- Chaos and insect ecology
- 作者: Logan, J.A. and Hain, F.P
- literature id: 32559
- catalog nub: TPL_LOGANn1991CAIEn91009300
- 文献库: Taxapad收录文献
- type: article
- publication name: Information Series - Virginia Polytechnic Institute and State University, College of Agriculture and Life Sciences
- publish date: 1991-01-01
- pages: 91-93
- 创建时间: 2021-03-02 15:00:32
- create by: zxmlmq (admin)
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comment:
Papers are presented from a symposium on the existence of chaos in ecological systems held at the IUFRO XLX World Congress in Montreal, Canada, on 5-1 1 August 1990. The role of chaos in the ecology of forest insect pests and their management is discussed in the introductory paper. The concept of deterministic chaos is introduced, the characteristics of chaotic systems are described and studies on chaos in insect population dynamics are summarized. The 2nd paper is concerned with chaos in ecology and resource management. Chaotic motion is described, and human and natural causes of chaos in ecological systems and its avoidance in managed ecosystems are discussed. Complex dynamic behaviours in ecosystems are addressed in the next paper, with reference to nonlinear modelling of time-series data. The analysis of population time series for 3 data sets (forest insects, voles and measles epidemics) is discussed. The detection of low-dimensional chaos in population dynamics data is reviewed critically in the 4th paper. It is shown with examples that many features that have been presented as evidence for chaos in population dynamics can also be observed in simulated data from non-chaotic, stochastic population models. Population fluctuations with a constant period but variations in amplitude can have features that have been interpreted as chaos, even when chaos is not present. In the final paper, a model of a predator-prey interaction based on a study of Helicoverpa virescens [Heliothis virescens) and the parasitoid Campoletis sonorensis is presented. 'ne model was constructed to examine emergent population dynamics of a behaviour-driven, individual level simulation with all random elements removed. none
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