RESUMO Compreender o solo, os atributos das plantas e a dinâmica das culturas de cenoura é vital para otimizar praticas de manejo a sitio especifico e melhorar o rendimento das culturas e a qualidade do solo. Este estudo teve como objetivo verificar a dependência e a variabilidade espacial entre a produtividade da cenoura irrigada e os atributos físicos do solo em um Latossolo Argiloso. A pesquisa ocorreu durante a safra 2021 em uma área comercial de produção de cenoura em Campos Altos, MG, Brasil. Foram estabelecidos cem pontos amostrais dentro da área irrigada, distribuídos em uma área quadrada de 40.000 m², posicionados nos centros de grades de 20 x 20 m. O estudo revelou alta produtividade na cultura da cenoura irrigada (99,74 t ha-1) com variabilidade moderada. Os atributos do solo apresentaram uma gama de heterogeneidade, variando de baixa a extremamente alta, dependendo da variável avaliada, determinada pelo coeficiente de variação. Dentre as variáveis que apresentam dependência espacial, a densidade de partículas apresentou alcance mínimo de 40 m, o que é recomendado para futuros estudos de cultivo de cenoura irrigada em Latossolo Argiloso. A disponibilidade total de água no solo demonstrou correlação espacial positiva e mostrou-se a variável recomendada para estimar a variabilidade espacial da produtividade da cultura da cenoura. Argiloso 202 Altos MG Brasil 40000 000 40.00 m² m 2 99,74 9974 99 74 (99,7 ha1 ha 1 ha-1 moderada heterogeneidade avaliada variação 4 mostrouse mostrou se 4000 00 40.0 99,7 997 9 7 (99, ha- 400 0 40. 99, (99 (9 (

ABSTRACT Understanding soil, plant attributes, and carrot crop dynamics is vital for optimizing site-specific management practices and enhancing crop yield and soil quality. This study aimed to ascertain the dependence and spatial variability between irrigated carrot yield and soil physical attributes in a clayey Oxisol. The research took place during the 2021 growing season in a commercial carrot production area in Campos Altos, MG, Brazil. One hundred sampling points were established within the irrigated area, distributed across a square expanse of 40,000 m², positioned at the centers of 20 × 20 m grids. The study revealed high yield in the irrigated carrot crop (99.74 t ha-1) with moderate variability. Soil attributes displayed a range of heterogeneity, ranging from low to extremely high, contingent on the variable assessed, as determined by the coefficient of variation. Among the variables exhibiting spatial dependence, particle density exhibited a minimum range of 40 m, which is recommended for further studies on irrigated carrot cultivation in a clayey Oxisol. Total soil water availability demonstrated a positive spatial correlation and proved to be the recommended variable for estimating the spatial variability of carrot crop yield. sitespecific site specific quality Oxisol 202 Altos MG Brazil 40000 000 40,00 m² 2 grids 99.74 9974 99 74 (99.7 ha1 ha 1 ha-1 heterogeneity assessed variation 4 4000 00 40,0 99.7 997 9 7 (99. ha- 400 0 40, 99. (99 (9 (

Resumen Los modelos de proyección estructurados (MPE) son una herramienta poderosa para investigar la dinámica de las poblaciones estructuradas, lo que los hace ideales para estudiar las especies vegetales, abarcando su variedad de formas de vida, tamaños, longevidad y complejidad del ciclo de vida. Los MPE son una de las herramientas más versátiles de la ecología vegetal, con cientos de especies estudiadas y una gran variedad de formulaciones alternativas para diferentes preguntas y objetivos. Revisamos algunas consideraciones conceptuales y metodológicas sobresalientes sobre la construcción y uso de los MPE, incluyendo los modelos matriciales de proyección, que son discretos, y los modelos integrales de proyección, que son continuos. Discutimos la selección de la variable de estado y la estimación de parámetros, especialmente aquellos que involucran transiciones difíciles de observar, tales como la cuantificación de la reproducción y la mortalidad de los individuos hacia el final de su ciclo de vida. Debido a la creciente importancia de investigar las tendencias poblacionales en un mundo que cambia rápidamente, destacamos el uso de los MPE tanto en un contexto ambiental como cuando las poblaciones se alejan de su equilibrio. El papel de la densodependencia recibe especial atención debido a que suele correlacionarse con el ambiente, potencialmente confundiendo ambos efectos. De igual modo, desentrañar los diferentes efectos ambientales plantea complicaciones propias, dificultando la comprobación de las relaciones de causalidad. Las alternativas disponibles se ilustran considerando la selección de variables, muestreo y tipos de modelos adecuados para diferentes propósitos.

