegetação nativa raleada com 50% e 75% (IFP-I e IFP-II, respectivamente) de sombreamento e em pastagem de Brachiaria brizantha cv. Marandu em monocultivo. Para cada tratamento foi demarcada uma área de 4.000 m² (40 x 100 m) que continham 32 pontos de coleta dispostos em malha de 4 x 25 m. Em cada ponto previamente marcado nos tratamentos avaliados se estimou as taxas de alongamento de lâminas foliares, senescência foliar e de alongamento de colmo. Ao final de cada ciclo produtivo foram determinados nas lâminas foliares e no colmo os teores de nutrientes (N, P, K, Ca e Mg). A extração de nutrientes foi calculada em função das taxas de produção bruta de forragem, de acúmulo de forragem e de folhas. Zonas de extração de nutrientes minerais pela fitomassa da Brachiaria brizantha cv. Marandu são definidas utilizando-se técnicas de geoestatística, de análise de componentes principais e da lógica de agrupamento não hierárquica de fuzzy k-médias. Assim o uso desses procedimentos é viável na definição e delimitação de zonas homogêneas dentro e entre os sistemas de produção de gramínea estudados.(AU)

The present study aimed to quantify, describe and identify areas of nutrient extraction by Brachiaria brizantha cv. Marandu biomass in integrated forest-pasture systems from a Cerrado-Amazon transition region with Typic Quartzipsamment soil by using geostatistical techniques, principal components analysis and non-hierarchical fuzzy k-means clustering. The evaluations were conducted in two integrated forest-pasture systems from an association with Brachiaria brizantha cv. Marandu and native vegetation thinned with 50% and 75% (integrated forest production-I (IFP-I) and IFP-II, respectively) shading and in Brachiaria brizantha cv. Marandu monoculture. For each treatment, an area of 4,000 m² (40 x 100 m) was demarcated containing 32 collection points arranged in a 4 x 25 m mesh. At each point, the rates of leaf elongation, senescence and stem elongation were estimated. At the end of each production cycle, the nutrient content (N, P, K, Ca and Mg) was determined in the leaf blades and stem. The nutrient uptake was calculated according to the rates of gross forage production, forage accumulation and leaf accumulation. The nutrient extraction zones of Brachiaria brizantha cv. Marandu biomass were defined using geostatistical techniques, principal components analysis and non-hierarchical fuzzy k-means clustering. Thus, the use of these procedures is feasible for the definition and delimitation of homogeneous zones within and between the pasture production systems studied.(AU)

Spatial variation and area definition of nutrient extraction by Marandu grass biomass / Variação espacial e definição de zonas de extração de nutrientes pela fitomassa do capim-Marandu

O objetivo foi quantificar, descrever e identificar zonas de extração de nutrientes pela fitomassa da Brachiaria brazantha cv. Marandu em sistemas de integração floresta-pasto em região de transição Cerrado-Amazônia sobre Neossolo Quartzarênico Órtico típico, por meio de técnicas de geoestatística, de análise de componentes principais e da lógica de agrupamento não hierárquica de fuzzy k-médias. As avaliações foram realizadas em dois sistemas de integração floresta-pasto originários da associação de Brachiaria brizantha cv. Marandu e vegetação nativa raleada com 50% e 75% (IFP-I e IFP-II, respectivamente) de sombreamento e em pastagem de Brachiaria brizantha cv. Marandu em monocultivo. Para cada tratamento foi demarcada uma área de 4.000 m² (40 x 100 m) que continham 32 pontos de coleta dispostos em malha de 4 x 25 m. Em cada ponto previamente marcado nos tratamentos avaliados se estimou as taxas de alongamento de lâminas foliares, senescência foliar e de alongamento de colmo. Ao final de cada ciclo produtivo foram determinados nas lâminas foliares e no colmo os teores de nutrientes (N, P, K, Ca e Mg). A extração de nutrientes foi calculada em função das taxas de produção bruta de forragem, de acúmulo de forragem e de folhas. Zonas de extração de nutrientes minerais pela fitomassa da Brachiaria brizantha cv. Marandu são definidas utilizando-se técnicas de geoestatística, de análise de componentes principais e da lógica de agrupamento não hierárquica de fuzzy k-médias. Assim o uso desses procedimentos é viável na definição e delimitação de zonas homogêneas dentro e entre os sistemas de produção de gramínea estudados.

