IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v292y2014icp37-44.html
   My bibliography  Save this article

Coverage and invariance for the biological control of pests in mediterranean greenhouses

Author

Listed:
  • Lloret-Climent, Miguel
  • Amorós-Jiménez, Rocco
  • González-Franco, Lucía
  • Nescolarde-Selva, Josué-Antonio

Abstract

A major problem related to the treatment of ecosystems is that they have no available mathematical formalization. This implies that many of their properties are not presented as short, rigorous modalities, but rather as long expressions which, from a biological standpoint, totally capture the significance of the property, but which have the disadvantage of not being sufficiently manageable, from a mathematical standpoint. The interpretation of ecosystems through networks allows us to employ the concepts of coverage and invariance alongside other related concepts. The latter will allow us to present the two most important relations in an ecosystem – predator–prey and competition – in a different way. Biological control, defined as “the use of living organisms, their resources or their products to prevent or reduce loss or damage caused by pests”, is now considered the environmentally safest and most economically advantageous method of pest control (van Lenteren, 2011). A guild includes all those organisms that share a common food resource (Polis et al., 1989), which in the context of biological control means all the natural enemies of a given pest. There are several types of intraguild interactions, but the one that has received most research attention is intraguild predation, which occurs when two organisms share the same prey while at the same time participating in some kind of trophic interaction. However, this is not the only intraguild relationship possible, and studies are now being conducted on others, such as oviposition deterrence. In this article, we apply the developed concepts of structural functions, coverage, invariant sets, etc. (Lloret et al., 1998; Esteve and Lloret, 2006a,b, 2007) to a tritrophic system that includes aphids, one of the most damaging pests and a current bottleneck for the success of biological control in Mediterranean greenhouses.

Suggested Citation

  • Lloret-Climent, Miguel & Amorós-Jiménez, Rocco & González-Franco, Lucía & Nescolarde-Selva, Josué-Antonio, 2014. "Coverage and invariance for the biological control of pests in mediterranean greenhouses," Ecological Modelling, Elsevier, vol. 292(C), pages 37-44.
    • Handle: RePEc:eee:ecomod:v:292:y:2014:i:c:p:37-44
    DOI: 10.1016/j.ecolmodel.2014.08.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380014004116
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2014.08.023?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. Fath, Brian D. & Scharler, Ursula M. & Ulanowicz, Robert E. & Hannon, Bruce, 2007. "Ecological network analysis: network construction," Ecological Modelling, Elsevier, vol. 208(1), pages 49-55.
    2. Lin, Yangchen & Sutherland, William J., 2013. "Color and degree of interspecific synchrony of environmental noise affect the variability of complex ecological networks," Ecological Modelling, Elsevier, vol. 263(C), pages 162-173.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Téllez, M.M. & Cabello, T. & Gámez, M. & Burguillo, F.J. & Rodríguez, E., 2020. "Comparative study of two predatory mites Amblyseius swirskii Athias-Henriot and Transeius montdorensis (Schicha) by predator-prey models for improving biological control of greenhouse cucumber," Ecological Modelling, Elsevier, vol. 431(C).