Abstract Structured projection models (SPMs) are a powerful tool to investigate the dynamics of structured populations, which makes them ideal for the study of plant species spanning their range of life forms, sizes, longevity, and life cycle complexity. They are one of the most versatile tools in plant ecology, with hundreds of species studied so far and a wide variety of alternative formulations for different questions and purposes. We revise some of the most salient conceptual and methodological issues in the construction and use of SPMs including both discrete matrix projection models and continuous integral projection models. Consideration is given to the selection of the state variable and the estimation of parameters, especially those involving transitions difficult to observe in the field, such as the quantification of offspring production and the rarely observed mortality of individuals towards the end of the life cycle. Due to the growing importance of investigating population trends in a rapidly changing world, we highlight the use of SPMs for populations under a variety of environmental influences and/or away from their expected equilibrium. The presumed role of population density receives special attention because it often correlates with features of the environment, thus potentially confounding the two effects. Similarly, disentangling the various environmental effects poses challenges of its own, making it difficult to prove causality. The alternatives available are illustrated considering the selection of variables, samples, and model type suitable for specific purposes.

RESUMO Os sensores utilizados na área de agricultura de precisão são capazes de realizar leituras pontuais georreferenciadas, determinando a condutividade elétrica, pH e matéria orgânica, sendo equipamentos de alta capacidade operacional, mas ainda com poucas informações sobre a qualidade dos dados coletados. Objetivou-se estabelecer correlações e diferenças entre dados de condutividade elétrica, pH e matéria orgânica coletados por sensor e obtidos por meio de análises laboratoriais. Os resultados foram analisados por meio de correlações estatísticas, análises geoestatísticas e geração de mapas pelo método de interpolação por krigagem de condutividade elétrica, pH e matéria orgânica, utilizando-se programas dedicados. O sensor demostrou que os dados coletados de condutividade elétrica, pH e matéria orgânica são confiáveis e robustos, devido à alta dependência espacial e à correta distância de amostragem comprovadas pelos valores de alcance.

ABSTRACT Sensors used in precision agriculture can perform readings of georeferenced points aiming to determine the electrical conductivity, pH and organic matter. These devices have a high operational capacity, but with little information on the quality of their collected data. This study aimed to establish correlations and differences among electrical conductivity, pH and organic matter data collected by sensor and obtained by laboratory analyses. The results were analyzed by statistical correlations, geostatistical analyses and map generation by the kriging interpolation method of electrical conductivity, pH and organic matter, using dedicated softwares. The sensor showed that the data collected for electrical conductivity, pH and organic matter are reliable and robust, due to the high spatial dependence and correct sampling distance confirmed by the range values.

Abstract Agriculture needs methodologies that assist in the determination of soil attributes and variability mapping attributes with greater levels of detail. Therefore, the objective of this research was to evaluate magnetic susceptibility as auxiliary variable for estimating soil attributes in areas of Indian Black Earths in the south of Amazonas State. Three Indian Black Earth areas are located in the municipalities of Apuí and Manicoré - Amazonas, under uses with coffee, cocoa and pasture. The soils were collected at the crossing points in the depth of 0.00 - 0.20 m, making a total of 88 sampling points/area, and totaling 264 samples. The points were georeferenced for geostatistical modeling. After that, physical and chemical analyzes were performed to obtain the values of soil and magnetic susceptibility attributes. Descriptive statistics, Pearson correlation, linear regression and geostatistical analyzes were applied for Pedotransfer Function modeling and the spatial variability of the analyzed attributes. Magnetic susceptibility showed a high degree of spatial dependence in the study areas, high range values, correlating with most of the assessed attributes, mainly physical, indicating potential in the prediction of the attributes in these environments. Pedotransfer functions vary among IBE’s sites in attribute prediction, ensuring moderate estimates for predicting soil attributes in IBE’s areas.

