IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v484y2023ics030438002300220x.html
   My bibliography  Save this article

Modelling the biocontrol of Spodoptera frugiperda: A mechanistic approach considering Bt crops and oviposition behaviour

Author

Listed:
  • dos Anjos, Lucas
  • Weber, Igor Daniel
  • Godoy, Wesley Augusto Conde

Abstract

The fall armyworm (Spodoptera frugiperda Smith & Abbot, 1797, Lepidoptera, Noctuidae) is a widespread agricultural pest native of the Americas. It is a lepidopteran pest with the ability to consume an enormous variety of crops. There are several control strategies, including natural enemies employed to control the pest, particularly egg parasitoids and genetically modified crops with Bacillus thuringiensis Berliner, 1915, Bacillaceae (Bt) toxins. However, the constant use of Bt crops has allowed the emergence of positive selection pressure to create pests increasingly resistant to the toxins. Furthermore, female moths can lay eggs in layers and deposit scales to enhance their defences against egg parasitoids. In the present work, we intend to understand how (i) the attack rate of the parasitoid, (ii) the degree of vulnerability of the eggs to parasitism, and (iii) the mortality caused by Bt toxins affect crop production and the overall dynamics. We developed a tritrophic crop-pest-parasitoid mathematical model to study the fall armyworm dynamics focusing on crop density. Our findings indicate that crop production decreases by approximately 60.03% in the absence of parasitoids. We discuss the results regarding pest resistance to Bt toxins, pest defence against parasitism, and the selection of parasitoids for pest control, and propose potential extensions for future work.

