Assessing the impact of biological control of Plutella xylostella through the application of Lotka–Volterra model

Tonnang, Henri E. Z.; Nedorezov, L. V.; Ochanda, Horace; Owino, JO; Löhr, B.

doi:10.1016/j.ecolmodel.2008.09.002

Cited by 27 publications

(9 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Predator–prey relationships like this one are often modeled using discrete equations to determine population sizes at given times, using parameters derived from observations of real environments and shaped to fit the equations. Tonnanga et al 43 used an analytical model to recreate the effect of introducing parasitoids (to determine the most efficient course of action to control the population). The Cell-DEVS model presented in this section is based on this model.…”

Section: Cell-devs Modeling and Simulation Of Environmental Modelsmentioning

confidence: 99%

Integrated cellular framework for modeling ecosystems: Theory and applications

Kazi

Wainer

2017

SIMULATION

View full text Add to dashboard Cite

We introduce an integrated framework for modeling and simulation of ecosystems based on cellular models. The framework integrates cellular modeling, web-based simulation, and geographic information systems (GISs) for data collection and visualization. In this framework, data extraction from GISs is automated; we use the Cell-DEVS formalism for modeling the ecosystem and the CD++ cellular modeling tool within the RISE (RESTful Interoperability Simulation Environment) middleware for web-based simulation. The simulation results are easily integrated with Google Earth data for visualization. We discuss the design, implementation, and benefits of the integrated approach for modeling and simulation in spatial analysis of ecosystem services. We show different case studies in the area of ecological systems, demonstrating how to apply the framework, its usability, and flexibility. We focus on the use of models available in remote servers, their integration with GIS data for inputs, and georeferenced visualization of the results. We show how the modeling methods based on DEVS and their modular interfaces make it easy to build such an architecture and we discuss its application to the field of environmental systems.

show abstract

Section: Cell-devs Modeling and Simulation Of Environmental Modelsmentioning

confidence: 99%

Integrated cellular framework for modeling ecosystems: Theory and applications

Kazi

Wainer

2017

SIMULATION

View full text Add to dashboard Cite

show abstract

“…No explicit method with a satisfactory accuracy of fitting has been developed, although choosing a mathematical model to describe a biological process is difficult because of the lack of standard criteria for the selection of a model describing a particular population dynamics (Isaev et al, 2001). In previous studies (Tonnang et al, 2008, 2009), we attempted to minimize the mean squared difference between the numerical solution of mechanistic model equations such as Lotka–Volterra (1931) and the experimental data for model parameter estimation. The obtained parameters failed to generate a satisfactory prediction.…”

Section: Discussionmentioning

confidence: 99%

Host–parasitoid population density prediction using artificial neural networks: diamondback moth and its natural enemies

Tonnang

Nedorezov

Owino

et al. 2010

Agri and Forest Entomology

Self Cite

View full text Add to dashboard Cite

1 An integrated pest management (IPM) system incorporating the introduction and field release of Diadegma semiclausum (Hellén), a parasitoid of diamondback moth (DBM) Plutella xylostella (L.), comprising the worst insect pest of the cabbage family, has been developed in Kenya to replace the pesticides-only approach. 2 Mathematical modelling using differential equations has been used in theoretical studies of host-parasitoid systems. Although, this method helps in gaining an understanding of the system's dynamics, it is generally less accurate when used for prediction. The artificial neural network (ANN) approach was therefore chosen to aid prediction. 3 The ANN methodology was applied to predict the population density of the DBM and D. semiclausum, its larval parasitoid. Two data sets, each from different release areas in the Kenya highlands, and both collected during a 3-year period after the release of the parasitoid, were used in the present study. Two ANN models were developed using these data. 4 The ANN approach gave satisfactory results for DBM and for D. semiclausum.Sensitivity analysis suggested that pest populations may be naturally controlled by rainfall. 5 The ANN provides a powerful tool for predicting host-parasitoid population densities and made few assumptions on the field data. The approach allowed the use of data collected at any appropriate scale of the system, bypassing the assumptions and uncertainties that could have occurred when parameters are imported from other systems. The methodology can be explored with respect to the development of tools for monitoring and forecasting the population densities of a pest and its natural enemies. In addition, the model can be used to evaluate the relative effectiveness of the natural enemies and to investigate augmentative biological control strategies.

show abstract

“…Hal ini akan menghasilkan penurunan ukuran populasi pemangsa. Kecenderungan ini terus berlanjut seiring berjalannya waktu hingga populasi pemangsa dan mangsa berada pada titik keseimbangan/kestabilan (Hadžiabdić et al 2017;Tonnang et al 2009). Selain itu, peningkatan kelimpahan serangga terbang pemangsa sesudah penjarangan hutan mungkin disebabkan oleh munculnya serangga terbang pemangsa yang lebih menyukai habitat yang terbuka dan memiliki daya jelajah geografis yang luas (Lien 2013;Simatupang et al 2019).…”

Section: Sebelum Penjaranganunclassified

Dampak Jangka Pendek Penjarangan Hutan Campuran terhadap Keanekaragaman Serangga Terbang di KPH Banten (Short-Term Impact of Thinning of Mixed Forest on the Diversity of Flying Insects in Forest Management Unit of Banten)

Budiaman

Haneda

Lumbantobing

2021

JSL

View full text Add to dashboard Cite

Forest thinning is a sylvicultural practice that aims to provide better growth space for increasing tree growth and stand quality. Forest thinning is a form of forest disturbance that has an impact on the forest environment, including flying insects. This study aimed to assess the impact of thinning of mixed forest stands on the diversity of flying insects. Eight circular plots of 0.1 ha were laid out systematically on thinning plots of 15.3 ha. Parameters observed in the plot included environment factors (stand composition, temperature, humidity, and canopy cover), abundance, species composition, and biodiversity index of flying insects (diversity index, species richness index, evenness index, and similarity index). The sweep net was used to collect the flying insects. Mann-Whitney test was used to compare the index of biodiversity of flying insects before and after forest thinning. Forest thinning caused a decrease in abundance, species composition, diversity index, richness index, and evenness index of flying insects. Forest thinning led to a decrease in the abundance of herbivorous flying insects and an increase in the abundance of predatory flying insects. Flying insect species found before thinning was not identical to those after thinning.Keywords: diversity index, flying insect, forest ecosystem, forest tending

show abstract

Assessing the impact of biological control of Plutella xylostella through the application of Lotka–Volterra model

Cited by 27 publications

References 26 publications

Integrated cellular framework for modeling ecosystems: Theory and applications

Integrated cellular framework for modeling ecosystems: Theory and applications

Host–parasitoid population density prediction using artificial neural networks: diamondback moth and its natural enemies

Dampak Jangka Pendek Penjarangan Hutan Campuran terhadap Keanekaragaman Serangga Terbang di KPH Banten (Short-Term Impact of Thinning of Mixed Forest on the Diversity of Flying Insects in Forest Management Unit of Banten)

Contact Info

Product

Resources

About