ABSTRACT. Spatial data (e.g., phytopathogenic data) do not always meet assumptions such as stationarity, isotropy and Gaussian distribution, thereby requiring complex spatial methods and models. Some deterministic assumption-free methods such as the inverse distance weighting can also be applied to predict spatial data, but their output is limited for graphical solutions (mapping). We adapted a computer-based prediction method called Circular Variable Radius Moving Window (CVRMW) that is based on two others: moving window kriging (MWK) and inverse squared-distance weighting (ISDW). The algorithm is developed to meet an objective function that minimizes the index of variation of the spatial observations inside the moving window. A code in R language is presented and thoroughly described. The outputs include the range of the spatial dependence as the radius calculated at every target location and the standard error of the predicted values, mapped to provide a useful tool for spatial exploratory analysis. The method does not make any assumptions about the spatial process, and it is an alternative for dealing with spatial heterogeneity.

Resumen Los modelos digitales de elevación mejoran la precisión en el análisis del terreno. Este trabajo tuvo como objetivo comparar diferentes métodos de interpolación utilizando criterios estadísticos en un levantamiento topográfico de 339 puntos levantados con estación total en la zona de San Juan de Lagunillas (Venezuela). Se documentó la existencia de un proceso de tendencia significativa con autocorrelación espacial modelada mediante un semivariograma gaussiano isotrópico. Los kriging consiguieron residuales menores a un error mínimo tolerable igual 0.1 m. El kriging residual fue el mejor evaluado en la validación cruzada con exclusión (error medio absoluto de 0.71 m). El kriging disyuntivo tuvo menor media del error pero un amplio rango del error y el mayor error medio absoluto (12.8 m). Los otros kriging tienen medias de la varianza del error superiores a 1.3 m y errores mínimos absolutos superiores a 0.85 m. Debido a la alta dependencia en la forma de especificación de los modelos se recomiendan las ayudas gráficas para un mejor ajuste.

Abstract Digital Elevation Models improve accuracy in terrain analysis. This work compared different interpolation methods using statistical criteria in a topographic survey of 339 points raised with a total station in the “San Juan de Lagunillas” area (Venezuela). The existence of a signiftablaicant trend process with spatial autocorrelation modeled by an isotropic Gaussian semivariogram was documented. The kriging allowed to obtain residuals less than a minimum tolerable error equal to 0.1 m. The residual kriging was the best evaluated in cross validation with exclusion (absolute mean error of 0.71 m). The disjunctive kriging showed a lower error average but a wider error range and the highest mean absolute error (12.8 m). The other kriging showed mean error variance greater than 1.3 m and absolute minimum errors greater than 0.85 m. Due to the high dependence on the model specification form, graphics are recommended for a better fit.

ABSTRACT Spatial and temporal variation of the physical and chemical conditions of coastal karst wetland ecosystems, which annually range from flooded to completely dry, generate a very dynamic fish community structure. We assessed the relative influence of spatial dependence and environmental factors on fish community structure in a seasonally flooded tropical karst system on the north-western coast of the Yucatan Peninsula, Mexico. Sampling was carried out between November 2009 and April 2010, while the area was inundated by seasonal floodwater. Fish biomass, abundance and species richness, as well as environmental variables and geographic location, were recorded. A variation partitioning analysis was performed to assess the influence of the spatial and environmental variables on the fish community using multiple regression, and a principal coordinates analysis of neighbor matrices (PCNM). Spatial factors had a greater influence on the changes in the community structure than the environmental factors. After spatial variation, environmental effects from conductivity, oxygen saturation, temperature and depth further shaped the community. These results imply that, despite the diversity of niches and wide variation in environmental conditions, the structuring force of the community is the spatial dynamic probably linked to species dispersal mechanisms and reproductive strategies.

ABSTRACT Soil nitrogen (N) variability affects the effective application of N fertilizers. The objective of this research was to determine and assess the spatial dependence of soil N in two different soils using spatial sampling and geostatistics fundamentals. An optimized nested sampling design was applied in two sites, using 16 main stations from where soil samples (0 - 23 cm) were obtained at 1.5, 4.5, 13.5, 40.5, and 121.5 m, at random directions. Soil samples were collected from an Andisol and an Inceptisol (2 x n = 98), and the potentially available N (PAN) was measured by anaerobic soil incubation for 7 days at 40oC (PAN = NH4+ day 7 - NH4+ day 1). The PAN variance components from each distance were calculated by residual maximum likelihood (REML), and then accumulated to plot an approach to the variogram. The results showed a wide range of values for PAN at both sites. The Andisol site registered high PAN levels, with a mean value of 32.92 mg NH4+ kg soil-1, which was five times larger than in the Inceptisol soil, probably associated with a larger soil organic matter content. The limit of the spatial dependence was 13.5 m for the Andisol, and 40.5 m for the Inceptisol soil, corresponding to the 59% and 35% of the process variance, respectively.