The present study aimed to quantify, describe and identify areas of nutrient extraction by Brachiaria brizantha cv. Marandu biomass in integrated forest-pasture systems from a Cerrado-Amazon transition region with Typic Quartzipsamment soil by using geostatistical techniques, principal components analysis and non-hierarchical fuzzy k-means clustering. The evaluations were conducted in two integrated forest-pasture systems from an association with Brachiaria brizantha cv. Marandu and native vegetation thinned with 50% and 75% (integrated forest production-I (IFP-I) and IFP-II, respectively) shading and in Brachiaria brizantha cv. Marandu monoculture. For each treatment, an area of 4,000 m² (40 x 100 m) was demarcated containing 32 collection points arranged in a 4 x 25 m mesh. At each point, the rates of leaf elongation, senescence and stem elongation were estimated. At the end of each production cycle, the nutrient content (N, P, K, Ca and Mg) was determined in the leaf blades and stem. The nutrient uptake was calculated according to the rates of gross forage production, forage accumulation and leaf accumulation. The nutrient extraction zones of Brachiaria brizantha cv. Marandu biomass were defined using geostatistical techniques, principal components analysis and non-hierarchical fuzzy k-means clustering. Thus, the use of these procedures is feasible for the definition and delimitation of homogeneous zones within and between the pasture production systems studied.

Integrating forest-pasture: Spatial analysis and delineation of zones of litter production and nutrient return / Integração floresta-pasto: análise espacial e delineamento de zonas de produção de serapilheira e retorno de nutrientes

This study aimed to quantify, describe, and identify plant litter production and nutrient accumulation zones in different forest-pasture integration (FPI) systems and forest strata of the Cerrado-Amazon transition on typical orthic Quartzarenic Neosol using spatial analysis, principal component analysis, and non-hierarchical fuzzy k-mean clustering logic techniques. The evaluations were performed at two FPI systems comprising a combination of Brachiaria brizantha cv. Marandu and thinned native vegetation with 50 and 75% (FPI-I and FPI-II, respectively) shade in an original thinned forest (NFI) and in an original intact forest (NF-II) with 80 and 95% shade, respectively. An area of 4,000 m² (40 x 100 m) that contained 32 sampling points arranged in a 4 x 25 m grid was demarcated for each treatment. Plant litter was collected using 32 collectors installed at equidistant points. Twelve nylon bags were placed on the soil surface at each point to evaluate the plant litter decomposition, totaling 384 bags per treatment. It was possible to quantify, describe, and define plant litter production and nutrient accumulation zones in different FPI systems and forest strata of the Cerrado-Amazon transition on orthic Quartzarenic Neosol using geostatistical analysis, principal components, and non-hierarchical fuzzy k-mean clustering logic procedures.

O objetivo foi quantificar, descrever e identificar zonas de produção de serapilheira e acúmulo de nutrientes em diferentes sistemas de integração floresta-pasto e estratos de floresta de transição Cerrado-Amazônia sobre Neossolo Quartzarênico Órtico típico, utilizando técnicas de análise espacial, de análise de componentes principais e da lógica de agrupamento não hierárquica de fuzzy k-médias. As avaliações foram realizadas em dois sistemas de integração floresta-pasto originários da associação de Brachiaria brizantha cv. Marandu e vegetação nativa raleada com 50% e 75% (IFP-I e IFP-II, respectivamente) de sombreamento numa floresta original raleado (FN-I) e em floresta original intacta (FN-II) com 80% e 95% de sombreamento, respectivamente. Para cada tratamento foi demarcada uma área de 4.000 m² (40 x 100 m) que continham 32 pontos de coleta dispostos em malha de 4 x 25 m. A serapilheira foi coletada por meio da instalação nos pontos equidistantes de 32 coletores. Para avaliar a decomposição da serapilheira foram distribuídas 12 sacolas de náilon na superfície do solo em cada ponto, totalizando 384 sacolas por tratamento. É demonstrado que é possível quantificar, descrever e definir zonas de produção de serapilheira e acúmulo de nutrientes em diferentes sistemas de integração floresta-pasto e estratos de floresta de transição Cerrado-Amazônia sobre Neossolo Quartzarênico Órtico, utilizandoos procedimentos de análise geoestatística, de componentes principais e da lógica de agrupamento não hierárquica de fuzzy k-médias.