# Caging Gammarus roeseli to track pesticide contamination: How agricultural practices shape water quality in small waterbodies?

Gaspard Conseil, Olivier Cardoso, Vincent Felten, Christophe Rosin, Laure

Pasquini, Marion Huguet-Cizo, Sylvain Milla, Damien Banas

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Gaspard Conseil, Olivier Cardoso, Vincent Felten, Christophe Rosin, Laure Pasquini, et al. "Caging Gammarus roeseli to track pesticide contamination: How agricultural practices shape water quality in small waterbodies?". Ecotoxicology and Environmental Safety, 2025, 295, pp.118143. 10.1016/j.ecoenv.2025.118143. hal-05042234

HAL Id: hal-05042234

https://hal.science/hal-05042234v1

Submitted on 22 Apr 2025

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

# Caging *Gammarus roeseli* to track pesticide contamination: How agricultural practices shape water quality in small waterbodies?

Gaspard Conseil<sup>a,b,* ,1 D</sup>, Olivier Cardoso<sup>c</sup>, Vincent Felten<sup>d</sup>, Christophe Rosin<sup>e D</sup>, Laure Pasquini<sup>e</sup>, Marion Huguet-Cizo<sup>a,1</sup>, Sylvain Milla<sup>a,1 D</sup>, Damien Banas<sup>a,** ,1 D</sup>

## ARTICLE INFO

Edited by Dr G Liu

**Keywords:**

Biomonitoring

Gammarids

Pesticide mixture

Transformation products

Aquatic agroecosystem

Ponds

## ABSTRACT

Contaminant monitoring in agroecosystems is increasingly revealing overlooked molecules, particularly within complex pesticide mixtures. This study assessed the effectiveness of chemical and ecotoxicological methods for evaluating contamination and biological responses in *Gammarus roeseli* exposed to pesticides and transformation products (TPs) in lentic small water bodies (LSWBs) near agricultural zones. We examined 7 LSWBs, finding variable contamination levels shaped by watershed composition differences. Analysis of 136 compounds identified key TPs, including chlorothalonil R471811, metazachlor ESA, and OXA, which collectively represented 86.2 % of the total quantified contaminants. These results underscore the persistence of both current and banned pesticides in the ponds studied. While *G. roeseli* showed favorable survival rates, significant reductions in locomotion and ventilation were observed at heavily contaminated sites, with biochemical analyses suggesting neurotoxic effects and activation of detoxification mechanisms in response to contaminants. Multivariate analyses revealed site-specific variations, highlighting the complex interactions between contamination levels and environmental conditions. Biomarker responses in gammarids served as sensitive indicators of residual toxicity in LSWBs, with frequent associations with historical contamination or current pesticide applications. This *in situ* caging approach across a contamination gradient demonstrates strong potential for biomonitoring and ecotoxicological assessments in agroecosystems. Extending exposure durations and including more heavily contaminated ponds could further enhance risk evaluation, thereby improving biomonitoring accuracy in headwater aquatic ecosystems. By integrating site-specific environmental conditions, contamination profiles, and biological responses, this study provides valuable insights into the influence of agricultural practices on LSWBs contamination and underscores the critical need to incorporate TPs into future risk assessment frameworks.

## 1. Introduction

The environmental dispersal of pesticides negatively impacts ecosystem health, affecting even remote areas (Ma et al., 2021; Riascos-Flores et al., 2021), and posing a global risk to aquatic ecosystems and the biodiversity they sustain (Köhler and Triebskorn, 2013; Akhtar et al., 2021; Wu et al., 2022).

As a result, many European water bodies are classified as degraded (Szöcs et al., 2017; Schreiner et al., 2021). Pesticides disrupt essential

ecosystem processes, altering the population structure of aquatic organisms, which is initially shaped by life-history traits and landscape characteristics (Rumschlag et al., 2020; Link et al., 2022). This leads to declines in sensitive taxa and losses in biodiversity in watercourses (Beketov et al., 2013; Bighiu et al., 2020).

Lentic small water bodies (LSWBs), such as barrage ponds receiving watershed runoff, are particularly sensitive to contamination from agricultural areas within their catchments. Representing a significant portion of total water bodies, these ponds are often used for fish farming

<footnote><sup>a</sup> Université de Lorraine, INRAE, L2A, Nancy F-54500, France</footnote>

<footnote><sup>b</sup> LTSER-Zone Atelier Moselle, Nancy F-57000, France</footnote>

<footnote><sup>c</sup> Office Français de la Biodiversité (OFB), Direction de la Recherche et de l'Appui Scientifique, 9 avenue Buffon, Orléans F45071, France</footnote>

<footnote><sup>d</sup> Université de Lorraine, CNRS, LIEC, Metz F-57000, France</footnote>

<footnote><sup>e</sup> ANSES, Nancy Laboratory for Hydrology, Water Chemistry Department, 40 Rue Lionnois, Nancy F-54000, France</footnote>

<footnote>* Corresponding author at: Université de Lorraine, INRAE, L2A, Nancy F-54500, France.</footnote>

<footnote>** Corresponding author.</footnote>

<footnote>E-mail addresses: gaspard.conseil@univ-lorraine.fr (G. Conseil), damien.banas@univ-lorraine.fr (D. Banas).</footnote>

<footnote n="1">¹ INRAE - National Research Institute for Agriculture, Food and the Environment (France)</footnote>
or livestock water supply and serve as reservoirs for water from tributaries that drain pesticide-intensive agricultural zones (Bichsel et al., 2016; Le Cor et al., 2021; Marín-Comitre et al., 2022).