Suggested Citation

  • dos Anjos, Lucas & Weber, Igor Daniel & Godoy, Wesley Augusto Conde, 2023. "Modelling the biocontrol of Spodoptera frugiperda: A mechanistic approach considering Bt crops and oviposition behaviour," Ecological Modelling, Elsevier, vol. 484(C).
    • Handle: RePEc:eee:ecomod:v:484:y:2023:i:c:s030438002300220x
    DOI: 10.1016/j.ecolmodel.2023.110490
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030438002300220X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2023.110490?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ma, Xiangmin & Shao, Yuanfu & Wang, Zhen & Luo, Mengzhuo & Fang, Xianjia & Ju, Zhixiang, 2016. "An impulsive two-stage predator–prey model with stage-structure and square root functional responses," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 119(C), pages 91-107.
    2. Rob Hyndman & Muhammad Akram & Blyth Archibald, 2008. "The admissible parameter space for exponential smoothing models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(2), pages 407-426, June.
    3. Kevin Shear McCann, 2000. "The diversity–stability debate," Nature, Nature, vol. 405(6783), pages 228-233, May.
    4. Schuwirth, Nele & Borgwardt, Florian & Domisch, Sami & Friedrichs, Martin & Kattwinkel, Mira & Kneis, David & Kuemmerlen, Mathias & Langhans, Simone D. & Martínez-López, Javier & Vermeiren, Peter, 2019. "How to make ecological models useful for environmental management," Ecological Modelling, Elsevier, vol. 411(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Brias, Antoine & Munch, Stephan B., 2021. "Ecosystem based multi-species management using Empirical Dynamic Programming," Ecological Modelling, Elsevier, vol. 441(C).
    2. Alysha M De Livera, 2010. "Automatic forecasting with a modified exponential smoothing state space framework," Monash Econometrics and Business Statistics Working Papers 10/10, Monash University, Department of Econometrics and Business Statistics.
    3. Ilan Vertinsky & Yingqiu Kuang & Dongsheng Zhou & Victor Cui, 2023. "The political economy and dynamics of bifurcated world governance and the decoupling of value chains: An alternative perspective," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 54(7), pages 1351-1377, September.
    4. Mosai, Alseno K. & Tokwana, Bontle C. & Tutu, Hlanganani, 2022. "Computer simulation modelling of the simultaneous adsorption of Cd, Cu and Cr from aqueous solutions by agricultural clay soil: A PHREEQC geochemical modelling code coupled to parameter estimation (PE," Ecological Modelling, Elsevier, vol. 465(C).
    5. Nonaka, Etsuko & Kuparinen, Anna, 2023. "Limited effects of size-selective harvesting and harvesting-induced life-history changes on the temporal variability of biomass dynamics in complex food webs," Ecological Modelling, Elsevier, vol. 476(C).
    6. Di Pirro, E. & Sallustio, L. & Capotorti, G. & Marchetti, M. & Lasserre, B., 2021. "A scenario-based approach to tackle trade-offs between biodiversity conservation and land use pressure in Central Italy," Ecological Modelling, Elsevier, vol. 448(C).
    7. Fernández-Amador, Octavio & Francois, Joseph F. & Oberdabernig, Doris A. & Tomberger, Patrick, 2020. "The methane footprint of nations: Stylized facts from a global panel dataset," Ecological Economics, Elsevier, vol. 170(C).
    8. Haag, Fridolin & Chennu, Arjun, 2023. "Assessing whether decisions are more sensitive to preference or prediction uncertainty with a value of information approach," Omega, Elsevier, vol. 121(C).
    9. Sutton, G.F. & Martin, G.D., 2022. "Testing MaxEnt model performance in a novel geographic region using an intentionally introduced insect," Ecological Modelling, Elsevier, vol. 473(C).
    10. Callesen, I. & Magnussen, A., 2021. "TransparC2U–A two-pool, pedology oriented forest soil carbon simulation model aimed at user investigations of multiple uncertainties," Ecological Modelling, Elsevier, vol. 453(C).
    11. Mortuja, Md Golam & Chaube, Mithilesh Kumar & Kumar, Santosh, 2021. "Dynamic analysis of a predator-prey system with nonlinear prey harvesting and square root functional response," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    12. Chinloy, Peter & Jiang, Cheng & John, Kose, 2020. "Investment, depreciation and obsolescence of R&D," Journal of Financial Stability, Elsevier, vol. 49(C).
    13. Yu, Tianhu & Cao, Dengqing & Yang, Yang & Liu, Shengqiang & Huang, Wenhu, 2016. "Robust synchronization of impulsively coupled complex dynamical network with delayed nonidentical nodes," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 92-101.
    14. Ying Chen & Binbin Lu & Chongyu Xu & Xingwei Chen & Meibing Liu & Lu Gao & Haijun Deng, 2022. "Uncertainty Evaluation of Best Management Practice Effectiveness Based on the AnnAGNPS Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(4), pages 1307-1321, March.
    15. So, Mike K.P. & Chung, Ray S.W., 2014. "Dynamic seasonality in time series," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 212-226.
    16. Lötjönen, Sanna & Ollikainen, Markku & Kotamäki, Niina & Huttunen, Markus & Huttunen, Inese, 2021. "Nutrient load compensation as a means of maintaining the good ecological status of surface waters," Ecological Economics, Elsevier, vol. 188(C).
    17. M. Barna, 2008. "The effects of cutting regimes on natural regeneration in submountain beech forests: species diversity and abundance," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 54(12), pages 533-544.
    18. Palamara, Gian Marco & Dennis, Stuart R. & Haenggi, Corinne & Schuwirth, Nele & Reichert, Peter, 2022. "Investigating the effect of pesticides on Daphnia population dynamics by inferring structure and parameters of a stochastic model," Ecological Modelling, Elsevier, vol. 472(C).
    19. Pakarinen, Suvi & Mattila, Tuomas & Melanen, Matti & Nissinen, Ari & Sokka, Laura, 2010. "Sustainability and industrial symbiosis—The evolution of a Finnish forest industry complex," Resources, Conservation & Recycling, Elsevier, vol. 54(12), pages 1393-1404.
    20. Sipos-Gug Sebastian & Badulescu Alina, 2014. "Entrepreneurship In Constructions Sector - Explanatory Economic Factors And Forecasts For Romania," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 379-389, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:484:y:2023:i:c:s030438002300220x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.