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Ecorelevance integration report on population modeling : integration of population modeling results for 8 species into an ecological modeling based laboratory to population effect extrapolation (ECOPEX) factor to perform an ecological relevancy normalization of the HC5 for nickel

Karel De Schamphelaere (UGent) , Simon Hansul, Sharon Janssen, Patrick Van Sprang, Karel Vlaeminck, Kristi Weighman (UGent) and Karel Viaene
(2022)
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Abstract
We developed population models for 8 species: 2 fish, 4 invertebrates, 1 algae and 1 aquatic plant and we applied these to extrapolate individual-level effects obtained in laboratory tests to population-level endpoints relating to population density. Overall, we conclude that the population-level is on average 2.7-fold less sensitive to nickel, than the individual (or laboratory) level, which could be implemented in generic assessments. However, for more specific, and higher tier assessments, our models are well equipped to deal both with uncertainties and the effects of several external factors on population-level effects for several species. Population models can thus support metals risk assessment to become more ecologically relevant.

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Citation

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MLA
De Schamphelaere, Karel, et al. Ecorelevance Integration Report on Population Modeling : Integration of Population Modeling Results for 8 Species into an Ecological Modeling Based Laboratory to Population Effect Extrapolation (ECOPEX) Factor to Perform an Ecological Relevancy Normalization of the HC5 for Nickel. Ghent University & ARCHE Assessing Risks of Chemicals, 2022.
APA
De Schamphelaere, K., Hansul, S., Janssen, S., Van Sprang, P., Vlaeminck, K., Weighman, K., & Viaene, K. (2022). Ecorelevance integration report on population modeling : integration of population modeling results for 8 species into an ecological modeling based laboratory to population effect extrapolation (ECOPEX) factor to perform an ecological relevancy normalization of the HC5 for nickel. Ghent University & ARCHE Assessing Risks of Chemicals.
Chicago author-date
De Schamphelaere, Karel, Simon Hansul, Sharon Janssen, Patrick Van Sprang, Karel Vlaeminck, Kristi Weighman, and Karel Viaene. 2022. “Ecorelevance Integration Report on Population Modeling : Integration of Population Modeling Results for 8 Species into an Ecological Modeling Based Laboratory to Population Effect Extrapolation (ECOPEX) Factor to Perform an Ecological Relevancy Normalization of the HC5 for Nickel.” Ghent University & ARCHE Assessing Risks of Chemicals.
Chicago author-date (all authors)
De Schamphelaere, Karel, Simon Hansul, Sharon Janssen, Patrick Van Sprang, Karel Vlaeminck, Kristi Weighman, and Karel Viaene. 2022. “Ecorelevance Integration Report on Population Modeling : Integration of Population Modeling Results for 8 Species into an Ecological Modeling Based Laboratory to Population Effect Extrapolation (ECOPEX) Factor to Perform an Ecological Relevancy Normalization of the HC5 for Nickel.” Ghent University & ARCHE Assessing Risks of Chemicals.
Vancouver
1.
De Schamphelaere K, Hansul S, Janssen S, Van Sprang P, Vlaeminck K, Weighman K, et al. Ecorelevance integration report on population modeling : integration of population modeling results for 8 species into an ecological modeling based laboratory to population effect extrapolation (ECOPEX) factor to perform an ecological relevancy normalization of the HC5 for nickel. Ghent University & ARCHE Assessing Risks of Chemicals; 2022.
IEEE
[1]
K. De Schamphelaere et al., “Ecorelevance integration report on population modeling : integration of population modeling results for 8 species into an ecological modeling based laboratory to population effect extrapolation (ECOPEX) factor to perform an ecological relevancy normalization of the HC5 for nickel.” Ghent University & ARCHE Assessing Risks of Chemicals, 2022.
@misc{01HCAHBPHJHN4N9M9T5S51X1B9,
  abstract     = {{We developed population models for 8 species: 2 fish, 4 invertebrates, 1 algae and 1 aquatic plant and we applied these to extrapolate individual-level effects obtained in laboratory tests to population-level endpoints relating to population density. Overall, we conclude that the population-level is on average 2.7-fold less sensitive to nickel, than the individual (or laboratory) level, which could be implemented in generic assessments. However, for more specific, and higher tier assessments, our models are well equipped to deal both with uncertainties and the effects of several external factors on population-level effects for several species. Population models can thus support metals risk assessment to become more ecologically relevant.}},
  author       = {{De Schamphelaere, Karel and Hansul, Simon and Janssen, Sharon and Van Sprang, Patrick and Vlaeminck, Karel and Weighman, Kristi and Viaene, Karel}},
  language     = {{eng}},
  publisher    = {{Ghent University & ARCHE Assessing Risks of Chemicals}},
  title        = {{Ecorelevance integration report on population modeling : integration of population modeling results for 8 species into an ecological modeling based laboratory to population effect extrapolation (ECOPEX) factor to perform an ecological relevancy normalization of the HC5 for nickel}},
  year         = {{2022}},
}