Pesticides degrade in the environment through biotic and abiotic processes, resulting in transformation products (TPs) (Belfroid et al., 1998). The widespread use of pesticides has led to the global detection of TPs in aquatic ecosystems (Hernández et al., 2008; Anagnostopoulou et al., 2022; Tao et al., 2022), as each pesticide can degrade into several TPs (Fenner et al., 2013; Rocco et al., 2022). Moreover, some TPs persist longer in the environment than their parent compounds, accumulating in matrices such as biota or sediment (Albanis et al., 1998; Ng et al., 2011; Rodrigues et al., 2022; Slaby et al., 2022). Factors contributing to this persistence include remobilization from soils, delayed transfer times, and limited degradation in saturated zones (Baran et al., 2021; Hintze et al., 2024). In some instances, TP concentrations surpass those of the original pesticides, as reported by Le Cor et al. (2021) in headwater streams that feed into LSWBs. Similar findings were noted by Ulrich et al. (2021) in German water bodies, underscoring the necessity of including TPs in monitoring programs for accurate exposure risk assessments (Mahler et al., 2021).

Despite the confirmed presence of TPs at measurable concentrations, knowledge of their ecotoxicity remains limited, hindering assessment of their effects on aquatic organisms (Osano et al., 2002; Mottier et al., 2014; Velisek et al., 2018). To understand these overlooked toxic effects, reference ecotoxicological data (e.g., EC₅₀, NOEC) are necessary for comparison with environmental concentrations for environmental risk assessments (Conseil et al., 2024) or direct assessments in the field. In this context, field-based approaches, reflecting realistic conditions and complex contaminant mixtures, are increasingly being implemented to assess the environmental impacts of contamination, with both active and passive biomonitoring methods used to evaluate the health of various organisms in natural and anthropogenic environments (Kunz et al., 2010; Gewurtz et al., 2011; Bancel et al., 2024; Slaby et al., 2024). While acute or chronic lethality is assessed when pesticides are placed on the market, identifying sublethal adverse effects of these substances and their TPs requires a comprehensive approach. To detect these effects, biomarkers related to critical physiological and behavioral functions are used to gauge organism stress (Schuijt et al., 2021). A multi-biomarker approach at various levels—from organism to cellular fractions—enables effective early detection of unintended effects from multiple chemical exposures (Van Der Oost et al., 2003; Lomartire, 2021; Capparelli et al., 2023).

Aquatic invertebrates are suitable for ecotoxicological assessments due to their ethical acceptability, cost-effectiveness, and reliability. Amphipods such as gammarids serve as indicator species in aquatic food webs and are prevalent in European freshwaters, making them ideal for biomarker development to assess chemical impacts on aquatic environments (Kunz et al., 2010; Chaumot et al., 2015). Notably, pesticide exposure in these species can disrupt behavioral functions like locomotion. Locomotion studies are, therefore, valuable for detecting early sublethal effects (Nørum et al., 2011). Biochemical markers reflecting cellular stress, digestion, molting, or osmoregulation have also been proposed for early toxicity detection (Arce Funck et al., 2013; Dedourge-Geffard et al., 2013; Chaumot et al., 2015; Arce-Funck et al., 2018; Gauthier et al., 2023). The integration of behavioral and biochemical markers significantly enhances the detection of sublethal effects in *Gammarus spp.* exposed to a wide range of contaminants, as demonstrated in both laboratory and field studies (Kunz et al., 2010; Vellinger et al., 2012; Wigh et al., 2017; Lebrun and Gismondi, 2020).

*Gammarus roeseli* is a crustacean partly characterized by its wide distribution and its suitability for field transplantation (Böttger et al., 2012; Garaud et al., 2015). While caging experiments with sentinel species are common in rivers and large lakes, their application within LSWBs remain limited (Brodeur et al., 2021; Georgieva et al., 2022; Li et al., 2018). However, LSWBs, particularly in agricultural headwaters, are critical and vulnerable ecosystems acting as contaminant sinks, with

specific exposure dynamics (Ulrich et al., 2018; Bahi et al., 2023). The unique combination of shallow depth, stagnant flow, and fluctuating environmental conditions (e.g., temperature, oxygen) fosters the selection of more stress-tolerant communities, potentially dampening sublethal responses (Lorenz et al., 2017). Indeed, recent findings suggest that long-term exposure in lentic systems can reduce organism sensitivity to toxic effects, leading to response patterns distinct from those observed in lotic ecosystems (Wijewardene et al., 2021; Raudonytė-Svirbutavičienė et al., 2023). Despite these challenges, LSWBs (such as ponds) can serve as effective ecological sentinels in agricultural landscapes. Their ability to integrate multiple pressures over time makes them valuable and promising tools for environmental monitoring and ecotoxicological assessments. Recent studies support both the use of prospective risk assessment frameworks (Ulrich et al., 2022; Conseil et al., 2024) and the deployment of caged organisms coupled with biomarkers as sensitive early-warning systems in these settings (Slaby et al., 2023).

In this context, we aimed to assess whether contamination levels in LSWBs surrounded by agricultural fields could affect the health of aquatic organisms. We hypothesized that: 1) the selected LSWBs (n = 7), chosen based on an agricultural-use gradient in their watershed, would exhibit varying levels of contamination, and 2) impacts on the exposed organisms' biomarkers would differ depending on these levels. Ultimately, we sought to classify the investigated LSWBs based on biological responses to contamination, as this serves as a cornerstone of effective biomonitoring. To test this, we exposed *G. roeseli* individuals in cages in 7 water bodies for 7 days. Changes in various biomarkers after this exposure period were assessed and examined in relation to pesticide- and TP-contamination levels in the water, as sublethal responses can serve as early warning signals, allowing preventive action before ecosystem-level degradation becomes irreversible.

## 2. Materials and methods

### 2.1. Characterization of the study area

This study was conducted in fishponds on headwater streams in northeastern France, focusing on sites of ecological, economic, and agricultural significance for traditional fish production. The selection of these ponds leveraged prior research and collaborations with local fish farmers (Gaillard et al., 2016; Slaby et al., 2022). Fig. 1 illustrates the watershed composition of the 7 LSWBs under investigation. These LSWBs are located on impermeable marly substrates of the Middle Keuper (Upper Triassic) and clay-marl soils typical of the region (Gaillard, 2014). This consistent geological and pedological context, characterized by hydromorphic valley-bottom soils, limits groundwater exchanges and ensures similar substrate conditions across sites, making surface runoff the main pathway for pesticide transfer. Notably, although most ponds are surrounded by conventional agricultural practices, the area around site A has been managed organically for an extended period (15 years).

