A Fuzzy-Based Model to Predict the Spatio-Temporal Performance of the Dolichogenidea gelechiidivoris Natural Enemy against Tuta absoluta under Climate Change

Biological reinforcement learning simulation for natural enemy -host behavior: Exploring deep learning algorithms for population dynamics

This study introduces a simulation of biological reinforcement learning to explore the behavior of natural enemies in the presence of host pests, aiming to analyze the population dynamics between natural enemies and insect pests within an ecological context. The simulation leverages on Q-learning, a reinforcement learning algorithm, to model the decision-making processes of both parasitoids/predators and pests, thereby assessing the impact of varying parasitism and predation rates on pest population growth. Simulation parameters, such as episode count, duration in months, steps, learning rate, and discount factor, were set arbitrarily. Environmental and reward matrices, representing climatic conditions, crop availability, and the rewards for different actions, were established for each month. Initial Q-tables for parasitoids/predators and pests, along with population arrays, were used to track population dynamics.•The simulation, illustrated through the Aphid-Ladybird beetle interaction case study over multiple episodes, includes a sensitivity analysis to evaluate the effects of different predation rates.•Findings reveal detailed population dynamics, phase relationships between predator and pest populations, and the significant influence of predation rates.•These insights contribute to a deeper understanding of ecological systems and inform potential pest management strategies.

Interactions between the Entomopathogenic Fungus Metarhizium anisopliae ICIPE 20 and the Endoparasitoid Dolichogenidea gelechiidivoris, and Implications for Combined Biocontrol of Tuta absoluta

The Integrated Pest Management (IPM) approach have been widely promoted and used for the management of native and invasive pests, while the use of various components of the IPM can have a synergetic, additive, or antagonistic effect on each other; this study evaluated the susceptibility of Dolichogenidea gelechiidivoris (Marsh) (Hymenoptera: Braconidae), to the Metarhizium anisopliae (Metschnikoff) ICIPE 20 through direct and indirect infection approaches. The effect of fungus on parasitoid longevity, survival of parasitized-larvae, preference of the parasitoid to fungal treated and untreated larvae, and percent parasitism of Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae) under different infection scenarios were assessed. The direct application of dry conidia to the parasitoid prior to exposure to the host, reduced D. gelechiidivoris longevity, though the infected female wasps still yielded high parasitism (over 70%). Infecting the parasitized larvae at different ages led to a respective reduction of parasitoid emergence by 35% and 23% for infection at 1 and 5 days post-parasitisation. Exposure of healthy-D. gelechiidivoris adults to a plant-sprayed with fungus did not affect their longevity, and no discriminatory host selection was observed. The highest mortality (~80%) of T. absoluta was achieved when D. gelechiidivoris and M. anisopliae ICIPE 20 were used in combination, indicating an additive impact on the target pest; however, field validation can shed more light on this outcome.