IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v267y2013icp1-10.html
   My bibliography  Save this article

Modelling estimates of honey bee (Apis spp.) colony density from drones

Author

Listed:
  • Arundel, Jonathan
  • Oldroyd, Benjamin P.
  • Winter, Stephan

Abstract

Given reports of declines in populations of pollinators globally, it is increasingly important to develop efficient procedures to assess the density and distribution of honey bee colonies in both agricultural and natural landscapes. One such procedure utilises the fact that drone honey bees from different colonies congregate in mating leks where they can be conveniently sampled. Genetic analysis of the captured drones can determine the number of colonies contributing to the sampled population. Here, through the use of sampling distributions derived from an agent-based model, we provide an improved procedure for estimating the density of colonies from the number of unique colonies identified from the sampled drones. We present simulations for different spatial environments and densities, and show that the number of unique colonies observed in a sample of drones collected at a drone trap covaries with the density of colonies in range of the sampled drone congregation area in a log-linear manner. As a consequence of this relationship, we find that colony densities from past surveys are likely to be lower than previously reported.

Suggested Citation

  • Arundel, Jonathan & Oldroyd, Benjamin P. & Winter, Stephan, 2013. "Modelling estimates of honey bee (Apis spp.) colony density from drones," Ecological Modelling, Elsevier, vol. 267(C), pages 1-10.
    • Handle: RePEc:eee:ecomod:v:267:y:2013:i:c:p:1-10
    DOI: 10.1016/j.ecolmodel.2013.07.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380013003530
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2013.07.008?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. Gallai, Nicola & Salles, Jean-Michel & Settele, Josef & Vaissière, Bernard E., 2009. "Economic valuation of the vulnerability of world agriculture confronted with pollinator decline," Ecological Economics, Elsevier, vol. 68(3), pages 810-821, January.
    2. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
    3. Baddeley, Adrian & Turner, Rolf, 2005. "spatstat: An R Package for Analyzing Spatial Point Patterns," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 12(i06).
    4. Arundel, Jonathan & Oldroyd, Benjamin P. & Winter, Stephan, 2012. "Modelling honey bee queen mating as a measure of feral colony density," Ecological Modelling, Elsevier, vol. 247(C), pages 48-57.
    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. Md Nabiul Islam Khan & Renske Hijbeek & Uta Berger & Nico Koedam & Uwe Grueters & S M Zahirul Islam & Md Asadul Hasan & Farid Dahdouh-Guebas, 2016. "An Evaluation of the Plant Density Estimator the Point-Centred Quarter Method (PCQM) Using Monte Carlo Simulation," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-18, June.
    2. Arundel, Jonathan & Oldroyd, Benjamin P. & Winter, Stephan, 2012. "Modelling honey bee queen mating as a measure of feral colony density," Ecological Modelling, Elsevier, vol. 247(C), pages 48-57.
    3. Grueters, U. & Seltmann, T. & Schmidt, H. & Horn, H. & Pranchai, A. & Vovides, A.G. & Peters, R. & Vogt, J. & Dahdouh-Guebas, F. & Berger, U., 2014. "The mangrove forest dynamics model mesoFON," Ecological Modelling, Elsevier, vol. 291(C), pages 28-41.
    4. Tardy, Olivia & Lenglos, Christophe & Lai, Sandra & Berteaux, Dominique & Leighton, Patrick A., 2023. "Rabies transmission in the Arctic: An agent-based model reveals the effects of broad-scale movement strategies on contact risk between Arctic foxes," Ecological Modelling, Elsevier, vol. 476(C).
    5. Vimercati, Giovanni & Hui, Cang & Davies, Sarah J. & Measey, G. John, 2017. "Integrating age structured and landscape resistance models to disentangle invasion dynamics of a pond-breeding anuran," Ecological Modelling, Elsevier, vol. 356(C), pages 104-116.
