Multivariate Functional Data Analysis Uncovers Behavioral Fingerprints in Invertebrate Locomotor Response to Micropollutants

Fuente: arXiv
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Autores principales: Ruck, George, Aubin, Jean-Baptiste, Delétang, Alexandre, Neuzeret, Didier, Geffard, Olivier, Chaumot, Arnaud
Formato: Preprint
Publicado: 2025
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author Ruck, George
Aubin, Jean-Baptiste
Delétang, Alexandre
Neuzeret, Didier
Geffard, Olivier
Chaumot, Arnaud
author_facet Ruck, George
Aubin, Jean-Baptiste
Delétang, Alexandre
Neuzeret, Didier
Geffard, Olivier
Chaumot, Arnaud
contents The need for effective biomonitoring in wastewater has become clear due to the impracticality of continuously tracking all chemicals and emerging contaminants in the aquatic exposome. Effect-based biomonitoring provides a cost-effective solution. The ToxMate device, which uses videotracking of locomotor behavior in aquatic invertebrates, has proven efficient for real-time detection of micropollutant surges in effluents. To extend the approach, this proof-of-concept study evaluates the potential to formalize behavioral fingerprints from real-time videotracking data to characterize qualitative variations in effluent contamination. We present the first application of a functional data analysis (FDA) framework in ecotoxicology. Data were obtained by simultaneously tracking three sentinel organisms from distinct taxa (a crustacean, an annelid, and a gastropod) during pulse exposures to four chemicals in the laboratory (two metals, one pharmaceutical, and one insecticide). Individual and multispecies responses were analy-zed to determine whether combining species enhances the resolution of contamination fingerprints through multidimensional FDA. Applying the same data-driven approach to field data from a wastewater treatment plant (WWTP) revealed four recurring types of micropollution events. This proof of concept demonstrates the potential of behavioral fingerprints to improve wastewater monitoring and reduce pollutant transfer to the environment.
format Preprint
id arxiv_https___arxiv_org_abs_2511_20723
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Multivariate Functional Data Analysis Uncovers Behavioral Fingerprints in Invertebrate Locomotor Response to Micropollutants
Ruck, George
Aubin, Jean-Baptiste
Delétang, Alexandre
Neuzeret, Didier
Geffard, Olivier
Chaumot, Arnaud
Quantitative Methods
The need for effective biomonitoring in wastewater has become clear due to the impracticality of continuously tracking all chemicals and emerging contaminants in the aquatic exposome. Effect-based biomonitoring provides a cost-effective solution. The ToxMate device, which uses videotracking of locomotor behavior in aquatic invertebrates, has proven efficient for real-time detection of micropollutant surges in effluents. To extend the approach, this proof-of-concept study evaluates the potential to formalize behavioral fingerprints from real-time videotracking data to characterize qualitative variations in effluent contamination. We present the first application of a functional data analysis (FDA) framework in ecotoxicology. Data were obtained by simultaneously tracking three sentinel organisms from distinct taxa (a crustacean, an annelid, and a gastropod) during pulse exposures to four chemicals in the laboratory (two metals, one pharmaceutical, and one insecticide). Individual and multispecies responses were analy-zed to determine whether combining species enhances the resolution of contamination fingerprints through multidimensional FDA. Applying the same data-driven approach to field data from a wastewater treatment plant (WWTP) revealed four recurring types of micropollution events. This proof of concept demonstrates the potential of behavioral fingerprints to improve wastewater monitoring and reduce pollutant transfer to the environment.
title Multivariate Functional Data Analysis Uncovers Behavioral Fingerprints in Invertebrate Locomotor Response to Micropollutants
topic Quantitative Methods
url https://arxiv.org/abs/2511.20723