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Developing integral projection models for ecotoxicology

Author

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  • Pollesch, N.L.
  • Flynn, K.M.
  • Kadlec, S.M.
  • Swintek, J.A.
  • Raimondo, S.
  • Etterson, M.A.

Abstract

In many ecosystems, especially aquatic ecosystems, size plays a critical role in the factors that determine an individual's ability to survive and reproduce. In aquatic ecotoxicology, size informs both realized and potential acute and chronic effects of chemical exposure. This paper demonstrates how chemical and nonchemical effects on growth, survival, and reproduction can be linked to population-level dynamics using size-structured integral projection models (IPM). The modeling approach was developed with the goals and constraints of ecological risk assessors in mind, who are tasked with estimating the effects of chemical exposures to wildlife populations in a data-limited environment. The included case study is a collection of daily time-step IPMs parameterized for the life history and annual cycle of fathead minnows (Pimephales promelas), which motivated the development of modeling techniques for seasonal, iteroparous reproduction, density dependent growth effects, and size-dependent over-winter survival. The effects of a time-variable annual chemical exposure were interpreted using a toxicokinetic-toxicodynamic model for acute survival and sub-lethal growth effects model for chronic effects and incorporated into the IPMs. This paper presents a first application of integral projection models to ecotoxicology. Our research demonstrates that size-structured IPMs provide a promising, flexible, framework for synthesizing ecotoxicologically relevant data and theory to explore the effects of chemical and nonchemical stressors and the resulting impacts on exposed populations.

Suggested Citation

  • Pollesch, N.L. & Flynn, K.M. & Kadlec, S.M. & Swintek, J.A. & Raimondo, S. & Etterson, M.A., 2022. "Developing integral projection models for ecotoxicology," Ecological Modelling, Elsevier, vol. 464(C).
    • Handle: RePEc:eee:ecomod:v:464:y:2022:i:c:s0304380021003586
    DOI: 10.1016/j.ecolmodel.2021.109813
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    References listed on IDEAS

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    1. Carlo Albert & Sören Vogel & Roman Ashauer, 2016. "Computationally Efficient Implementation of a Novel Algorithm for the General Unified Threshold Model of Survival (GUTS)," PLOS Computational Biology, Public Library of Science, vol. 12(6), pages 1-19, June.
    2. Raimondo, Sandy, 2013. "Density dependent functional forms drive compensation in populations exposed to stressors," Ecological Modelling, Elsevier, vol. 265(C), pages 149-157.
    3. J. Swintek & M. Etterson & K. Flynn & R. Johnson, 2019. "Optimized temporal sampling designs of the Weibull growth curve with extensions to the von Bertalanffy model," Environmetrics, John Wiley & Sons, Ltd., vol. 30(6), September.
    4. Erickson, Richard A. & Eager, Eric A. & Brey, Marybeth K. & Hansen, Michael J. & Kocovsky, Patrick M., 2017. "An integral projection model with YY-males and application to evaluating grass carp control," Ecological Modelling, Elsevier, vol. 361(C), pages 14-25.
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    Cited by:

    1. Peirce, J. & Sandland, G. & Bennie, B. & Erickson, R., 2023. "An integral projection model for gizzard shad (Dorosoma cepedianum) utilizing density-dependent age-0 survival," Ecological Modelling, Elsevier, vol. 477(C).

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