A stochastic model of a temperature-dependent population

Curry, Guy L.; Feldman, Richard M.; Smith, Kirby C.

doi:10.1016/0040-5809(78)90042-4

Cited by 95 publications

(49 citation statements)

References 15 publications

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“…Over 500 mathematical models have been applied to establish the phenology of pest species in relation to the biological time expressed in ADD (Nietschke et al 2007), many of which considered the age structure (e.g., Curry et al 1978;Osawa et al 1983;Hudes and Shoemaker 1988;Munholland and Dennis 1992) for their applications to pest control (Nietschke et al 2007). However, far fewer (50) are applicable in biological control (Barlow 2004).…”

Section: Dynamic Modelmentioning

confidence: 99%

A new multistage dynamic model for biological control exemplified by the host–parasitoid system Spodoptera exigua–Chelonus oculator

et al. 2014

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Over the last few decades, important advances have been made in understanding of host-parasitoid relations and their applications to biological pest control. Not only has the number of agent species increased, but new manipulation techniques for natural enemies have also been empirically introduced, particularly in greenhouse crops. This makes biocontrol more complex, requiring a new mathematical modeling approach appropriate for the optimization of the release of agents. The present paper aimed at filling this gap by the development of a temperature-and stage-dependent dynamic mathematical model of the host-parasitoid system with an improved functional response. The model is appropriate not only for simulation analysis of the efficiency of biocontrol agents, but also for the application of optimal control methodology for the optimal timing of agent releases, and for the consideration of economic implications. Based on both laboratory and greenhouse trials, the model was validated and fitted to the data of Chelonus oculator (F.) (Hym.: Braconidae) as a biological control agent against the beet armyworm, Spodoptera exigua Hübner (Lep.: Noctuidae). We emphasize that this model can be easily adapted to other interacting species involved in biological or integrated pest control with either parasitoid or predator agents. Key message• The paper aimed at filling the gap between existing host-parasitoid models and the empirically introduced new manipulation techniques of biocontrol. • The result is a temperature-and stage-dependent dynamic model of the host-parasitoid system, appropriate for simulation analysis and optimization of the release of biocontrol agents • For an illustration, the model is validated and fitted to the data of a concrete host-parasitoid system. • Our model building can be easily adapted to biocontrol by predatory agents.

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Section: Dynamic Modelmentioning

confidence: 99%

A new multistage dynamic model for biological control exemplified by the host–parasitoid system Spodoptera exigua–Chelonus oculator

et al. 2014

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“…Thereafter, a point object was created for each geographical coordinate (longitude and latitude) in a table format with two columns each for minimum and maximum temperatures, respectively Tonnang et al, 2013). Based on the simulated temperatures and outputs of the phenology model, the life table parameters were calculated for each Julian day using the method suggested by Curry et al (1978):…”

Section: Estimation Of Life Table Parametersmentioning

confidence: 99%

Predicting the impact of climate change on regional and seasonal abundance of the mealybug Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae) using temperature-driven phenology model linked to GIS

Fand

Tonnang

Kumar

et al. 2014

Ecological Modelling

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“…Development of crop system models is becoming commonplace (Gutierrez and Wang, 1976;Wang et al, 1977;Curry et al, 1978;Brown et al, 1985;Gutierrez et al, 1975Gutierrez et al, , 1987and Baumgartner et al, 1986). In this work a distributed delay model (cf.…”

Section: Population Dynamics Modelmentioning

confidence: 99%

An overview of a systems model of cassava and cassava pests in Africa

Gutiérrez

Wermelinger

Schulthess

et al. 1987

Int. J. Trop. Insect Sci.

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Abstract-A systems model is described for cassava, Manihot esculenta Crantz, two of its introduced herbivores, the cassava green mite (CGM), Mononychellus tanajoa (Bondar), sensu lato, and the cassava mealybug (CM), Phenacoccus manihoti Mat.-Ferr., the introduced CM parasitoid, Epidinocarsis lopezi (DeSantis) and coccinellid predator of the genus Hyperaspis. The systems model includes the effects of weather, soil nitrogen and water levels on the interactions of the system's components.The model simulates the distribution of developmental times of cohorts initated at the same time, as well as the number and biomass (energy) dynamics of all populations over time. Biomass acquisition and allocation at the population and organism subunit levels (e.g. leaves, fruit, ova) were also simulated. A common acquisition (i.e. functional response) submodel was used to estimate daily photosynthetic as well as nitrogen and water uptake rates in cassava, in addition to herbivory, parasitism and predation rates for the arthropod species.This paper presents an overview of the systems model. Simulation results for the plant under pest free conditions were compared to field data. In addition, the model was used to estimate tuber yield losses due to CM and CGM feeding, and to examine the beneficial effects of introduced CM natural enemies as measured by reductions in tuber yield losses.

show abstract

A stochastic model of a temperature-dependent population

Cited by 95 publications

References 15 publications

A new multistage dynamic model for biological control exemplified by the host–parasitoid system Spodoptera exigua–Chelonus oculator

A new multistage dynamic model for biological control exemplified by the host–parasitoid system Spodoptera exigua–Chelonus oculator

Predicting the impact of climate change on regional and seasonal abundance of the mealybug Phenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae) using temperature-driven phenology model linked to GIS

An overview of a systems model of cassava and cassava pests in Africa

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