All selected LSWBs are extensively managed fishponds, with homogeneous management practices, notably without artificial feeding or chemical treatments. As a result, chemical inputs mainly originate from diffuse agricultural sources within the surrounding catchments. Detailed coordinates and catchment characteristics for each LSWBs are provided in Table S4. Pond surface areas and watershed features were analyzed using QGIS software (v.3.18.3 with GRASS 7.8.5) and data from Data-GrandEst and BD TOPO® IGN. The selected LSWBs represent a range of environmental contexts influenced by different agricultural practices, ensuring a diverse contamination gradient.

All LSWBs adjacent to agricultural areas are bordered by a minimum 5-meter-wide grass buffer strip. The experiments were conducted over an 11-day period, from June 12th to June 23rd, 2023, which included 4 days for acclimation (see 2.4) followed by 7 days of exposure. This timeframe was chosen to capture the occurrence of pesticides and TPs in
<figure><img src="image_4.png" /><figcaption>Fig. 1. Map of the entire study area displaying the 7 studied ponds, denoted by letters A to G. The map was generated using QGIS (v.3.18.3).</figcaption></figure>

the ponds during late spring, a period associated with contaminant accumulation and retention in LSWBs (Gaillard et al., 2016).

## 2.2. Chemical analysis

### 2.2.1. Water grab sampling and extract preparation

To measure contamination at each studied site, 10-L water samples were obtained at 3 water-sampling times—the beginning (T0), end (T7), and throughout the 7-day exposure—to create an average composite sample (T0–7). Composite samples were obtained using automatic samplers that collected water at a frequency of 12 samples per day. An additional 10-L water sample was collected as a grab sample from each site at the end of the experiment (T7) for use in behavioral tests (i.e., ventilation and locomotion, see 2.8 below) conducted immediately after the exposure period. Samples were stored in glass bottles (ISO 4796–1:2016; 10 L), transported in reefer containers, and kept at –18 °C until chemical analysis. The methodology described by Pasquini et al. (2025) was followed.

### 2.2.2. Analysis of pesticides

LC-MS-grade acetonitrile (ACN), dichloromethane, dimethyl sulfoxide, formic acid, methanol, and ultrapure water were utilized in this study. Analytical standard solutions of the studied pesticides (purity >96%, mostly >99%, Dufour et al., 2021) were prepared in ACN (100 mg/L), stored at –18 °C, and mixed to achieve a concentration of 5 µg/L. Native and isotope-labeled compounds (13 C and 2 H) were obtained from various suppliers, while certain transformation product (TP) standards not commercially available were sourced from agricultural companies (Table S1).

The pesticide and TP list was based on two decades of watershed treatment analyses and included both currently used and historically banned contaminants still detectable in the environment. This selection prioritized TPs due to their stability and prevalence over parent compounds in aquatic systems, evidenced by recent insights into freshwater contamination in Europe (Kiefer et al., 2019; Menger et al., 2021). A total of 136 compounds, comprising substances prioritized by the EU Water Framework Directive (WFD) for water quality monitoring, along with relevant TPs as specified by EU Directive 2020/2184, were included in this analysis. The analyte list, organized by chemical class, is
shown in Table S1 and includes 24 herbicides with 52 TPs, 7 fungicides with 16 TPs, 13 insecticides with 23 TPs, and 1 common TP from the benzamide family. The limits of quantification and measurement uncertainties for these substances analyzed by LHN-ANSES (the French national reference laboratory for water monitoring) are particularly low and are provided in Table S2.

## 2.3. Collection and maintenance of exposed gammarids

Specimens of *G. roeseli* were collected in June 2023 using a hand net in the Nied River (Rémilly, northeastern France), which served as the original supply site (OS) for gammarids. This OS has been used in several studies (e.g., Andreï et al., 2016; Techer and Banas, 2018), and will enable the amplitude of responses to be compared with other studies.

The amphipod *Gammarus roeseli*, native to the Balkans, was first observed in France around 1835 (Jaźdżewski, 1980). In France, this freshwater species, inhabiting ponds, lakes, and streams (Karaman and Pinkster, 1977), long described as an exotic or invasive species, is now considered to be a naturalized species. This amphipod is iteroparous, but depending on environmental conditions (temperature, food resources, etc.), its lifespan ranges between 1 and 3 years. Compared to other *Gammarus* species, *G. roeseli* is more abundant at warmer temperatures and in rivers with moderate water flow (Pöckl and Humpesch, 1990; Pöckl et al., 2003). *G. roeseli* was selected because this species i) inhabits ponds, ii) is holobiotic, iii) is widespread, iv) often occurs at high densities and is easy to collect, v) is easy to identify down to the species level, vi) is characterized by sexual dimorphism, vii) is sensitive to a wide range of stresses, viii) is currently used in ecotoxicological tests, ix) is considered an important food resource for macroinvertebrates, fish, birds, and amphibians (MacNeil et al., 2000), and x) plays a major role in the leaf litter breakdown process as an omnivorous shredder, and consequently in the entire aquatic food web (Forrow and Maltby, 2000).

Size and sex sorting were conducted in the field, with adults calibrated to $1.0 \pm 0.25$ cm in length and sex differentiated during pre-copulation or according to gnathopod size, a sexually dimorphic trait. The gammarids were transported back to the laboratory in a refrigerated box containing site water and ice blocks.

