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.

A mathematical model for mapping the insecticide resistance trend in the Anopheles gambiae mosquito population under climate variability in Africa.

The control of arthropod disease vectors using chemical insecticides is vital in combating malaria, however the increasing insecticide resistance (IR) poses a challenge. Furthermore, climate variability affects mosquito population dynamics and subsequently IR propagation. We present a mathematical model to decipher the relationship between IR in Anopheles gambiae populations and climate variability.

in Togo 5 years on: early impact of the invasion and future developments.

The infestation of the fall armyworm (FAW), (J.E. Smith) (Lepidoptera: Noctuidae) in Africa since 2016 has been a major threat to maize production.

A Fuzzy-Based Model to Predict the Spatio-Temporal Performance of the Natural Enemy against under Climate Change.

The South American tomato pinworm, Tuta absoluta, causes up to 100% tomato crop losses. As Tuta absoluta is non-native to African agroecologies and lacks efficient resident natural enemies, the microgastrine koinobiont solitary oligophagous larval endoparasitoid, Dolichogenidea gelechiidivoris (Marsh) (Syn.: Apanteles gelechiidivoris Marsh) (Hymenoptera: Braconidae) was released for classical biological control.

Genetic studies of fall armyworm indicate a new introduction into Africa and identify limits to its migratory behavior.

The fall armyworm, Spodoptera frugiperda (J.E. Smith) is native to the Americas and a major pest of corn and several other crops of economic importance.

The fall armyworm strain associated with most rice, millet, and pasture infestations in the Western Hemisphere is rare or absent in Ghana and Togo.

The moth pest fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) is now present throughout much of the Eastern Hemisphere where it poses a significant economic threat to a number of crops.

Trapping Spodoptera frugiperda (Lepidoptera: Noctuidae) Moths in Different Crop Habitats in Togo and Ghana.

The economic impact of the invasion of Spodoptera frugiperda (J.E. Smith, Lepidoptera: Noctuidae) into Africa has so far been limited to maize agriculture but could potentially impact many other crops.

Maize Infestation of Fall Armyworm (Lepidoptera: Noctuidae) Within Agro-Ecological Zones of Togo and Ghana in West Africa 3 Yr After Its Invasion.

The fall armyworm Spodoptera frugiperda (J. E. Smith) invaded several West African countries in 2016 causing severe injury to maize plants and economic damage.

Analysis of strain distribution, migratory potential, and invasion history of fall armyworm populations in northern Sub-Saharan Africa.

Fall armyworm (Spodoptera frugiperda J.E. Smith) is a noctuid moth pest endemic throughout the Western Hemisphere that has recently become widespread in sub-Saharan Africa.

Comparative molecular analyses of invasive fall armyworm in Togo reveal strong similarities to populations from the eastern United States and the Greater Antilles.

The fall armyworm (Spodoptera frugiperda, J.E. Smith) is a noctuid moth that is a major and ubiquitous agricultural pest in the Western Hemisphere.