57 Ecotracer applications

Ecotracer is the unofficial fourth module of the Ecopath with Ecosim software, designed for tracking persistent contaminants in food webs. Ecotracer requires a balanced Ecopath model to trace the contaminant in model groups/species of the model and in the environment (e.g., water concentration)[1] [2].

After achieving a mass‐balanced Ecopath model of a specific ecosystem, Ecotracer simulates the flows of a contaminant due to predator/prey interactions following Ecopath parameters, the temporal changes of these flows through Ecosim and spatial‐temporal dynamic of the contaminant through Ecospace. Ecotracer requires contaminant specific parameters for the modelled functional groups based on a kinetic toxicology approach to estimate initial conditions.

Typical applications of Ecotracer have been for contaminants that can have potential detrimental impacts on human and environmental health including bio-accumulating heavy metal such as mercury[3], radioisotopes and stable isotopes[4] [5] [6], polychlorinated biphenyls (PCBs)[7] and more recently microplastic[8] [9].

Ecotracer estimates the concentration of a contaminant in modeled groups and computes temporal (Ecosim) and spatial (Ecospace) build-ups in concentration. Ecotracer simulates the contaminant fluxes and resulting concentrations in each group using a modified transfer contaminant model[10] [11] that applies to both the environment and biota. In practice, Ecotracer calculates the contaminant concentration as trade-off between “gains” and “losses” for the environment and all groups/species in the model (Table 1). The use of a food web modeling approach allows disentangling contaminant fluxes through groups considering their direct uptake from the environment as well as through trophic interactions. Ecotracer can also estimate functional groups’ contaminant concentrations when data of the initial conditions are lacking, and make forward projections based on changing environmental concentrations.

Table 1 – Gains and losses that can be accounted for during contaminant tracing using Ecotracer

Environment (e.g., seawater)
Gains Losses
Contaminant inflow rate to environment Contaminant decay rates in the environment
The sum of all contaminant excretory products from all the living groups/species Contaminant outflow rate
The sum of all contaminant uptake rates by all groups/species
For each group/species
Gains Losses
Direct contaminant uptake rates from the environment Contaminant decay rates in the group
Indirect contaminant uptake rates from trophic interactions Contaminant excretion rates

Attribution

The chapter is based on de Mutsert et al.[12], adapted with permission, License Number 5651431253138. Rather than citing this chapter, please cite the source.


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  2. Walters, W.J., Christensen, V., 2018. Ecotracer: analyzing concentration of contaminants and radioisotopes in an aquatic spatial-dynamic food web model. Journal of Environmental Radioactivity 181, 118–127. https://doi.org/10.1016/j.jenvrad.2017.11.008
  3. Booth, S., Zeller, D., 2005. Mercury, Food Webs, and Marine Mammals: Implications of Diet and Climate Change for Human Health. Environmental Health Perspectives 113, 521–526. https://doi.org/10.1289/ehp.7603
  4. Sandberg, J., Kumblad, L., Kautsky, U., 2007. Can ECOPATH with ECOSIM enhance models of radionuclide flows in food webs? – an example for 14C in a coastal food web in the Baltic Sea. Journal of Environmental Radioactivity 92, 96–111. https://doi.org/10.1016/j.jenvrad.2006.09.010
  5. Tierney, K.M., Heymans, J.J., Muir, G.K.P., Cook, G.T., Buszowski, J., Steenbeek, J., Walters, W.J., Christensen, V., MacKinnon, G., Howe, J.A., Xu, S., 2018. Modelling marine trophic transfer of radiocarbon (14C) from a nuclear facility. Environmental Modelling & Software 102, 138–154. https://doi.org/10.1016/j.envsoft.2018.01.013
  6. Booth, S., Walters, W.J., Steenbeek, J., Christensen, V., Charmasson, S., 2020. An Ecopath with Ecosim model for the Pacific coast of eastern Japan: Describing the marine environment and its fisheries prior to the Great East Japan earthquake. Ecological Modelling 428, 109087. https://doi.org/10.1016/j.ecolmodel.2020.109087
  7. Booth, S., Cheung, W.W.L., Coombs-Wallace, A.P., Zeller, D., Christensen, V., Pauly, D., 2016. Pollutants in the seas around us, in: Pauly, D., Zeller, D. (Eds.), Global Atlas of Marine Fisheries: A Critical Appraisal of Catches and Ecosystem Impacts. Island Press. pp. 152–170.
  8. Boyer, J., Rubalcava, K., Booth, S., Townsend, H., 2022. Proof-of-concept model for exploring the impacts of microplastics accumulation in the Maryland coastal bays ecosystem. Ecological Modelling 464, 109849. https://doi.org/10.1016/j.ecolmodel.2021.109849
  9. Ma, Y., You, X., 2021. Modelling the accumulation of microplastics through food webs with the example Baiyangdian Lake, China. Science of The Total Environment 762, 144110. https://doi.org/10.1016/j.scitotenv.2020.144110
  10. Thomann, R.V., 1981. Equilibrium Model of Fate of Microcontaminants in Diverse Aquatic Food Chains. Can. J. Fish. Aquat. Sci. 38, 280–296. https://doi.org/10.1139/f81-040
  11. Landrum, P.F., Lydy, M.J., Lee, H., 1992. Toxicokinetics in aquatic systems: Model comparisons and use in hazard assessment. Environ Toxicol Chem 11, 1709–1725. https://doi.org/10.1002/etc.5620111205
  12. De Mutsert K, Marta Coll, Jeroen Steenbeek, Cameron Ainsworth, Joe Buszowski, David Chagaris, Villy Christensen, Sheila J.J. Heymans, Kristy A. Lewis, Simone Libralato, Greig Oldford, Chiara Piroddi, Giovanni Romagnoni, Natalia Serpetti, Michael Spence, Carl Walters. 2023. Advances in spatial-temporal coastal and marine ecosystem modeling using Ecopath with Ecosim and Ecospace. Treatise on Estuarine and Coastal Science, 2nd Edition. Elsevier. https://doi.org/10.1016/B978-0-323-90798-9.00035-4

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