    6. Arii, Ken & Caspersen, John P. & Jones, Trevor A. & Thomas, Sean C., 2008. "A selection harvesting algorithm for use in spatially explicit individual-based forest simulation models," Ecological Modelling, Elsevier, vol. 211(3), pages 251-266.
    7. Balzan, Mario V & Caruana, Julio & Zammit, Annrica, 2018. "Assessing the capacity and flow of ecosystem services in multifunctional landscapes: Evidence of a rural-urban gradient in a Mediterranean small island state," Land Use Policy, Elsevier, vol. 75(C), pages 711-725.
    8. Jagadish, Arundhati & Dwivedi, Puneet & McEntire, Kira D. & Chandar, Mamta, 2019. "Agent-based modeling of “cleaner” cookstove adoption and woodfuel use: An integrative empirical approach," Forest Policy and Economics, Elsevier, vol. 106(C), pages 1-1.
    9. Smith, Helen F. & Sullivan, Caroline A., 2014. "Ecosystem services within agricultural landscapes—Farmers' perceptions," Ecological Economics, Elsevier, vol. 98(C), pages 72-80.
    10. Kathrin Stenchly & Marc Victor Hansen & Katharina Stein & Andreas Buerkert & Wilhelm Loewenstein, 2018. "Income Vulnerability of West African Farming Households to Losses in Pollination Services: A Case Study from Ouagadougou, Burkina Faso," Sustainability, MDPI, vol. 10(11), pages 1-12, November.
    11. Grazia Zulian & Joachim Maes & Maria Luisa Paracchini, 2013. "Linking Land Cover Data and Crop Yields for Mapping and Assessment of Pollination Services in Europe," Land, MDPI, vol. 2(3), pages 1-21, September.
    12. Jiao Jieying & Hu Guanyu & Yan Jun, 2021. "A Bayesian marked spatial point processes model for basketball shot chart," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 17(2), pages 77-90, June.
    13. Hinker, Jonas & Hemkendreis, Christian & Drewing, Emily & März, Steven & Hidalgo Rodríguez, Diego I. & Myrzik, Johanna M.A., 2017. "A novel conceptual model facilitating the derivation of agent-based models for analyzing socio-technical optimality gaps in the energy domain," Energy, Elsevier, vol. 137(C), pages 1219-1230.
    14. Frank Davenport, 2017. "Estimating standard errors in spatial panel models with time varying spatial correlation," Papers in Regional Science, Wiley Blackwell, vol. 96, pages 155-177, March.
    15. Tianran Ding & Wouter Achten, 2023. "Coupling agent-based modeling with territorial LCA to support agricultural land-use planning," ULB Institutional Repository 2013/359527, ULB -- Universite Libre de Bruxelles.
    16. Jascha-Alexander Koch & Jens Lausen & Moritz Kohlhase, 2021. "Internalizing the externalities of overfunding: an agent-based model approach for analyzing the market dynamics on crowdfunding platforms," Journal of Business Economics, Springer, vol. 91(9), pages 1387-1430, November.
    17. Crevier, Lucas Phillip & Salkeld, Joseph H & Marley, Jessa & Parrott, Lael, 2021. "Making the best possible choice: Using agent-based modelling to inform wildlife management in small communities," Ecological Modelling, Elsevier, vol. 446(C).
    18. Leandro, Camila & Jay-Robert, Pierre & Mériguet, Bruno & Houard, Xavier & Renner, Ian W., 2020. "Is my sdm good enough? insights from a citizen science dataset in a point process modeling framework," Ecological Modelling, Elsevier, vol. 438(C).
    19. Ulfia A. Lenfers & Julius Weyl & Thomas Clemen, 2018. "Firewood Collection in South Africa: Adaptive Behavior in Social-Ecological Models," Land, MDPI, vol. 7(3), pages 1-17, August.
    20. David, Viviane & Joachim, Sandrine & Tebby, Cleo & Porcher, Jean-Marc & Beaudouin, Rémy, 2019. "Modelling population dynamics in mesocosms using an individual-based model coupled to a bioenergetics model," Ecological Modelling, Elsevier, vol. 398(C), pages 55-66.

    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:267:y:2013:i:c:p:1-10. 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.