Leaf-cutting ants of the genus Atta are an important insect pest in forest plantations in many countries of South America. The objective of this work was to evaluate the potential for using Landsat-8 images, with medium spatial resolution and distributed free of charge, to detect leaf-cutting ant nests in Tectona grandis plantations in Brazil, using partial least squares discriminant analysis (PLS-DA). The regression model adjusted by PLS-DA selected three principal components with a cross-validation error of 0.275 to map and predict the presence of leaf-cutting ant nests in these plantations. The most important bands and vegetation indices were selected using the main variables in the projection (VIP) and predicted pixels with the presence or absence of leaf-cutting ant nests with an accuracy of 72.3% on an independent validation data set. The study indicates that Landsat-8 OLI images have the potential to detect and map leaf-cutting ant nests in T. grandis plantations.

The effects of intercropping of Brassicaceae with coriander (Coriandrum sativum), dill (Anethum graveolens), African marigold (Tagetes erecta) and calendula (Calendula officinalis) on the abundance, species richness and diversity of predators and parasitoids of Lipaphis erysimi have been assessed. The numbers of aphids, parasitized aphids and natural enemies were determined during two consecutive phases. The first period comprised the vegetative phase of companion plants up to the onset of flowering and the development of kale up to the start of harvesting, while the second period encompassed the late flowering of companion plants up to senescence and the complete harvesting phase of kale. The establishment of L. erysimi and its natural enemies during the first period was enhanced by the climatic conditions and the additional nutritional resources offered by companion plants. Over the complete 13 week period, the abundance of natural enemies in kale intercropped with African marigold, calendula, coriander and dill increased by factors of 3.1, 2.1, 2.0 and 1.6, respectively, compared with the kale monoculture, while species richness increased by 1.8-fold in kale/African marigold intercrop and by a factor of 2.7 in the other treatments. The predominant predators were Syrphidae larvae and Hippodamia convergens whereas the predominant parasitoid was Diaeretiella rapae. The diversity of natural enemies was similar in all crops owing to the high proportion of syrphids in relation to the other groups of insects. The improved resources offered by companion plants can be exploited in the conservative biological control of insect pests. Key words: Conservation biological control, natural enemies, insect seasonality, Hemiptera, Aphididae, Asteraceae, Apiaceae, Lipaphis erysimi, abundance, richness, Syrphidae, ladybird, kale

Leaf-cutting ants are one of the most important pests of eucalyptus plantations and it is essential to monitor and control these insects to avoid damage to wood production. The objective of this research was to assess the utility of the multispectral sensor, Sentinel-2 (S-2) in mapping defoliation caused by leaf-cutting ants in Eucalyptus plantations. The study was carried out in Eucalyptus plantations in Telêmaco Borba, Paraná state, Brazil. The leaf-cutting ant nests were located, measured and georeferenced. Multispectral images from bands 2, 3, 4 and 8 of the S-2 satellite and four vegetation indices (VIs) were tested in predicting and mapping leaf-cutting ant defoliation. From each image scene the reflectance values were extracted and a partial least squares discriminant analysis (PLS-DA) was performed. The predictive variables, included in the PLS-DA regression, were selected based on the calculation of the variable importance in the projection (VIP). The accuracy of the mapping was 84.5% using six main components, demonstrating a satisfactory approach to operationally classifying canopies of Eucalyptus stands attacked by leaf-cutting ants. The study indicates the potential of freely available medium resolution Multispectral instrument (MSI) S-2 images, to accurately detect and map defoliation caused by Atta species in commercial forest plantations.