Complexity dynamics and simulations in a discrete switching ecosystem induced by an intermittent threshold control strategy
| Autor: | Wenjie Qin, Xin Li Hu, Marco Tosato |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Integrated pest management
Computer science Control (management) 02 engineering and technology threshold policy dynamic complexity multiple coexisting attractors Control theory 0502 economics and business QA1-939 0202 electrical engineering electronic engineering information engineering Control parameters Pest Control Biological Ecosystem business.industry Applied Mathematics 05 social sciences Pest control General Medicine switching model Computational Mathematics Complex dynamics Modeling and Simulation Key (cryptography) 020201 artificial intelligence & image processing State (computer science) Pest Control General Agricultural and Biological Sciences business TP248.13-248.65 Mathematics 050203 business & management Biotechnology |
| Zdroj: | Mathematical Biosciences and Engineering, Vol 17, Iss 3, Pp 2164-2178 (2020) |
| ISSN: | 1551-0018 |
| Popis: | Pest control is a worldwide challenge. An approach that has been developed to meet this challenge is the integrated pest management (IPM) strategy, which aims to offer environmentally sensitive solutions to pest problems, and takes into account the complex dynamics involved in the design of controlling pests. In this paper, we propose a discrete switching host-parasitoid model with a threshold control strategy, meanwhile, provide some qualitative analyses of the complexity of dynamic behaviors of the model that includes single and multi-parameter bifurcations and chaos. Furthermore, we do some numerical bifurcations and parameter sensibility analysis, revealing how the key control parameters and initial interaction state between the two populations affect pest control, as well as the dynamical balance between of the hosts and parasitoids. The model and analytical techniques developed in this work could be applied in other settings relevant to threshold control strategies. |
| Databáze: | OpenAIRE |
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