Some specimens were directly preserved for future analysis at the time of sampling to reflect the initial health status (Initial State: IS). Acclimation occurred in a climatic chamber (Aralab FITOCLIMA 600) using water from OS for a duration of 4 days, after which T0 of the experiment began. During acclimation, specimens were fed *ad libitum* with rehydrated alder leaves (*Alnus glutinosa*) from a natural forest. The study focused on male gammarids of calibrated size to standardize putative variations in digestive metabolism, reproductive state, and energy reserves, while also ensuring the use of non-parasitized individuals to avoid influencing measured responses (Gismondi et al., 2012a; Charron et al., 2013; Rothe et al., 2022; Grabner et al., 2023).

## 2.4. Exposition set-up

At T0, for control exposure, organisms were deployed at OS using a fixed-attachment system positioned at the waterbed's edge. This setup ensured that the cages containing the gammarids were suspended mid-stream, following established biomonitoring protocols for *Gammarus spp.* (Coulaud et al., 2011). The purpose of this control exposure was to isolate the effects of caging itself at the OS, thereby minimizing confounding factors in the post-exposure assessment of stress and biological responses.

Simultaneously, organisms from the same population were exposed in several ponds using a custom-designed floating system fabricated in the laboratory (Fig. S1.1), enabling comparison across different environmental conditions. For practical and logistical reasons, pond exposures were conducted over 3 consecutive periods, each corresponding to a 7-day exposure (Fig. S1.2). Tetrahedral polypropylene cages fabricated in-house, with a volume of 1.2 L ($12 \times 20$ cm), were used. One-

millimeter mesh facilitated continuous water exchange while retaining the organisms inside the cages. For each site, 80 gammarids were exposed using 4 cages (replicates) containing 20 individuals each, and supplemented with *A. glutinosa* leaves ($5.48 \pm 0.69$ g per cage) to mitigate cannibalism (Dick, 1995; Kinzler et al., 2009). The cages were assembled and sealed in the field to minimize transport stress. A consistent number of organisms (80 individuals) was used for the initial characterization of health status at OS before exposure.

## 2.5. Mortality monitoring

At T7 at each site (the 7 LSWBs and OS), gammarids were removed from the cages. Suspected dead individuals were examined under a binocular microscope, with death defined as the absence of response to gentle mechanical stimulation (Taylor et al., 1994) and the lack of other physiological activities such as ventilation. The number of dead individuals was counted to calculate a survival rate (%). Subsequent analyses were conducted on the surviving gammarids at the end of the exposure period (T7).

## 2.6. Sample/homogenate preparation

At T7, and for each site, the live gammarids were subjected to locomotion and ventilation tests (see 2.8 below) before being dried with filter paper and pooled into 3 groups. These groups corresponded to 3 of the 4 cages set up at each site, each containing 5 male gammarids for biomarker and energy reserve measurements. The 4th cage was included as a contingency to account for potential high mortality, but in practice, analyses were based on samples from 3 cages (triplicate). Each pool was weighed to ensure a minimum mass of 10 mg for adequate reactivity in the assay methods, with variations considered negligible (Xuereb et al., 2009a). The gammarids were flash-frozen in liquid nitrogen and stored in 2-mL centrifuge tubes at -80 °C. Homogenates were prepared by bead milling in extraction phosphate buffer using an oscillating mill (Retsch MM 400, Haan, Germany) with 2 steel beads (Ø 2 mm) and 2 glass beads (Ø 4 mm) over three 30-second milling sessions at 30 Hz/s. The homogenates were then centrifuged (Eppendorf 5804 R, Hamburg, Germany) at 9000 g for 15 minutes at 4 °C.

Cytosolic supernatants (post-mitochondrial or S9 fractions) were collected and aliquoted into 100-µL portions in microtubes (250 µL), with at least 10 aliquots per pool for subsequent assays. The S9 fractions were used for assays and total protein quantification in a 96-well microplate system at room temperature. All biochemical and enzymatic assays were performed in the following months.

## 2.7. Behavioral traits

### 2.7.1. Locomotor activity

Locomotor activity was assessed using a modified method from Felten et al. (2008). Ten gammarids were observed for each group (i.e., each cage), and the number of times they crossed a radial line in a tank containing 800 mL of exposure medium was recorded. At T7 and at each site, 10 living gammarids from each cage were placed in a beaker with water collected at T7 from their exposure site. Following a 5-minute acclimation period, observations were made under consistent lighting conditions. The number of *G. roeseli* individuals crossing the radial line was recorded over a 30-second interval, repeated 3 times. This activity was used as a proxy for the metabolic status related to movement following exposure. Results are expressed as the number of line crossings per minute (LC/min).

### 2.7.2. Ventilatory activity

Using the same gammarids from the locomotion characterization, ventilatory activity was recorded by counting pleopod beats for 1 minute following the method described by Hervant et al. (1997). Each gammarid was placed in a glass tube measuring 25 cm in length and
0.75 cm in width, and allowed to acclimate for 30 seconds. Pleopod beats were then counted visually using a manual cell counter, but only when the animal was at rest. Results are expressed as pleopod beats per minute (PB/min).

## 2.8. Multi-biomarker approach

The use of diverse biomarkers aims to capture the various mechanisms by which contaminants exert their effects, enhancing the assessment of environmental quality beyond simple measures of mortality or behavior (Milinkovitch et al., 2019). Except for mortality (2.6) and behavioral tests (2.8), all biomarkers were measured on the in toto homogenates (2.7). For these analyses, 3 pools, each representing one of the 3 selected cages, were used to ensure the results were representative of the different replicates. Furthermore, each biomarker measurement was performed in technical triplicates to enhance the reliability and robustness of the data. All readings from the assays were conducted using a multimode microplate reader (BioTek Synergy HT; BioTek Instruments, United States).

### 2.8.1. Proteins

Total protein content in the S9 fraction, which includes enzymes involved in xenobiotic metabolism, was quantified using the Pierce BCA Protein Assay Kit (Pierce Biotechnology, Rockford, Illinois, USA). Measurements were calibrated with a bovine serum albumin (BSA) standard curve prepared by serial dilutions in a 96-well microtiter plate, following the manufacturer's instructions. This method normalizes biochemical activities, providing a weighting factor, with all biomarker activities adjusted according to protein content (except for AChE). All biomarkers are reported as nmoles of substrate hydrolyzed per minute per mg of protein (nmol/min/mg protein), with AChE reported as nmoles per mg of fresh weight (nmol/min/mg fw).

