Movement ecology and functional relationships in natural enemies of Spodoptera frugiperda

• Ano de defesa: 2023
• Autor(a) principal: Tomé, Maysa Pereira
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Bt crops; Computational modeling; Inimigos naturais; Insect resistance; Modelagem computacional; Natural enemies; Plantas Bt; Resistência de pragas
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/11/11146/tde-11042023-144222/

Studying the nuances of an agroecosystem so that pest management programs involving the combination of transgenic plants and natural enemies are environmentally and economically sustainable is a great challenge. Therefore, this research aimed to study the interaction of management practices on the natural enemies of Spodoptera frugiperda (Lepidoptera: Noctuidae), considering an agricultural scenario composed of Bt plants (Bacillus thuringiensis) and different genotypes of the pest. We conducted a study to investigate, firstly, whether different genotypes would interact differently with biological control agents, addressing specific predator-prey systems for the species in question. We carried out predation and functional response experiments in the laboratory with nymphs and adults of the predatory bug Podisus nigrispinus (Hemiptera: Pentatomidae), on larvae of S. frugiperda resistant and susceptible to Bt toxins. Adults and nymphs showed a type II functional response, regardless of prey genotype. The predation dynamics was the same for both genotypes, however, the maximum predation was reached by adults facing susceptible prey. Nymphs spent ∽2.9 minutes to feed on larvae. The PCA analysis showed that the predation behavior of predators depends on the prey genotype. Our research also investigated how resistance in S. frugiperda occurs in areas of Bt and non-Bt maize, spatially arranged in bands and randomly, surrounded by grassy plants (Cynodon nlemfuensis), considering off-season periods. We used individual-based computational modeling to create the proposed landscape and entered the biological data of the pest along with the model. The results showed that the presence of grasses contributed to the reduction of the resistance allele in the field. Random (seed mixture) arrangements were favorable to the increase of resistant individuals in the field (95.86%). Arrangements in strips proved to be more efficient in managing resistance, but still allowed an increase of 82.10%. Off-season periods contributed both to the reduction of the population of S. frugiperda and to the reduction in the frequency of the resistance allele. Finally, still using computational modeling based on the individual, we studied the combination of pest management techniques: Bt and non-Bt plants, natural enemies of S. frugiperda and insecticides. Our goal was to understand how these tools act in resistance management and how this integration could affect natural enemies (parasitoids) and, consequently, their ecosystem services. The results showed that larger refuge zones benefit natural enemies and, at the same time, help to reduce the frequency of resistance in the field. On the other hand, these areas favored an increase in the population of pests in the field. Insecticides with 50 and 100% selectivity contributed to the permanence of parasitoids, along with refuge zones in proportions of 15 and 20%. The scenarios with the smallest refuge zone (5%) and 0% selectivity on natural enemies, had an increase in the frequency of initial resistance (1%) and, therefore, were considered inappropriate for pest management.