RESUMEN La alta variabilidad del nitrógeno (N) en el suelo afecta la aplicación efectiva de fertilizantes nitrogenados. El objetivo de esta investigación fue determinar y evaluar la dependencia espacial del N en dos tipos de suelo. Para ello se utilizó un diseño espacial anidado optimizado, con 16 estaciones de muestreo, y en direcciones aleatorias se tomaron muestras de suelo (0-23 cm) a intervalos de distancia de 1,5; 4,5; 13,5; 40,5; y 121,5 m. Los suelos evaluados fueron un Andisol y un Inceptisol (2 x n = 98), en los que se midió el potencial de nitrógeno disponible (PND) a través de incubación anaeróbica de suelo por 7 días a 40oC (PND = NH4+ día 7 - NH4+ día 1). La dependencia espacial del PND en cada uno de los sitios fue establecida mediante la acumulación de varianza de cada distancia, calculada a través de un análisis de máxima probabilidad residual (REML), y posterior aproximación al variograma. Los resultados mostraron un rango amplio de valores en ambos sitios. El sitio Andisol registró un elevado PND, con un valor promedio de 32,92 mg NH4+ kg-1, cinco veces mayor que en el Inceptisol, lo que se explicó principalmente por un mayor contenido de materia orgánica. La dependencia espacial del PND para ambos sitios se obtuvo a intervalos de 13,5 y 40,5 m, logrando cuantificar un 59% de la variabilidad del proceso en el sitio Andisol, y tan sólo un 35% en el sitio Inceptisol.

RESUMO Avaliou-se o uso da análise fractal como ferramenta na determinação de padrões na escala de pastejo em pastagens naturais submetidas a diferentes manejos. Os tratamentos testados em Santa Maria foram: pastejo com queima, pastejo sem queima, exclusão com queima, exclusão sem queima. Em Bagé, os tratamentos avaliados foram: pastagem natural e pastagem natural com introdução de azevém, trevo-branco e cornichão. A caracterização da composição florística da pastagem foi realizada pelo método Botanal. A diversidade da pastagem foi calculada pelos índices de Shannon (H’) e equitabilidade. A informação da dimensão fractal foi calculada pela regressão entre H’(ε) e o logaritmo natural de ε, sendo a inclinação da linha a informação da dimensão fractal. Os índices de Shannon e equitabilidade demonstraram dependência em relação à área amostral, onde a maior diversidade florística e a homogeneidade da frequência de distribuição de plantas entre espécies foram observadas no intervalo amostral de 0,87 e 1,03m2. A dimensão fractal pode ser uma ferramenta na determinação de padrões na comunidade vegetal na escala reduzida de pastejo. A limitação do emprego dessa técnica para escalas reduzidas é a necessidade de um número maior de repetições.

ABSTRACT The use of fractal analysis was evaluated as a tool in the determination of grazing patterns in natural grasslands submitted to different managements. The treatments tested in Santa Maria were grazing with burning, grazing without burning, exclusion with burning and exclusion without burning. In Bagé, the evaluated treatments were natural pasture and introduction of ryegrass, white clover and birdsfoot trefoil in a natural grassland. The characterization of the floristic composition of the pasture was performed by the BOTANAL method. The pasture diversity was calculated by Shannon (H') and Evenness (J) indexes. The fractal dimension information was calculated by regression between H'(ε) and ε natural algorithm, with the line’s slope being the fractal dimension information. Shannon and Evenness indexes showed dependence on the sample area, where the highest floristic diversity and homogeneity of the distribution frequency of plants between species were observed in the sample range of 0.87 to 1.03m2. The fractal dimension can be a tool in determining patterns in the plant community on the reduced grazing scale. The limitation of the use of this technique for reduced scales is the need for a greater number of repetitions.

