ABSTRACT: Environmental impacts caused by the addition of rare earth elements (REEs) to agricultural soils are a growing concern. The sedimentary basin of the Gurguéia River is located in one of the last agricultural frontiers in Brazil; nevertheless, data regarding quality reference values (QRVs) for REEs in soils are still scarce. The objective of this study was therefore to determine the natural concentration and establish the QRVs of REEs in soils of Gurguéia watershed, Brazil. Fifty-five composite soil samples were collected at sites under no or minimal anthropic interference. The average REE natural concentrations in soils from the Gurguéia watershed were lower than those found in other regions of Brazil and worldwide, following the order (mg kg−1): Ce (14.01) > Nd (6.19) > La (5.52) > Pr (2.51) > Sm (1.45) > Gd (0.93) > Dy (0.63) > Er (0.42) > Yb (0.39) > Tb (0.28) > Eu (0.26) > Lu (0.20). The parent material was the main factor that controlled the distribution of REEs in soils. The QRVs in soils followed the order (mg kg−1): Ce (18.8) > Nd (7.92) > La (6.32) > Pr (3.3) > Sm (1.97) > Gd (1.35) > Dy (0.85) > Er (0.55) > Yb (0.47) > Tb (0.37) > Lu (0.25). These values serve as a basis to assist the development of legislation, including REE thresholds for Brazilian soils.

Resumo Este trabalho teve como objetivo selecionar modelos de semivariograma para estimar tendências de precipitação mensal no Estado da Paraíba-Brasil usando krigagem comum. A metodologia envolve a aplicação de interpolação geoestatística de registros de precipitação de 51 anos de 69 estações de chuva em todo o estado. A análise de semivariogramas mostrou que meses específicos apresentaram forte dependência espacial (Índice de Dependência Espacial - IDE <25%). As tendências foram submetidas aos seguintes modelos: circular, esférico, pentassesférico, exponencial, gaussiano, quadrático racional, K - Bessel e tetrasspherical. Os melhores modelos de ajuste foram selecionados por validação cruzada e Índice de Comparação de Erros (ICE). Cada conjunto de dados (mês) possuía uma estrutura de dependência espacial específica, o que tornava necessário definir modelos específicos de semivariograma, a fim de aprimorar o ajuste do semivariograma experimental. Além disso, o mapa mensal de tendências foi plotado para justificar os modelos escolhidos.

Abstract This work aimed to select semivariogram models to estimate trends in monthly precipitation in Paraiba State-Brazil using ordinary kriging. The methodology involves the application of geostatistical interpolation of precipitation records of 51 years from 69 rainfall stations across the state. Analysis of semivariograms showed that specific months had a strong spatial dependence (Index of Spatial Dependence - IDE < 25%). The trends were subjected to the following models: circular, spherical, pentaspherical, exponential, Gaussian, rational quadratic, K-Bessel and tetraspherical. The best fit models were selected by cross-validation and Error Comparison Index (ECI). Each data set (month) had a particular spatial dependence structure, which made it necessary to define specific models of semivariogram in order to enhance the adjustment of the experimental semivariogram. Besides, the monthly trend map was plotted to justify the chosen models.

RESUMO O conhecimento da disponibilidade hídrica natural, caracterizada pelas vazões mínimas, é essencial para o planejamento e a gestão dos recursos hídricos. Uma das técnicas hidrológicas mais utilizadas para estimar a vazão é a regionalização, mas a extrapolação das equações de regionalização para além dos limites dos dados usados para estimar os parâmetros do modelo de regressão não é recomendada. Este trabalho propõe um novo método para minimizar o risco associado à extrapolação das equações de regionalização de vazões mínimas. O método baseia-se na utilização de um valor de limiar, que é a máxima vazão mínima específica estimada nas estações fluviométricas utilizadas no estudo de regionalização. Quando a vazão mínima específica estimada a partir da equação de regionalização excede o valor limiar, a vazão mínima é obtida multiplicando-se a área de drenagem pelo valor limiar. Esta restrição impõe um limite físico para as vazões mínimas, o que reduz o risco de superestimar as vazões nas regiões de extrapolação. Um estudo de caso foi realizado para a bacia Urucuia, no Brasil, e os resultados obtidos mostraram um bom desempenho da equação de regionalização, o que reduz o risco de extrapolação.

ABSTRACT Knowledge of natural water availability, which is characterized by low flows, is essential for planning and management of water resources. One of the most widely used hydrological techniques to determine streamflow is regionalization, but the extrapolation of regionalization equations beyond the limits of sample data is not recommended. This paper proposes a new method for reducing overestimation errors associated with the extrapolation of regionalization equations for low flows. The method is based on the use of a threshold value for the maximum specific low flow discharge estimated at the gauging sites that are used in the regionalization. When a specific low flow, which has been estimated using the regionalization equation, exceeds the threshold value, the low flow can be obtained by multiplying the drainage area by the threshold value. This restriction imposes a physical limit to the low flow, which reduces the error of overestimating flows in regions of extrapolation. A case study was done in the Urucuia river basin, in Brazil, and the results showed the regionalization equation to perform positively in reducing the risk of extrapolation.

The breeding habitat of sandflies is a little studied and poorly understood phenomenon. More importantly, oviposition behaviour is a largely neglected aspect of sandfly biology and this knowledge gap further undermines our understanding of the biology of sandflies. Pheromones released by the eggs play an important role in identifying good sites for oviposition by female insects. Several recent studies have examined the oviposition pheromone. The present study provides a preliminary report on the oviposition behaviour of Phlebotomus argentipes, the only vector of kala-azar (or visceral leishmaniasis) on the Indian sub-continent. Sandflies prefer to oviposit their eggs on surfaces that contain organic substances, especially substances with an odour of decaying animal products and the remains of conspecific eggs. The results presented here suggest that the odour released by the organic substances of old sandfly colony remains that contain dead flies, old unhatched eggs, larval food containing vertebrate faeces, frass and other organic matter serves as an attractant for the ovipositing females of P. argentipes and hence greatly increases the number of oviposited eggs compared to eggs deposited in controlled oviposition pots. This result will be helpful in maintaining an efficient colony of P. argentipes and may be a promising tool for monitoring and controlling the target insect as part of a synergistic approach.