### 2.8.2. Energy reserves

Glucose serves as the primary energy source among energy reserves, with elevated levels indicating sudden glycogen depletion, often signaling stress responses or metabolic disturbances. The total sugar assay was based on the protocol of Masuko et al. (2005), adapted from Dubois et al. (1956). In brief, concentrated sulfuric acid dehydrates saccharides and polysaccharides (e.g., glycogen), forming orange-colored complexes with phenol. These complexes were quantified at 490 nm and expressed as glucose equivalents using a standard curve (obtained from standard solution of glucose monohydrate). The carbohydrate concentrations are reported in mg/g fresh weight.

### 2.8.3. Neurotoxicity (acetylcholinesterase; AChE)

Variations in acetylcholinesterase activity were used as a biomarker for neurotoxicity, following a method adapted from Ellman et al. (1961) for microplates (see Xuereb et al., 2007). This response is related to behavioral changes (Xuereb et al., 2009b) and has proven effective for field surveys (Xuereb et al., 2009a). In essence, 20 µL of 0.0076 M dithiobisnitrobenzoate, 20 µL of S9 fraction, 330 µL of 0.1 M phosphate buffer, and 10 µL of acetylthiocholine iodide solution were added in each well of a 96-well microtiter plate. The hydrolysis of acetylthiocholine iodide, producing the yellow product 5-thio-2-nitrobenzoic acid, was monitored at 405 nm every minute for at least 4 minutes. Significant inhibition or enhancement was defined as a 10 % change compared to OS, indicating potential exposure to neurotoxic compounds.

### 2.8.4. Metabolism protection (carboxylesterase; CbE)

Carboxylesterase (CbE) was selected as a biomarker for its critical role in detoxifying ester-based insecticides such as carbamates and organophosphates. By breaking down ester groups into alcohol and acid, these enzymes help mitigate the toxic effects of these contaminants. CbE activity was measured using a method adapted from Ljungquist and

Augustinsson (1971) and refined for microplates by Baker et al. (1998). The assay employs 4-nitrophenyl acetate (4NA) as a substrate, and CbE activity results in the formation of yellow nitrophenol. This product is quantified by measuring absorbance at 405 nm every minute for 4 minutes at 20 °C.

### 2.8.5. Detoxification activity (glutathione S-transferase; GST)

Glutathione S-transferase (GST) detoxifies hydrophobic xenobiotics like PCBs, PAHs, and pesticides. As part of the antioxidant defense, its activity serves as a biomarker for contaminant exposure, generally increasing with pollutants but potentially inhibited under severe toxicity. Glutathione S-transferase (GST) activity was measured following the method of Habig et al. (1976). Each of the 96 microplate wells received 170 µL of 2.2 mM reduced glutathione, 10 µL of 38 mM 1-chloro-2,4-dinitrobenzene, 150 µL of 0.1 M phosphate buffer, and 20 µL of the S9 fraction. The GST activity was assessed at 340 nm, with measurements taken every minute for at least 4 minutes.

### 2.8.6. Oxidative damage (thiobarbituric acid reactive substances; TBARS)

Thiobarbituric acid reactive substance (TBARS) content serves as an integrative parameter for assessing oxidative stress, reflecting the consequences of lipid peroxidation. Elevated TBARS levels indicate increased oxidative damage, often resulting from stressors like pesticide exposure. The concentration of TBARS was determined using a method originally developed by Ohkawa et al. (1978), with further adaptations made based on the protocol by Camejo et al. (1998) for microplate applications. TBARS primarily comprise malondialdehyde (MDA), a byproduct of lipid peroxidation. This assay involves reacting MDA with thiobarbituric acid (TBA) under acidic and heated conditions, producing a fluorescent pigment (excitation at 532 nm, emission at 553 nm). To prevent the artificial formation of MDA during the assay, butylated hydroxytoluene (BHT) is added as an antioxidant. Calibration is achieved using MDA standards, generated by acid hydrolysis of a 1,1,3,3-tetramethoxypropane (TMP) solution.

## 2.9. Statistical analysis

All statistical analyses were conducted using R software version 4.3.3. Water concentrations of pesticides and TPs, along with behavioral and biochemical data, are presented as mean ± standard error of the mean (SEM). Prior to statistical testing, normality was assessed using Shapiro's test, and homogeneity of variance was evaluated using Levene's test. Based on these assessments, differences between exposure conditions in the ponds and OS were analyzed. To ensure the relevance of the caged organisms used as controls, additional comparisons were conducted between non-caged individuals sampled at T0 and those retrieved after 7 days of caging at the origin site (T7-OS). Details of this analysis are available in Table S7 of the supplementary material.

Environmental parameters were examined separately using ANOVA followed by Tukey's test for parametric data, or Kruskal-Wallis tests followed by Dunn's test for non-parametric data. Behavioral traits and biomarker responses from ponds A to G were compared to those from the OS using either t-tests or Mann-Whitney tests, depending on data distribution. The biochemical responses of gammarids were closely analyzed, focusing on deviations from post-exposure conditions in OS, which served as a negative control. Additionally, biomarker responses and environmental parameters underwent hierarchical agglomerative clustering (HAC), alongside a standardized principal component analysis (PCA) that included biological responses, contamination levels, and key environmental parameters as explanatory variables. To mitigate multidimensional noise, the analysis focused on the first 4 dimensions (explained variance = 75.4 %). The resulting biplot was based on the first 2 dimensions, which accounted for 50.1 % of the total dataset inertia. These analyses aimed to elucidate the relationships between biomarker responses and LSWB characteristics, facilitating the classification of sites. All hypotheses were tested at the α = 0.05 significance
level.