    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. Dunlap, J. & Schramski, J.R., 2024. "Energy-systems accounting in industrial-natural systems; An energy analysis of a managed forest ecosystem including food web biomass dynamics," Ecological Modelling, Elsevier, vol. 488(C).
    2. Panyam, Varuneswara & Huang, Hao & Davis, Katherine & Layton, Astrid, 2019. "Bio-inspired design for robust power grid networks," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    3. De Montis, Andrea & Ganciu, Amedeo & Cabras, Matteo & Bardi, Antonietta & Mulas, Maurizio, 2019. "Comparative ecological network analysis: An application to Italy," Land Use Policy, Elsevier, vol. 81(C), pages 714-724.
    4. Chen, G.Q. & Chen, Z.M., 2011. "Greenhouse gas emissions and natural resources use by the world economy: Ecological input–output modeling," Ecological Modelling, Elsevier, vol. 222(14), pages 2362-2376.
    5. Borrett, Stuart R. & Sheble, Laura & Moody, James & Anway, Evan C., 2018. "Bibliometric review of ecological network analysis: 2010–2016," Ecological Modelling, Elsevier, vol. 382(C), pages 63-82.
    6. Chen, Shaoqing & Chen, Bin, 2017. "Coupling of carbon and energy flows in cities: A meta-analysis and nexus modelling," Applied Energy, Elsevier, vol. 194(C), pages 774-783.
    7. Zhijun Luo & Xiaofang Yang & Songkai Luo, 2024. "Land Use Simulation and Ecological Network Construction around Poyang Lake Area in China under the Goal of Sustainable Development," Sustainability, MDPI, vol. 16(18), pages 1-24, September.
    8. Li, Lianwei & Li, Wendy & Zou, Quan & Ma, Zhanshan (Sam), 2020. "Network analysis of the hot spring microbiome sketches out possible niche differentiations among ecological guilds," Ecological Modelling, Elsevier, vol. 431(C).
    9. Gao, Jing & Gong, Jian & Li, Yao & Yang, Jianxin & Liang, Xun, 2024. "Ecological network assessment in dynamic landscapes: Multi-scenario simulation and conservation priority analysis," Land Use Policy, Elsevier, vol. 139(C).
    10. Wang, Shengyan & Li, Bingkang & Zhao, Xudong & Hu, Qianchen & Liu, Da, 2024. "Assessing fossil energy supply security in China using ecological network analysis from a supply chain perspective," Energy, Elsevier, vol. 288(C).
    11. Hines, David E. & Borrett, Stuart R., 2014. "A comparison of network, neighborhood, and node levels of analyses in two models of nitrogen cycling in the Cape Fear River Estuary," Ecological Modelling, Elsevier, vol. 293(C), pages 210-220.
    12. Jiali Huang & Robert E Ulanowicz, 2014. "Ecological Network Analysis for Economic Systems: Growth and Development and Implications for Sustainable Development," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-8, June.
    13. Almpanidou, Vasiliki & Mazaris, Antonios D. & Mertzanis, Yorgos & Avraam, Ioannis & Antoniou, Ioannis & Pantis, John D. & Sgardelis, Stefanos P., 2014. "Providing insights on habitat connectivity for male brown bears: A combination of habitat suitability and landscape graph-based models," Ecological Modelling, Elsevier, vol. 286(C), pages 37-44.
    14. Borrett, S.R. & Freeze, M.A., 2011. "Reconnecting environs to their environment," Ecological Modelling, Elsevier, vol. 222(14), pages 2393-2403.
    15. Duan, Cuncun & Chen, Bin & Feng, Kuishuang & Liu, Zhu & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2018. "Interregional carbon flows of China," Applied Energy, Elsevier, vol. 227(C), pages 342-352.
    16. Phillips, Jonathan D., 2011. "Predicting modes of spatial change from state-and-transition models," Ecological Modelling, Elsevier, vol. 222(3), pages 475-484.
    17. Eniko Kovacs & Maria-Alexandra Hoaghia & Lacrimioara Senila & Daniela Alexandra Scurtu & Diana Elena Dumitras & Cecilia Roman, 2020. "Sustainability Problematization and Modeling Opportunities," Sustainability, MDPI, vol. 12(23), pages 1-26, December.
    18. Borrett, Stuart R. & Moody, James & Edelmann, Achim, 2014. "The rise of Network Ecology: Maps of the topic diversity and scientific collaboration," Ecological Modelling, Elsevier, vol. 293(C), pages 111-127.
    19. Kim, Daehyun & Phillips, Jonathan D., 2013. "Predicting the structure and mode of vegetation dynamics: An application of graph theory to state-and-transition models," Ecological Modelling, Elsevier, vol. 265(C), pages 64-73.
    20. Stefano Allesina & Mercedes Pascual, 2009. "Googling Food Webs: Can an Eigenvector Measure Species' Importance for Coextinctions?," PLOS Computational Biology, Public Library of Science, vol. 5(9), pages 1-6, September.

    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:292:y:2014:i:c:p:37-44. 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.