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Assessing population impacts of toxicant-induced disruption of breeding behaviours using an individual-based model for the three-spined stickleback

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Listed:
  • Mintram, Kate S.
  • Brown, A. Ross
  • Maynard, Samuel K.
  • Liu, Chun
  • Parker, Sarah-Jane
  • Tyler, Charles R.
  • Thorbek, Pernille

Abstract

The effects of toxicant exposure on individuals captured in standard environmental risk assessments (ERA) do not necessarily translate proportionally into effects at the population-level. Population models can incorporate population resilience, physiological susceptibility, and likelihood of exposure, and can therefore be employed to extrapolate from individual- to population-level effects in ERA. Here, we present the development of an individual-based model (IBM) for the three-spined stickleback (Gasterosteus aculeatus) and its application in assessing population-level effects of disrupted male breeding behaviour after exposure to the anti-androgenic pesticide, fenitrothion. The stickleback is abundant in marine, brackish, and freshwater systems throughout Europe and their complex breeding strategy makes wild populations potentially vulnerable to the effects of endocrine disrupting chemicals (EDCs). Modelled population dynamics matched those of a UK field population and the IBM is therefore considered to be representative of a natural population. Literature derived dose-response relationships of fenitrothion-induced disruption of male breeding behaviours were applied in the IBM to assess population-level impacts. The modelled population was exposed to fenitrothion under both continuous (worst-case) and intermittent (realistic) exposure patterns and population recovery was assessed. The results suggest that disruption of male breeding behaviours at the individual-level cause impacts on population abundance under both fenitrothion exposure regimes; however, density-dependent processes can compensate for some of these effects, particularly for an intermittent exposure scenario. Our findings further demonstrate the importance of understanding life-history traits, including reproductive strategies and behaviours, and their density-dependence, when assessing the potential population-level risks of EDCs.

Suggested Citation

  • Mintram, Kate S. & Brown, A. Ross & Maynard, Samuel K. & Liu, Chun & Parker, Sarah-Jane & Tyler, Charles R. & Thorbek, Pernille, 2018. "Assessing population impacts of toxicant-induced disruption of breeding behaviours using an individual-based model for the three-spined stickleback," Ecological Modelling, Elsevier, vol. 387(C), pages 107-117.
    • Handle: RePEc:eee:ecomod:v:387:y:2018:i:c:p:107-117
    DOI: 10.1016/j.ecolmodel.2018.09.003
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    References listed on IDEAS

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    1. Somers, I.F., 1988. "On a seasonally oscillating growth function," Fishbyte, The WorldFish Center, vol. 6(1), pages 8-11.
    2. Hazlerigg, Charles R.E. & Tyler, Charles R. & Lorenzen, Kai & Wheeler, James R. & Thorbek, Pernille, 2014. "Population relevance of toxicant mediated changes in sex ratio in fish: An assessment using an individual-based zebrafish (Danio rerio) model," Ecological Modelling, Elsevier, vol. 280(C), pages 76-88.
    3. Sable, Shaye E. & Rose, Kenneth A., 2008. "A comparison of individual-based and matrix projection models for simulating yellow perch population dynamics in Oneida Lake, New York, USA," Ecological Modelling, Elsevier, vol. 215(1), pages 105-121.
    4. Ibrahim, Lara & Preuss, Thomas G. & Schaeffer, Andreas & Hommen, Udo, 2014. "A contribution to the identification of representative vulnerable fish species for pesticide risk assessment in Europe—A comparison of population resilience using matrix models," Ecological Modelling, Elsevier, vol. 280(C), pages 65-75.
    5. 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.
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