Resumen Introducción. La producción lechera en zonas tropicales se caracteriza por una alta dependencia del recurso forrajero, lo que la hace sensible a las variables climáticas, de las cuales existe información limitada sobre su efecto en el rendimiento de razas lecheras especializadas. Objetivo. El objetivo del presente estudio fue evaluar la asociación entre el índice de temperatura y humedad (ITH) y la producción diaria de leche (kgl) de vacas de razas Holstein, Jersey y sus cruces. Materiales y métodos. El estudio se efectuó en las regiones Norte y Central de Costa Rica, con datos recolectados entre 1990 y 2015. Los valores de ITH se obtuvieron mediante modelos predictivos lineales y modelos espaciales de autocorrelación, ajustados sobre 3547 registros mensuales de temperatura máxima y humedad relativa de diecisiete estaciones meteorológicas. Se analizaron 6 478 582 registros de kgl provenientes de 418 hatos lecheros, mediante un modelo lineal mixto generalizado (GLMM), que consideró los efectos fijos de la raza, el año y el mes calendario, número de parto, etapa de lactancia, raza×etapa de lactancia, ENOS (Efecto “El Niño”), ITH y raza×ITH, además del efecto aleatorio de la vaca. Resultados. Todos los factores presentaron efecto altamente significativo (p<0,0001) sobre la kgl. Para el rango de ITH entre 72-88 se estimaron reducciones lineales de 0,41 (r2=0,94), 0,36 (r2=0,95) y 0,29 (r2=0,82) kg día-1 para Holstein, Holstein×Jersey y Jersey, respectivamente. No se observaron tendencias significativas en los kgl para ITH <72. Las pérdidas económicas atribuibles a la mayor exposición al estrés en la región norte comparada con la región central se estimaron en $680, $587 y $477 por lactancia por vaca para Holstein, Holstein×Jersey y Jersey, respectivamente. Conclusión. Hubo relación inversa entre el índice de temperatura y humedad, y la producción de leche en vacas Holstein, Jersey y sus cruces, en esta región tropical.

Abstract Introduction. Dairy production in tropical zones is characterized by a high dependence on the forage resource, which makes it sensitive to climatic variables of which there is limited information on their effect on the performance of specialized dairy breeds. Objective. The objective of this study was to evaluate the association between temperature and humidity index (THI) and daily milk production (kgl) of cows breeds Holstein, Jersey, and their crosses. Materials and methods. The study was conducted in the northern and central regions of Costa Rica, with data collected between 1990 and 2015. THI values were obtained using linear predictive models and spatial autocorrelation models, applied to 3,547 monthly records of maximum temperature and relative humidity from seventeen weather stations. 6,478,582 kgl records from 418 dairy herds were analyzed, using a generalized mixed linear model (GLMM), which considered the fixed effects of breed, year and month, birth number, lactation stage, breed × lactation stage, ENSO (Effect “El Niño”), ITH and breed×ITH, in addition to a random effect of the cow. Results. All factors had a highly significant effect (p<0.0001) on kgl. For the ITH range between 72-88, linear reductions of 0.41 (r2=0.94), 0.36 (r2=0.95) and 0.29 (r2=0.82) kg day-1 were estimated for Holstein, Holstein×Jersey and Jersey, respectively. No significant trends were observed for kgl when ITH <72. The economic losses attributable to the greater stress exposure in the north compared to the central region were estimated at $680, $587 and $477 per lactation and cow for Holstein, Holstein×Jersey and Jersey, respectively. Conclusion. There was an inverse relationship between temperature and humidity index and milk production in Holstein, Jersey and crossbreed cows for this tropical region.

ABSTRACT In the study of spatial variability of soil attributes, it is essential to define a sampling plan with adequate sample size. This study aimed to evaluate, through simulated data, the influence of parameters of the geostatistical model and sampling configuration on the optimization process, and resize and reduce the sample size of a sampling configuration of a commercial area composed of 102 points. For this, an optimization process called genetic algorithm (GA) was used to optimize the efficiency of the geostatistical model estimation based on the Fisher information matrix. The simulated data evidenced that the variation of the nugget effect or practical range did not significantly alter the sample size. GA was efficient in reducing the sample size, determining for soil chemical attributes a sample size between 30 and 40 points (29.41 to 39.22% of the initial sampling grid). The presence of spatial dependence was observed for all soil chemical attributes in the two sampling configurations (initial and optimized). The optimized sampling configuration evidenced an increase in trend intensity in the north direction and a more efficient estimation of parameters of the linear spatial regression model.

