IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v222y2011i19p3587-3597.html
   My bibliography  Save this article

Modeling effects of toxin exposure in fish on long-term population size, with an application to selenium toxicity in bluegill (Lepomis macrochirus)

Author

Listed:
  • Gledhill, Michelle
  • Van Kirk, Robert W.

Abstract

A primary goal in ecotoxicology is the prediction of population-level effects of contaminant exposure based on individual-level response. Assessment of toxicity at the population level has predominately focused on the population growth rate (PGR), but the PGR may not be a relevant toxicological endpoint for populations at equilibrium. Equilibrium population size may be a more meaningful endpoint than the PGR because a population with smaller equilibrium size is more susceptible to the negative effects of environmental variability. We address the individual-to-population extrapolation problem with modeling utilizing classical mathematical theory. We developed and analyzed a general model applicable to many freshwater fish species, that includes density-dependent juvenile survival and additional juvenile mortality due to toxicity exposure, and we quantified effect on equilibrium population size as a means of assessing toxicity. Individual-level effects are typically greater than population-level effects until the individual effect is large, due to compensatory density-dependent relationships. These effects are sensitive to the recruitment potential of a population, in particular the low-density first-year survival rate Sb. Assuming high Sb could result in underestimating effects of population-level toxicity. The equilibrium size depends directly on Sb, the reproductive potential, the toxin concentration at which mean mortality is 50% (LC50), and the rate at which individual mortality increases with increasing toxin concentration. More experimental data are needed to decrease the uncertainty in estimating these parameters. We then used existing data for selenium toxicity in bluegill sunfish to parameterize a simulation version of the model as an example to assess the effects of environmental stochasticity on toxicity response. Effects of environmental variability resulted in simulated extinctions at much lower toxin concentrations than predicted deterministically.

Suggested Citation

  • Gledhill, Michelle & Van Kirk, Robert W., 2011. "Modeling effects of toxin exposure in fish on long-term population size, with an application to selenium toxicity in bluegill (Lepomis macrochirus)," Ecological Modelling, Elsevier, vol. 222(19), pages 3587-3597.
    • Handle: RePEc:eee:ecomod:v:222:y:2011:i:19:p:3587-3597
    DOI: 10.1016/j.ecolmodel.2011.08.023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380011004558
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2011.08.023?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. Brett A. Melbourne & Alan Hastings, 2008. "Extinction risk depends strongly on factors contributing to stochasticity," Nature, Nature, vol. 454(7200), pages 100-103, July.
    2. Van Kirk, Robert W. & Hill, Sheryl L., 2007. "Demographic model predicts trout population response to selenium based on individual-level toxicity," Ecological Modelling, Elsevier, vol. 206(3), pages 407-420.
    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. Brito, Izabella de Andrade & López-Barrera, Ellie Anne & Araújo, Sabrina Borges Lino & Ribeiro, Ciro Alberto de Oliveira, 2017. "Modeling the exposure risk of the silver catfish Rhamdia quelen (Teleostei, Heptapteridae) to wastewater," Ecological Modelling, Elsevier, vol. 347(C), pages 40-49.

