No abstract

Mocis latipes (Guenée, 1852) (Lepidoptera: Erebidae) has been recognized as a major owlet caterpillar associated to the herbivory of gramineaceous plants across the American continent. During outbreaks, the caterpillars are capable of completely consuming preferred hosts (grasses) and, when these hosts are destroyed, they can move to adjacent non-grass plants and cause similar damage. Meteorological variable such as temperature and humidity are described as factors that affect the development and abundance of M. latipes. This paper aimed to describe and compare the spatial and temporal distribution of M. latipes in different locations in Brazil and to evaluate the influence of meteorological variables on the temporal range. A total of 12 locations were evaluated, in each collection point light traps were installed near cultivated areas. In order to understand the influence of meteorological variables on the abundance of M. latipes, the data were analyzed using a Generalized Linear Model according to Poisson regression. A linear regression was also used to verify the relation between the abundance and the latitude. A total of 1,985 moths were collected. The highest collections were in Amazon and Cerrado biomes. Results show that abundance was inversely related to increasing latitude and Poisson regression analysis indicated that the main meteorological variables were significantly related to abundance at each site. This study shows that due to the high preference for gramineas and the high temperature requirements (30°C), M. latipes is an important species in hot regions and regions with hight humidity. Furthurmore, even in higher latitudes, in subtropical areas, during summer months, populations can Rapidly growth being able to cause economic damages.

Population dynamics studies make it possible to predict the response of species to seasonal and inter‐annual climatic phenomena in hypothetical scenarios of climatic abnormality. However, long‐term studies on the temporal distribution and abundances of species are still scarce in the literature, including for species of agricultural importance. The present study aimed to bridge this gap through monthly collection events of species of cutworms (species of Agrotis and Feltia) across eight crop seasons (from July 2012 to June 2020) in the Brazilian Savanna (Cerrado). This biome is characterised by an irregular distribution of rainfall during a normal year, including two well‐defined periods of dry and rainy seasons. Only five species of cutworms were recorded: Agrotis ipsilon, Agrotis canities, Feltia repleta, Feltia submontana and Feltia subterranea, all widely distributed across South America. Except for F. submontana, occurring only in the autumn, other species occurred nearly year‐round, with distinct peaks of abundance in the dry season (April to October), supporting the hypothesis that species of Agrotina are well adapted to dry environments. The association of cutworms with dry environments was recovered for multivoltine, abundant species, such as A. ipsilon and F. subterranea, as for univoltine species, such as F. submontana. Across eight crop seasons, the abundance of all species decreased, coinciding with a high intensity El Niño effect. However, the effect itself was not found to be significant to predict the temporal distribution and abundances of cutworms and the causes of population decrease from 2014 to 2015 crop season remain to be explained. After the temporal autocorrelation effects were removed, it was revealed that the abundance of cutworms tends to be larger in crop seasons with less precipitation. Thus, this variable can be used to predict outbreaks of cutworms in the Cerrado. Some species of cutworms deserve special concern due to their frequency, seasonality and higher abundances in the Cerrado during the dry season. Their adaptability to adverse conditions may increase their spatio‐temporal distribution in Brazil and the frequency of outbreaks in a scenario of climate change, with the continuing reduction of rainfall in central and southeastern Brazil.