# 3. Results

## 3.1. Environmental conditions of the ponds

Key environmental parameters related to the pond conditions are detailed in Table S5 (mean ± SD). The origin site (OS) of the gammarids had the coolest water (20.2 ± 0.6 °C). Temperature exhibited slight variations across the studied pond sites, with site A (25.1 ± 1.1 °C) being marginally warmer than most other sites, and significantly different to OS and site G (21.9 ± 0.8 °C). Oxygen levels were strongly variable, with a maximum of 6.8 mg/L (site A and OS) and relatively low values for sites E to G (<3.8 mg/L, with a minimum of 2.8 ± 0.7 mg/L in site G). Conductivity showed the greatest variation among environmental conditions, notably between site F and OS (173.3 ± 4.7 vs. 1976 ± 20.8 µS/cm, respectively; a significant difference). Monthly precipitation data for 2023, depicted in a histogram (Fig. S2), indicate that June was the second-driest month of the year, with only 1.14 mm of rain.

## 3.2. Quantification of contamination within the sites

In the 7 ponds, the 136 contaminants were searched for and quantified in samples collected at T0, T7, and in the composite mean sample T0-7. Among these 44 pesticides and 92 TPs analyzed, 4 pesticides and 25 TPs were quantified, representing 9.1 % and 27.2 % of the targeted contaminants, respectively. Detailed site-specific concentrations, including mean values ± SEM and minimum and maximum values, are available in Table S6. Average contaminant concentrations quantified at the 3 water sampling times (T0, T0-7, and T7), from 3 water samples revealed that while some contaminants were detected only sporadically, others were consistently prevalent. Notably, concentrations exceeding 500 ng/L were recorded for flufenacet ESA and metolachlor ESA, both at site C. The sums of average concentrations are illustrated in Fig. 2,

providing an overview of the total contaminant load at each site (in ng/L).

Site C exhibited the highest total contamination level among the studied LSWBs, with a concentration of 2692 ± 60 ng/L. In contrast, site D was the least contaminated, with values of 161 ± 8.95 ng/L (denoted by letter “b” in Fig. 2). Site OS, from which the gammarids were collected, showed an intermediate contamination level of 633 ± 14.7 ng/L (indicated by the dotted line in Fig. 2). At this site, contamination was predominantly composed of TPs, with only 2 parent compounds (bentazone and metolachlor) present, together accounting for only 1.9 % of the total concentration. Overall, based on the statistical analyses related to contamination, 3 distinct groups were identified: site D (low contamination levels); sites A, B, E, F, and OS (intermediate contamination); and sites C and G (notably high contamination).

Moreover, 5 compounds were frequently quantified across all sites, appearing in over 75 % of the samples: chlorothalonil R471811 (96 %), metazachlor ESA (88 %), metazachlor OXA (75 %), terbuthylazine metabolite LM2 (75 %), and metolachlor ESA (75 %). Notably, the 10 most frequently quantified molecules were TPs, two of which originated from banned pesticides (metolachlor ESA and atrazine-2-hydroxy). Among the 7 ponds studied, 5 sites exhibited a contaminant profile exclusively composed of TPs (see Fig. S3). Site G had the highest number of TPs (n = 18) despite no pesticides being detected in it.

## 3.3. Individual mortality

After 7 days of exposure, the survival rate of gammarids at OS was 91.25 %. In contrast, survival rates in the ponds ranged from 63.8 ± 8.5 % to 82.5 ± 10.4 %, with most sites maintaining rates above 70 %. Compared to OS, significantly lower survival rates were recorded in sites B (71.3 ± 11.1 %), C (63.8 ± 8.5 %), F (70 ± 10.8 %), and G (68.8 ± 8.5 %), while high and similar survival rates (exceeding 75 %) were observed in sites D and E (Fig. S4; Wilcoxon tests; $p \le 0.05$). Beyond mortality, we first verified the relevance of the control group.

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Sums of average water concentrations of contaminants (pesticides and TPs, in ng/L) by site (from A to G, at T0, T0-7, and T7). Data are expressed as mean ± standard error (n = 3). Molecules not quantified (<LOQ) were assigned a value of 0. The dashed black line represents the contamination state of the origin site (OS). Groups sharing the same letter do not differ significantly according to Kruskal-Wallis test followed by Dunn's post hoc test.</figcaption></figure>
No significant differences were found between IS (T0) and OS (T7) organisms, except for a slight increase in ventilation rate (Table S7), confirming that caging had no substantial impact. Comparisons were thus performed against OS individuals to ensure consistency across exposure conditions.

### 3.4. Behavioral responses

The average number of line crossings (LC) for control organisms was 5.1 ± 0.2 LC/min (OS at T7; Fig. 3A). Site D exhibited a non-significant reduction (8 %) in locomotion compared to OS. Significant reductions in locomotor activity were observed at site A (decrease of 18 %, t-test; p < 0.05) and more pronounced decreases (p < 0.01) at sites F and G (by 25 % and 23 %, respectively), with site C showing the most substantial reduction (by 31 %).

The pleopod beat rate for control organisms was 253.3 ± 5 PB/min (OS at T7; Fig. 3B), with the lowest rate (181.9 ± 6.3 PB/min) recorded at site C, representing a 28 % reduction. In contrast, site E exhibited the highest rate (291.6 ± 8 PB/min), corresponding to a 15 % increase compared to the control.

Compared to the reference value (OS), a significant increase in pleopod beats, indicative of hyperventilation, was noted at sites D and E (p < 0.01). Conversely, hypoventilation, characterized by a significant reduction in pleopod beats relative to OS, was observed at sites A, C, F, and G (p < 0.01), with a minimum decrease of 16 % at site G.

### 3.5. Biochemical responses

Different biochemical responses were closely examined based on their percentage of deviations from OS for each site (Fig. 4; for each biomarker, see Fig. S5).

