Equations for modelling contaminant impacts throughout a marine ecosystem

Biological risk assessment modelling for oil spills using whole-of-ecosystem models has the benefit of assessing species-specific toxicology and the chronic impact of oil spills by layering these impacts on top of the already-built ecosystem within the model. In deterministic models this approach requires tracking contaminants as they move throughout the biology of the ecosystem, from uptake to loss. Here we consolidate, modify, and add to existing equations to produce a synergistic set that can be used to define the impact of contaminants on biological groups throughout the food web. We demonstrate how these equations work, individually as well as in tandem, for oil-based contaminants by implementing them in a three-dimensional marine ecosystem model. We assess the sensitivity of parameters within these equations, showing the impact on the model outcome. Although we focus on oil-based contaminants in our examples, the equations presented can be applied to any contaminants in the aquatic or marine environment. • Whole-of-ecosystem models allow tracking oil spills throughout a marine ecosystem. • Contaminant movements are tracked in the biology of the system from uptake to loss. • We show synergistic equations for contaminants in deterministic ecosystem models. • We exemplify how equations work with parameter estimates for oil-based contaminants. • Presented contaminant equations can be applied to a range of marine contaminants.

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Publication Details

Journal
Ocean Modelling
Published
2025-11-08
DOI
https://doi.org/10.1016/j.ocemod.2025.102646
Primary Topic
Oil Spill Detection and Mitigation
Type
article
Field-Weighted Citation Impact
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article

Equations for modelling contaminant impacts throughout a marine ecosystem

Raisha Lovindeer, Hem Nalini Morzaria‐Luna, Elizabeth A. Fulton, Alaia Morell et al.
Ocean Modelling
Oil Spill Detection and Mitigation
article

Equations for modelling contaminant impacts throughout a marine ecosystem

Raisha Lovindeer, Hem Nalini Morzaria‐Luna, Elizabeth A. Fulton, Alaia Morell, Susan E. Allen, Javier Porobic Gárate, Douglas J. Latornell
article en

Abstract

Biological risk assessment modelling for oil spills using whole-of-ecosystem models has the benefit of assessing species-specific toxicology and the chronic impact of oil spills by layering these impacts on top of the already-built ecosystem within the model. In deterministic models this approach requires tracking contaminants as they move throughout the biology of the ecosystem, from uptake to loss. Here we consolidate, modify, and add to existing equations to produce a synergistic set that can be used to define the impact of contaminants on biological groups throughout the food web. We demonstrate how these equations work, individually as well as in tandem, for oil-based contaminants by implementing them in a three-dimensional marine ecosystem model. We assess the sensitivity of parameters within these equations, showing the impact on the model outcome. Although we focus on oil-based contaminants in our examples, the equations presented can be applied to any contaminants in the aquatic or marine environment. • Whole-of-ecosystem models allow tracking oil spills throughout a marine ecosystem. • Contaminant movements are tracked in the biology of the system from uptake to loss. • We show synergistic equations for contaminants in deterministic ecosystem models. • We exemplify how equations work with parameter estimates for oil-based contaminants. • Presented contaminant equations can be applied to a range of marine contaminants.

Ocean ModellingVol. 199
NOAA National Marine Fisheries Service (US), CSIRO Oceans and Atmosphere (AU), University of Tasmania (AU), University of British Columbia (CA), The King's College (US), University of Puget Sound (US), Centre for Marine Socioecology (AU), University of Washington Tacoma (US), NOAA National Marine Fisheries Service Northwest Fisheries Science Center (US)
Openalex Percentile: Top 73%
Oil Spill Detection and Mitigation
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