2014
DOI: 10.1016/j.ecolmodel.2014.05.017
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Butterfly catastrophe model for wheat aphid population dynamics: Construction, analysis and application

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Cited by 11 publications
(6 citation statements)
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“…There is much non-linearity prevalent; there are far more than the minimum two state variables required for chaos; the equations are non-autonomous; and the intrinsic time scales of the dynamics of the aphid sub-model and the tree sub-model are very different and incommensurate [ 42 , 43 ]. This chaotic variety indicates that focusing on management/control strategies in order to minimize adverse consequences may be difficult, even with the assistance of a process-based model (or further consideration of chaotic aphid population dynamics see [ 44 48 ]). Rutherford Aris [ 49 ] succinctly summed up this problem as follows (pp.…”
Section: Discussionmentioning
confidence: 99%
“…There is much non-linearity prevalent; there are far more than the minimum two state variables required for chaos; the equations are non-autonomous; and the intrinsic time scales of the dynamics of the aphid sub-model and the tree sub-model are very different and incommensurate [ 42 , 43 ]. This chaotic variety indicates that focusing on management/control strategies in order to minimize adverse consequences may be difficult, even with the assistance of a process-based model (or further consideration of chaotic aphid population dynamics see [ 44 48 ]). Rutherford Aris [ 49 ] succinctly summed up this problem as follows (pp.…”
Section: Discussionmentioning
confidence: 99%
“…For aphid pests, abiotic factors, presence, and abundance of natural enemies and aphid identification modules are built into DSS models such as GETLAUS, CEAS, and APHIDSim (Gosselke et al 2001 ; Piyaratne et al 2013 ; Rossing et al 1994 ; Gonzalez-Andujar et al 1993 ; Kwon and Kim 2017 ). Aside from theoretical models (Wu et al 2014 ; Fabre et al 2010 ; Ma et al 2001 ; Xian et al 2007 ; Giarola et al 2006 ), spatially explicit models can account for landscape composition and configuration, or for other factors such as wind speed and wind direction (Parry et al 2006 ). Thresholds have been defined for wireworms (Furlan 2014 ), brown planthopper (Zheng et al 2007 ) and for different cotton pests, including A. gossypii (Silvie et al 2013 ; Sequeira and Naranjo 2008 ).…”
Section: Resultsmentioning
confidence: 99%
“…There is much non-linearity prevalent; there are far more than the minimum two state variables required for chaos; the equations are non-autonomous; and the intrinsic time scales of the dynamics of the aphid sub-model and the tree sub-model are very different and incommensurate [43,44]. This chaotic variety indicates that focusing on management/control strategies in order to minimize adverse consequences may be difficult, even with the assistance of a process-based model (for further consideration of chaotic aphid population dynamics see [45][46][47][48][49]).…”
Section: Discussionmentioning
confidence: 99%