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Autor(en) / Beteiligte
Titel
Catastrophic behavior of aphid population dynamics: An analysis of swallowtail model
Ist Teil von
  • Computational ecology and software, 2014-09, Vol.4 (3), p.135-146
Ort / Verlag
Hong Kong: Computational Ecology and Software
Erscheinungsjahr
2014
Link zum Volltext
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
  • Catastrophe phenomena are frequent in insect ecology, especially in aphid populations. Complexity of this phenomenon urges different modeling frameworks other than traditional methodologies to understand the trajectories of their behavior. Situations like this can be best handled using catastrophe theory. A few numbers of experiments have been conducted to develop catastrophe models in insect ecology, especially for aphids, and most of them are based on cusp catastrophe theory which is a lower dimensional model. However few attempts using higher dimensional models such as swallowtail or butterfly theory to analyze aphid population dynamics are also exist. In this paper we tried to analyze a recently developed higher dimensional catastrophe theory model (APHIDSim) in order to identify catastrophe regions, and used independent data to identify if catastrophic behavior is observed in the data and consequently to further verify the model. Here we found that identifying catastrophe regions is possible using catastrophe theory model, and it can be used to analyze catastrophes in insect ecology by graphically interpreting the simulated results. Increasing of insect population is intrinsically catastrophic and catastrophes (jumps) occur between states even if the driving variables still change smoothly. The results further verified the previously developed model, and we suggest that insect management program developers should consider this phenomenon when they design the management strategies for insect controlling.
Sprache
Englisch
Identifikatoren
ISSN: 2220-721X
eISSN: 2220-721X
DOI: 10.0000/issn-2220-721x-compuecol-2014-v4-0012
Titel-ID: cdi_doaj_primary_oai_doaj_org_article_aabeed284859468cba6561221149b203

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