ABSTRACT The goal of this study was to use the spatial bootstrap method to model the spatial dependence structure of soybean yield and soil chemical attributes in an agricultural area. The study involved developing confidence intervals in probability plots to determine the probability distributions assumed by the data; determine the empirical distributions of the semivariances and model parameters, allowing to obtain statistics and confidence intervals; and to construct maps for the variables. The quantile-quantile plots indicated that the data follows a normal distribution. The confidence intervals for the semivariances helped to model the spatial dependence structure, and the descriptive statistics of the bootstrap replicates of the model parameters allowed to test the consistency of the estimates. The soil chemical attributes (calcium, potassium, and organic matter) were at levels suitable for soybean cultivation. However, the pH was below the ideal range in most of the study area, and water stress during cultivation decreased the mean yield. Therefore, according to the results, a recommendation to the farmer is to correct the soil pH to increase the yield.

RESUMO Em viveiros de mudas de cafeeiro (Coffea arabica) ocorrem condições favoráveis para a ocorrência de epidemias da mancha aureolada (Pseudomonas syringae pv. garcae). Estudar a distribuição espacial de plantas doentes pode auxiliar na adoção de estratégias de manejo. Nesse sentido, a geoestatística tem sido aplicada para modelar a distribuição espacial e estudar aspectos epidemiológicos de doenças de plantas. Assim, este estudo foi desenvolvido para caracterizar o padrão de distribuição espacial da mancha aureolada em viveiro de mudas de cafeeiro. Para isso, o progresso da doença foi monitorido ao longo do tempo em 704 mudas organizadas em linhas e colunas em viveiro. Considerando o diâmetro médio dos recipientes utilizados para produção das mudas, foi realizado o georreferencimento das mudas no viveiro em sistema de coordenadas plano-cartesiano. Os dados de incidência da doença foram submetidos a uma análise exploratória não espacial e à análise geoestatística. O semivariograma isotrópico esférico foi ajustado aos dados e a interpolação dos dados foi realizada por krigagem ordinária para visualizar a distribuição espacial de mudas sintomáticas. Epidemia da doença foi detectada em viveiro durante o período experimental, havendo variabilidade e dependência espacial em relação à distribuição das mudas doentes. Com o decorrer da epidemia, houve aumento da população de plantas doença, número e tamanho dos focos e coalescência desses. Além disso, houve aumento do valor do alcance, patamar e do efeito pepita. Os mapas de krigagem mostraram o progresso da doença e sua variação. A epidemia da mancha aureolada do cafeeiro iniciou com padrão aleatório de distribuição espacial, progredindo para padrão agregado.

ABSTRACT In nurseries of coffee tree seedlings (Coffea arabica), there are favorable conditions for bacterial blight epidemics (Pseudomonas syringae pv. garcae). Studying the spatial distribution of diseased plants can help in the adoption of management strategies. Likewise, geostatistics has been applied to shape the spatial distribution and study epidemiological aspects of plant diseases. Thus, this study was developed to characterize the spatial distribution pattern of bacterial blight in a nursery of coffee tree seedlings. The disease progress was monitored over time in 704 seedlings organized in lines and columns in a nursery. Considering the mean diameter of the pots used for producing seedlings, georeferencing was carried out in Cartesian coordinate system for the seedlings in the nursery. The disease incidence data were subjected to non-spatial exploratory analysis and geostatistical analysis. The spherical isotropic semivariogram model was adjusted to the data and data interpolation was performed by ordinary kriging to visualize the spatial distribution of symptomatic seedlings. Bacterial blight epidemic was detected in the nursery during the experimental period, and there was variability and spatial dependence in relation to the distribution of diseased seedlings. As the epidemic progressed, the population of diseased plants increased, as well as the number and the size of the foci and their coalescence. Besides, there was an increase in the range value, sill and nugget effect. The kriging maps showed the disease progress and its variance. The bacterial blight epidemic of coffee tree started with a random spatial distribution pattern, progressing to an aggregate pattern.

