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Sensitivity analyses for simulating pesticide impacts on honey bee colonies

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  • Kuan, A. Carmen
  • DeGrandi-Hoffman, Gloria
  • Curry, Robert J.
  • Garber, Kristina V.
  • Kanarek, Andrew R.
  • Snyder, Marcia N.
  • Wolfe, Kurt L.
  • Purucker, S. Thomas

Abstract

We employ Monte Carlo simulation and sensitivity analysis techniques to describe the population dynamics of pesticide exposure to a honey bee colony using the VarroaPop + Pesticide model. Simulations are performed of hive population trajectories with and without pesticide exposure to determine the effects of weather, queen strength, foraging activity, colony resources, and Varroa populations on colony growth and survival. The daily resolution of the model allows us to conditionally identify sensitivity metrics. Simulations indicate queen strength and forager lifespan are consistent, critical inputs for colony dynamics in both the control and exposed conditions. Adult contact toxicity, application rate and nectar load become critical parameters for colony dynamics within exposed simulations. Daily sensitivity analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs.

Suggested Citation

  • Kuan, A. Carmen & DeGrandi-Hoffman, Gloria & Curry, Robert J. & Garber, Kristina V. & Kanarek, Andrew R. & Snyder, Marcia N. & Wolfe, Kurt L. & Purucker, S. Thomas, 2018. "Sensitivity analyses for simulating pesticide impacts on honey bee colonies," Ecological Modelling, Elsevier, vol. 376(C), pages 15-27.
  • Handle: RePEc:eee:ecomod:v:376:y:2018:i:c:p:15-27
    DOI: 10.1016/j.ecolmodel.2018.02.010
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    References listed on IDEAS

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    1. Schmickl, Thomas & Crailsheim, Karl, 2007. "HoPoMo: A model of honeybee intracolonial population dynamics and resource management," Ecological Modelling, Elsevier, vol. 204(1), pages 219-245.
    2. 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.
    3. Purucker, S.T. & Welsh, C.J.E. & Stewart, R.N. & Starzec, P., 2007. "Use of habitat-contamination spatial correlation to determine when to perform a spatially explicit ecological risk assessment," Ecological Modelling, Elsevier, vol. 204(1), pages 180-192.
    4. Nicholas W Calderone, 2012. "Insect Pollinated Crops, Insect Pollinators and US Agriculture: Trend Analysis of Aggregate Data for the Period 1992–2009," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-27, May.
    5. 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.
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    Cited by:

    1. Hong, Wei & Chen, Bingxue & Lu, Yuntao & Lu, Chuanqi & Liu, Shengping, 2022. "Using system equalization principle to study the effects of multiple factors to the development of bee colony," Ecological Modelling, Elsevier, vol. 470(C).
    2. Zheng, Yanan & Goodhue, Rachael E., 2022. "Intensive or Extensive Margin Effects? Growers’ Responses to the Restriction of High-Volatile Organic Compound (VOC) Pesticide Products in the San Joaquin Valley, California," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322085, Agricultural and Applied Economics Association.

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