Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits

Sanne J.P. Van Den Berg, Hans Baveco, Emma Butler, Frederik De Laender, Andreas Focks, Antonio Franco, Cecilie Rendal, Paul J. Van Den Brink

Research output: Contribution to journalArticle

Abstract

In this study, a trait-based macroinvertebrate sensitivity modeling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of predefined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family, or class which was most sensitive to all MOAs and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71% of the species, no or incomplete trait data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g., target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute toward a new predictive ecotoxicology framework.

Original languageEnglish
Pages (from-to)6025-6034
Number of pages10
JournalEnvironmental Science and Technology
Volume53
Issue number10
DOIs
Publication statusPublished - 21 May 2019

Fingerprint

macroinvertebrate
modeling
ecotoxicology
Life cycle
Animals
ranking
life cycle
Testing
chemical
animal
Direction compound
Ecotoxicology

Cite this

Van Den Berg, Sanne J.P. ; Baveco, Hans ; Butler, Emma ; De Laender, Frederik ; Focks, Andreas ; Franco, Antonio ; Rendal, Cecilie ; Van Den Brink, Paul J. / Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits. In: Environmental Science and Technology. 2019 ; Vol. 53, No. 10. pp. 6025-6034.
@article{1bf4b95f9e0d4c7f81092dceeee47787,
title = "Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits",
abstract = "In this study, a trait-based macroinvertebrate sensitivity modeling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of predefined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family, or class which was most sensitive to all MOAs and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71{\%} of the species, no or incomplete trait data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g., target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute toward a new predictive ecotoxicology framework.",
author = "{Van Den Berg}, {Sanne J.P.} and Hans Baveco and Emma Butler and {De Laender}, Frederik and Andreas Focks and Antonio Franco and Cecilie Rendal and {Van Den Brink}, {Paul J.}",
year = "2019",
month = "5",
day = "21",
doi = "10.1021/acs.est.9b00893",
language = "English",
volume = "53",
pages = "6025--6034",
journal = "Environmental Science and Technology",
issn = "0013-936X",
publisher = "American Chemical Society",
number = "10",

}

Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits. / Van Den Berg, Sanne J.P.; Baveco, Hans; Butler, Emma; De Laender, Frederik; Focks, Andreas; Franco, Antonio; Rendal, Cecilie; Van Den Brink, Paul J.

In: Environmental Science and Technology, Vol. 53, No. 10, 21.05.2019, p. 6025-6034.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Modeling the Sensitivity of Aquatic Macroinvertebrates to Chemicals Using Traits

AU - Van Den Berg, Sanne J.P.

AU - Baveco, Hans

AU - Butler, Emma

AU - De Laender, Frederik

AU - Focks, Andreas

AU - Franco, Antonio

AU - Rendal, Cecilie

AU - Van Den Brink, Paul J.

PY - 2019/5/21

Y1 - 2019/5/21

N2 - In this study, a trait-based macroinvertebrate sensitivity modeling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of predefined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family, or class which was most sensitive to all MOAs and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71% of the species, no or incomplete trait data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g., target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute toward a new predictive ecotoxicology framework.

AB - In this study, a trait-based macroinvertebrate sensitivity modeling tool is presented that provides two main outcomes: (1) it constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for each one of a diverse set of predefined Modes of Action (MOAs) and (2) it reveals data gaps and restrictions, helping with the direction of future research. Besides revealing taxonomic patterns of species sensitivity, we find that there was not one genus, family, or class which was most sensitive to all MOAs and that common test taxa were often not the most sensitive at all. Traits like life cycle duration and feeding mode were identified as important in explaining species sensitivity. For 71% of the species, no or incomplete trait data were available, making the lack of trait data the main obstacle in model construction. Research focus should therefore be on completing trait databases and enhancing them with finer morphological traits, focusing on the toxicodynamics of the chemical (e.g., target site distribution). Further improved sensitivity models can help with the creation of ecological scenarios by predicting the sensitivity of untested species. Through this development, our approach can help reduce animal testing and contribute toward a new predictive ecotoxicology framework.

UR - http://www.scopus.com/inward/record.url?scp=85065754182&partnerID=8YFLogxK

U2 - 10.1021/acs.est.9b00893

DO - 10.1021/acs.est.9b00893

M3 - Article

VL - 53

SP - 6025

EP - 6034

JO - Environmental Science and Technology

JF - Environmental Science and Technology

SN - 0013-936X

IS - 10

ER -