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A System Dynamics Model for Pests and Natural Enemies Interactions by Bonoukpoè Mawuko Sokame; Henri E. Z. Tonnang; Sevgan Subramanian; Anani Y. Bruce; Thomas Dubois; Sunday Ekesi; Paul-André Calatayud is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.
What is A System Dynamics Model for Pests and Natural Enemies Interactions about?
## Abstract Stemborers (Busseola fusca, Sesamia calamistis and Chilo partellus), the fall armyworm (Spodoptera frugiperda) and associated parasitoids constitute an interacting system in maize fields in Kenya. This work aims at developing and evaluating models that represent the evolution of those interactions by applying system thinking and system dynamics approaches with its archetypes [causal loop diagram (CLD), reinforcing (R) and balancing (B)] to analyse the population of these multi-species systems. The software Vensim PLE 8.0.9 was used to implement the models and carry out the simulations of single- and multi-species systems. The results showed that when a single pest species with its associated parasitoids interact with the host plant, the species was able to establish and sustain by cyclical relationship between populations of the pest and the associated parasitoids. However, in multi- pest species systems, dominance of S. frugiperda and C. partellus over B. fusca and S. calamistis was observed, but without extinction. However, there was a likelihood for B. fusca being displaced by C. partellus. Overall, the models predict the co-existence of fall armyworm with stemborer
Who reads A System Dynamics Model for Pests and Natural Enemies Interactions?
It is typically read by researchers, students, and practitioners in Biochemistry, Genetics and Molecular Biology.
- Author
- Bonoukpoè Mawuko Sokame; Henri E. Z. Tonnang; Sevgan Subramanian; Anani Y. Bruce; Thomas Dubois; Sunday Ekesi; Paul-André Calatayud
- Publisher
- Springer Science and Business Media LLC
- Published
- 2021
- Language
- EN
- Field
- Biochemistry, Genetics and Molecular Biology (Life Sciences)