Protein content ranged from 17.28 ± 1.72 mg/g fresh weight at site E to 31.65 ± 0.7 mg/g fresh weight at site F. Compared to OS (18.28 ± 0.48 mg/g fresh weight), significant differences in protein levels were observed at sites A and C (t-test, p < 0.05; Fig. 4 & S5.1).

The mean carbohydrate concentration, expressed as glucose equivalent and used as a proxy for fast energy reserves, was 8.09 ± 0.66 mg/g at the origin site and ranged from 1.25 to 13.07 mg/g. Compared to OS, a significantly lower carbohydrate content was detected at site B (t-test, p < 0.01), whereas higher carbohydrate contents were detected at sites C and F (t-test, p < 0.05; Fig. 4 & S5.2)

In the neurotoxicity evaluation, baseline AChE activity in gammarids after 7 days of exposure at OS was 4.45 ± 0.2 nmol/min/mg of fresh weight. Compared to the control (OS), a significant increase in AChE activity was observed at sites A, C, F, and G (Mann-Whitney U test, p < 0.01; Fig. 4 & S5.3), with a maximum increase of 77 % for site C exposure.

Although CbE is part of the same esterase family as AChE, its activity exhibited significant but less-pronounced variations across exposure conditions, possibly due to high variability among triplicate measurements (see large standard errors, e.g., at site D). The baseline CbE activity at OS was 47.70 ± 8.27 nmol/min/mg protein, and the sole significant difference to this—a drop by 68 %—was recorded after 7-day exposure at site C (t-test, p < 0.01; Fig. 4 & S5.4).

For detoxification activity, glutathione S-transferase (GST) and thiobarbituric acid reactive substances (TBARS) were analyzed. GST activity for exposures at sites A, B, E, and F showed significant increases, ranging from 3 % to 164 % (site A), compared to OS (2.66 ± 1.12 nmol/min/mg protein; p < 0.05; Fig. 4 & S5.5). An increasing trend was also noted at site G (p ≈ 0.096).

The baseline TBARS activity at OS was 25.82 ± 1.64 nmol<sub>MDA</sub>/min/mg protein, with values ranging from 18.7 (site F) to 34.4 (site E) nmol<sub>MDA</sub>/min/mg protein across all LSWBs. Compared to OS, gammarids exposed to site C showed a statistically significant increase of 25 % in TBARS activity (p < 0.05; Fig. 4 & S5.6), whereas those exposed to site F exhibited a significant reduction of 27 % (p < 0.05).

### 3.6. Multivariate integration of biological responses

To comprehensively analyze the observed variations and underlying patterns, a principal component analysis (PCA) was performed, with the first 2 dimensions explaining a combined variance of 50.1 % (Fig. S6). In the variable-based PCA plot (Fig. S7), the primary contributors to dimension 1 were AChE, ventilation, and locomotion, accounting for 20.15 %, 18.41 %, and 12.2 % of the variance, respectively. Dimension 2 was predominantly influenced by GST (28.74 %) and conductivity (26.98 %), critical for site differentiation (Fig. 5A).

The PCA biplot (Fig. 5A) illustrates the relationships between environmental parameters and the biochemical and physiological responses of *G. roeseli* across various sites, and shows that pesticide concentrations correlated positively with AChE activity and negatively with CbE activity. Site C was noted for its high pesticide contamination and elevated

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Behavioral traits measured following *in situ* exposure (at T7) at each site. A. Locomotion, represented by the number of line crossings per minute (LC/min). B. Ventilation, measured as the number of pleopod beats per minute (PB/min). Data are expressed as mean ± standard error (n = 12). Statistical analyses included a U test for ventilation and a t-test for locomotion, comparing each site against the control site at T7 (OS; \*p < 0.05; \*\*p < 0.01).</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Fig. 4. Differential biochemical responses and protein levels in *Gammarus roeseli* observed after field exposure, shown as percentage deviations from the control (OS) under various exposure conditions. Deviations are expressed as positive or negative percentages relative to the control. Error bars represent the standard error of the mean (SEM; n = 3). Significant differences from the control are indicated by * (p-value < 0.05) and ** (p-value < 0.01) based on t-tests or U tests on the original data (not on percentage). AChE, acetylcholinesterase; CbE, carboxylesterase; GST, glutathione S-transferase; and TBARS, thiobarbituric acid reactive substances.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 5. Results of principal component analysis (PCA) of biomarker responses and environmental parameters measured at study sites, followed by hierarchical agglomerative clustering (HCA). A. Biplot with site delineation using ellipses around the centroids. Each dot represents a pool of gammarids. B. Dendrogram representation of the HCA (based on 3 cages per site).</figcaption></figure>

AChE activity. Conversely, site F showed an increase in protein and carbohydrate levels. Sites D, B, and E exhibited similar behavioral disturbances and carboxylesterase (CbE) activity. In contrast, OS had unique environmental conditions with elevated conductivity and oxygen levels, representing a baseline with minimal contamination and less biochemical stress compared to more contaminated sites.

The clustering analysis further revealed 4 distinct site-specific response clusters (Fig. 5B), highlighting the variability in environmental conditions and in the biological responses of the gammarids. It is important to note that some sites do not fully correspond to a single,

homogeneous cluster, as each site is represented by 3 independent conditions (i.e., 3 cages). Therefore, the observed disparity within a site can be attributed to inter-cage variability. Cluster 1, encompassing sites C, F, and G, was characterized by heightened metabolic activity, reduced behavioral activity, and enhanced detoxification processes. In contrast, Cluster 2, comprising sites D and E, exhibited reduced activity of metabolic and enzymatic markers, with ventilation serving as a key indicator of this cluster. Cluster 3, consisting of sites A and B, displayed a metabolic shift toward adaptation, marked by a concurrent decrease in carbohydrate levels and a slight increase in protein levels. Finally,
Cluster 4, primarily comprising OS (along with a single observation from site D), was characterized by elevated conductivity and oxygen levels, serving as a control for interpreting the physiological and biochemical responses observed at more impacted sites. In summary, the clustering analysis highlights the intricate nature of stress responses in caged crustaceans, revealing distinct physiological and biochemical acclimation patterns across the study sites.