RESUMO A cobertura do solo e o tipo de vegetação influenciam nos fluxos radiativos, na refletância do solo abaixo do dossel e na transmitância do dossel. Neste contexto, este trabalho analisou a variação espacial e temporal da radiação fotossinteticamente ativa refletida pelo solo em uma floresta sazonalmente inundável com dominância de cambará (Vochysia divergens Pohl) no Pantanal Mato-grossense. A área de estudo foi dividida em 5 transectos com 11 pontos amostrais, totalizando 55 pontos medidos de dezembro de 2011 a novembro de 2012. A análise da distribuição espacial da radiação fotossinteticamente ativa refletida pelo solo foi realizada utilizando semivariogramas, aplicando-se o modelo esférico. Encontrou-se correlação negativa das variáveis transmitância do dossel, radiação fotossinteticamente ativa incidente abaixo do dossel e refletida pelo solo com o índice de área foliar e positiva entre radiação fotossinteticamente ativa incidente abaixo do dossel e refletida pelo solo. Os resultados espaciais indicaram dependência espacial da radiação fotossinteticamente ativa refletida nos 9 meses analisados. O efeito pepita foi pequeno nas análises e o alcance mais comum entre os semivariogramas foi 100 m em dezembro/2011, janeiro/2012 e novembro/2012, com o maior alcance ocorrendo no mês de junho/2012. As mudanças da radiação fotossinteticamente ativa refletida podem ser consideradas pela diferença da cota topográfica, ocorrendo acúmulo de umidade no transecto mais baixo, e pela diferença de vegetação encontrada na região, alterando a coloração e/ou cobertura do solo, mudando assim a reflexão.

ABSTRACT Ground cover and the vegetation type influence radiative flux through reflectance off the soil beneath the canopy and by transmittance from the canopy. Here, we analyze spatial and temporal variation in reflected photosynthetically active radiation (PAR), from soil in a seasonally flooded forest dominated by Vochysia divergens Pohl in a wetland area of Mato-Grosso State, Brazil. The study area was divided into 5 transects with 11 sampling points, totaling 55 measured points and samples were taken between December 2011 and November 2012. The spatial distribution of reflected PAR was assessed by applying the spherical model to semivariograms. We found a negative correlation between leaf area index and canopy transmittance, PAR below the canopy and PAR reflected by soil, and a positive correlation between PAR below the canopy and PAR reflected by soil. Our results indicate the spatial dependence of reflected PAR during the 9 months of the study. The most common range between the semivariograms was 100 m in December/2011, January/2011 and November/2012, and the greatest range was in June/2012. These variations in reflected PAR are likely caused by differences in topographical elevation, moisture buildup and vegetation differences which have the capacity to alter soil color and/or cover, thereby altering light reflection.

Resumo: Este estudo tem como objetivo propor um índice de dependência espacial (e sua classificação), a partir do conceito de áreas de correlação espacial, para os modelos Cúbico, Pentaesférico e Wave. O índice, denominado Índice de Dependência Espacial (IDE), abrange os seguintes parâmetros: o alcance (a), o efeito pepita (C 0 ) e contribuição (C 1 ), além de considerar a distância máxima entre pontos amostrados (MD) e o fator modelo (FM). O índice proposto, ao contrário do mais utilizado na literatura, considera a influência do parâmetro alcance para descrever a dependência espacial, destacando a importância desta formulação. A classificação de dependência espacial, construída com base no comportamento assimétrico observado no IDE, foi realizada considerando categorizações da mediana e do 3º quartil do índice. Obtemos a classificação de dependência espacial em termos de fraca, moderada e forte, tal como é normalmente descrito na literatura.

Abstract: This study aims to propose a spatial dependence index (and its classification), from the concept of spatial correlation areas, for the Cubic, Pentaspherical and Wave models. The index, called Spatial Dependence Index (SDI), covers the following parameters: the range (a), the nugget effect (C 0 ) and the contribution (C 1 ), beyond considering the maximum distance (MD) between sampled points and the model factor (MF). The proposed index, unlike the most used in the literature, considers the influence of the range parameter to describe the spatial dependence, highlighting the importance of this formulation. The spatial dependence classification, based on the observed asymmetric behavior in the SDI, was performed considering categorizations from the median and the 3rd quartile of the index. We obtain the spatial dependence classification in terms of weak, moderate, and strong, just as it is usually described in literature.