Recently, the Neotropical brown stink bug, Euschistus heros (Pentatomidae: Hemiptera), has been detected in cotton in the Brazilian Cerrado. Several reliable surveys have been conducted on the spatial distribution of stink bugs in soybean; however, few studies have examined the behavior of this insect in cotton in Brazil. Thus, this study examined the spatial distribution of E. heros in cotton using aggregation indices based on the variance-to-mean ratio, Morisita index, exponent k, Poisson and negative binomial distributions. Inverse Distance Weighting interpolation maps were also used to represent insect density. The study was conducted in a 1.1 hectare experimental cotton field in which 64 equally-sized plots were sampled on a weekly basis. Our findings revealed that stink bugs presented an aggregate distribution in 2 sampling weeks based on aggregation indices, and this pattern was best described by a negative binomial distribution. Maps showing the density of pests can be an important tool for sampling pests in crops and control measures in early stages of infestation, when there is an edge effect on the distribution of E. heros, can be an efficient strategy in cotton.

The objective of this work was to analyze the faunistic composition of the insect pests that occur during the fallow period in cotton (Gossypium hirsutum) crop residues in the state of Mato Grosso do Sul, Brazil. The study sites were the municipalities of Alcinópolis, Chapadão do Sul, Costa Rica, Aral Moreira, Dourados, and Sidrolândia. A sampling design with two replicates per municipality was used. Each replicate comprised 100 random points, and each point corresponded to a cotton plant that was entirely inspected, to count the insect pests on it. The obtained fauna was analyzed and a rarefaction curve of the species was generated. During the evaluation period, a total of 23 species were recorded in the cotton crop residue, and the most frequent and abundant were Bemisia tabaci, Aphis gossypii, Frankliniella schultzei, and Anthonomus grandis. The caterpillars were predominantly found on the non-Bt cotton crops in Dourados, and Chapadão do Sul was the municipality that exhibited the greatest species diversity. Despite being mandatory, the destruction of cotton stalks during the fallow period was not able to completely eliminate the insect pests during the study period; among these insect pests, A. grandis stands out, a species that affects the dynamics of cotton pest control.

The red-banded stink bug, Piezodorus guildinii, is an important pest in soybean. Information on its distribution is needed to determine the most effective timing for pest control and strategies to avoid yield losses, such as adequate monitoring. The present study was aimed at examining the temporal variation and spatial distribution of P. guildinii in soybean. The experimental design comprised an area of 5400 m² planted with soybean, with 54 plots of 100 m² each, in which plants were examined weekly for nymphs and adults of P. guildinii with a beating sheet. Evaluations were carried out from soybean emergence to harvest; however, P. guildinii occurred only during the reproductive stage. Based on aggregation indices, theoretical frequency distributions, and semivariograms, nymphs and adults were randomly distributed at the beginning of infestation but, tended to be aggregate during pod setting and seed filling. Our findings have a contribution to improving pest sampling systems and infestation mapping, including future semiochemicals studies.

Soybean varieties with indeterminate growth habit are widely used in the state of Mato Grosso do Sul and are characterized by not having well-defined phenological stages. Due to the importance of bee conservation, studies on the frequency and time of visitation in indeterminate soybean are needed. Samples were collected in a 4-ha plot of soybeans not treated with insecticides. Sampling was carried out at random spots, throughout the flowering period, starting at 08h:00min, during 15 min/hour, successively until 16h:00min. Generalized Linear Models were generated and the Poisson regression model provided the best fit, reflecting the significant differences revealed by the deviance analysis. The association between bees and climatic variables was tested with the Spearman’s correlation. The temporal pattern of bee visitation was independently influenced by flowering period and time of day. However climatic variables did not influence significantly bee visitation rate. In the first days of flowering, bees were more abundant, especially between 10h and 15h. These results have practical implications in the maintenance of this species during soybean management practices, contributing to a balanced coexistence between beekeepers and soybean growers, by avoiding applications of phytosanitary products during the periods of high bee visitation.

Residues of plant protection products have been reported in floral resources such as pollen, but the potential risks of pollinator exposure are still unclear. Therefore, studies are needed to assess the risk of exposure/intoxication of bees, as they collect these resources to maintain their colony. The present study used a randomized design with five treatments: thiamethoxam, clothianidin, imidacloprid, fipronil, and a control. Pollen was collected from two soybean plants per repetition during their entire flowering period, mixed with 8 g of sugar cake (distilled water + sugar), and offered to adult bees that were then followed for the assessment of mortality over time (1, 2, 4, 8, 16, 24 and 32 h after initial exposure). Among the generalized linear models evaluated, the beta binomial model was the best fit. The treatments were compared within each time period by overlapping credibility intervals using Bayesian inference. The probability of bee mortality was low in the first hours of evaluation and gradually increased over time in all chemical treatments. When comparing the means of the beta-binomial model, no statistical differences among treatments was observed, indicating a mortality similar to that of the control group.