    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. Méndez, Vicenç & Llopis, Isaac & Campos, Daniel & Horsthemke, Werner, 2010. "Extinction conditions for isolated populations affected by environmental stochasticity," Theoretical Population Biology, Elsevier, vol. 77(4), pages 250-256.
    2. Vilenkin, Boris & Chikatunov, Vladimir I. & Pavlíček, Tomáš, 2009. "The pattern of species turnover resulting from stochastic population dynamics: The model and field data," Ecological Modelling, Elsevier, vol. 220(5), pages 657-661.
    3. Zhao, Yu & Yuan, Sanling, 2016. "Stability in distribution of a stochastic hybrid competitive Lotka–Volterra model with Lévy jumps," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 98-109.
    4. Anna Kuparinen & Robert B O'Hara & Juha Merilä, 2008. "Probabilistic Models for Continuous Ontogenetic Transition Processes," PLOS ONE, Public Library of Science, vol. 3(11), pages 1-7, November.
    5. Eriksson, A. & Elías-Wolff, F. & Mehlig, B., 2013. "Metapopulation dynamics on the brink of extinction," Theoretical Population Biology, Elsevier, vol. 83(C), pages 101-122.
    6. Steiner, Ulrich K. & Tuljapurkar, Shripad, 2020. "Drivers of diversity in individual life courses: Sensitivity of the population entropy of a Markov chain," Theoretical Population Biology, Elsevier, vol. 133(C), pages 159-167.
    7. Eleanor S Devenish-Nelson & Philip A Stephens & Stephen Harris & Carl Soulsbury & Shane A Richards, 2013. "Does Litter Size Variation Affect Models of Terrestrial Carnivore Extinction Risk and Management?," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-9, February.
    8. Izquierdo, Salvador & Dopazo, César & Fueyo, Norberto, 2010. "Supply-cost curves for geographically distributed renewable-energy resources," Energy Policy, Elsevier, vol. 38(1), pages 667-672, January.
    9. Vuilleumier, Séverine & Possingham, Hugh P., 2012. "Interacting populations in heterogeneous environments," Ecological Modelling, Elsevier, vol. 228(C), pages 96-105.
    10. Jacob LaRiviere & David Kling & James N Sanchirico & Charles Sims & Michael Springborn, 2018. "The Treatment of Uncertainty and Learning in the Economics of Natural Resource and Environmental Management," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 12(1), pages 92-112.
    11. Liu, He & Dai, Chuanjun & Yu, Hengguo & Guo, Qing & Li, Jianbing & Hao, Aimin & Kikuchi, Jun & Zhao, Min, 2023. "Dynamics of a stochastic non-autonomous phytoplankton–zooplankton system involving toxin-producing phytoplankton and impulsive perturbations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 368-386.
    12. Ponciano, José M. & Taper, Mark L. & Dennis, Brian, 2018. "Ecological change points: The strength of density dependence and the loss of history," Theoretical Population Biology, Elsevier, vol. 121(C), pages 45-59.
    13. Donovan, Pierce & Springborn, Michael, 2022. "Balancing conservation and commerce: A shadow value viability approach for governing bycatch," Journal of Environmental Economics and Management, Elsevier, vol. 114(C).
    14. Chen, Aimin & Wang, Pei & Zhou, Tianshou & Tian, Tianhai, 2022. "Balance of positive and negative regulation for trade-off between efficiency and resilience of high-dimensional networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    15. Erickson, Richard A. & Cox, Stephen B. & Oates, Jessica L. & Anderson, Todd A. & Salice, Christopher J. & Long, Kevin R., 2014. "A Daphnia population model that considers pesticide exposure and demographic stochasticity," Ecological Modelling, Elsevier, vol. 275(C), pages 37-47.
    16. Garnier, Aurelie & Darmency, Henri & Tricault, Yann & Chèvre, Anne-Marie & Lecomte, Jane, 2014. "A stochastic cellular model with uncertainty analysis to assess the risk of transgene invasion after crop-wild hybridization: Oilseed rape and wild radish as a case study," Ecological Modelling, Elsevier, vol. 276(C), pages 85-94.
    17. Ponciano, José Miguel, 2018. "A parametric interpretation of Bayesian Nonparametric Inference from Gene Genealogies: Linking ecological, population genetics and evolutionary processes," Theoretical Population Biology, Elsevier, vol. 122(C), pages 128-136.
    18. Nothaaß, Dorian & Taubert, Franziska & Huth, Andreas & Clark, Adam Thomas, 2023. "Modelling species invasion using a metapopulation model with variable mortality and stochastic birth-death processes," Ecological Modelling, Elsevier, vol. 481(C).
    19. Sloggy, Matthew R. & Kling, David M. & Plantinga, Andrew J., 2020. "Measure twice, cut once: Optimal inventory and harvest under volume uncertainty and stochastic price dynamics," Journal of Environmental Economics and Management, Elsevier, vol. 103(C).
    20. Charles Sims & David Finnoff & Alan Hastings & Jacob Hochard, 2017. "Listing and Delisting Thresholds under the Endangered Species Act," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 549-570.

    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:222:y:2011:i:19:p:3587-3597. 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.