# 4. Discussion

## 4.1. Environmental stress dynamics and multi-contamination by TPs in LSWBs

This study assessed the effects of pesticide and transformation product (TP) contamination levels in headwater lentic small water bodies (LSWBs) on the survival and biomarker responses of *Gammarus roeseli*. Environmental parameters such as hypoxia, temperature variations, and natural stressors likely played a significant role in shaping the physiological stress experienced by *G. roeseli*. Conductivity varied significantly among sites, with the highest conductivity (1976 ± 20.8 µS/cm) detected at the origin site (OS), potentially due to natural mineralization or upstream inputs, and the lowest at site F (173.3 ± 4.7 µS/cm). The acclimation phase (2.4) adjusted the gammarids' environment to match the LSWBs' conductivity, minimizing osmotic stress and its impact on ventilation.

Critically low dissolved oxygen levels were recorded at sites E and G (3.1 ± 1 mg/L and 2.8 ± 0.7 mg/L, respectively), yet mortality rates varied: Site G exhibited reduced survival, whereas site E showed resilience, suggesting other factors modulated these outcomes. *G. roeseli* prefers stagnant, muddy water and is sensitive to agitation rather than temperature variations (Roux *et al.*, 1980). Its low-oxygen tolerance is similar to that of *G. pulex* (positive rheotaxis cessation at 3.1 and 2.7 mg/L, respectively; Vobis, 1973), whereas *G. fossarum* requires higher oxygen levels (5.3 mg/L; Henry and Danielopol, 1998). Unlike *G. fossarum*, *G. roeseli* demonstrates the ability to withstand hypoxia in caged conditions, as shown in this study, reinforcing its suitability for lotic environments with fluctuating oxygen levels (Williams *et al.*, 2004).

Temperature variations, ranging from 21.9 ± 0.8 °C at site G to 25.1 ± 1.1 °C at site A, may have further influenced metabolic rates and sensitivity to toxic exposure (Sornom *et al.*, 2010). The prolonged dry period during the study, followed by occasional rainfall (Fig. S2), simulated field-relevant short-term exposures, emphasizing the risk of episodic pesticide inputs after rain events. Most quantified compounds were herbicides, which target photosynthetic organisms but can adversely affect non-target species like aquatic invertebrates (Liebmann *et al.*, 2024).

Indeed, beyond the environmental conditions inherent to each site, contamination appears to have been a major contributing factor. Significant multi-contamination was observed across sites, with TPs identified as the primary contaminants. Out of the 91 compounds analyzed, 25 TPs were quantified, accounting for approximately 86 % of total contaminant occurrence, with flufenacet-ESA concentrations reaching up to 560 ng/L at site C. This concentration alone exceeds the drinking water limit set for the sum of pesticides by the EU Drinking Water Directive 98/83/EC. This finding aligns with Ulrich *et al.* (2021), who identified similar TPs (e.g., metazachlor ESA and OXA) in agricultural water bodies in Germany. Our research extends this knowledge to headwater ponds, including forested areas that have not been treated with these herbicides.

The highest contamination levels were recorded at site C, with total concentrations of 2692 ± 60 ng/L, while site D had the lowest, at 161 ± 8.95 ng/L. TPs were detected at all sites, often at concentrations exceeding those of their parent compounds, indicating potential transport via both water and atmospheric processes. The rapid transformation rates of certain pesticides, such as metolachlor (Table S3;

water-phase DT₅₀ of 9 days; PPDB; Lewis *et al.*, 2016), likely accounted for the more frequent detection of TPs compared to their parent compounds. Additionally, the hydraulic residence time in these lentic environments may promote pesticide degradation (Gaullier *et al.*, 2019), leading to limited detection of parent compounds, as noted by Mahler *et al.* (2021) in small streams in the United States. The shallow depth of LSWBs enhances the water-sediment and water-air interfaces, promoting the development of biotic matrices (e.g., plants, biofilm) that facilitate pesticide degradation more effectively than in deeper aquatic ecosystems (Hijosa-Valsero *et al.*, 2016; Slaby *et al.*, 2022; Hu and Tao, 2023). Although TPs are also present in lotic environments, their concentrations tend to be lower, indicating a more pronounced presence in LSWBs (Feng *et al.*, 2024). Nonetheless, in the aforementioned study, TPs accounted for an average of 51 % of the total concentration, highlighting their significant role in the contamination of lotic waters.

Our results indicated that oxalic (OXA) and ethanesulfonic (ESA) acids from chloroacetanilide pesticides, along with TPs from dimethachlor, flufenacet, and metolachlor, were frequently quantified (FOQ > 50 %). Chloroacetanilides and their TPs are prevalent in French waters due to extensive use in maize cultivation (Hvězdová *et al.*, 2018; Baran *et al.*, 2021). The ponds with the highest contaminant concentrations (C, E, F, and G) corresponded to the largest agricultural areas in their watersheds (Table S4.2), consistent with findings from other contexts, such as river sub-catchments (Dabrowski *et al.*, 2002). In watersheds with reduced pesticide use, sites like pond A may still exhibit residual effects from past applications. Riedo *et al.* (2021) documented persistent impacts of historical pesticide use on soil bacterial communities, which may similarly affect aquatic fauna and flora in organically managed systems. Likewise, Fisher *et al.* (2021) observed that TPs, including those from acetanilide and aldicarb, remained in Long Island's (USA) groundwater decades after their ban, underscoring the enduring impacts of historical pesticide use. Various input pathways (e.g., drift, volatilization) may significantly influence the contamination status of LSWBs, highlighting the need for a comprehensive understanding of long-distance transport phenomena and aerial deposition of pesticides to protect aquatic biota (Matthies *et al.*, 2009; Bish *et al.*, 2021). Additionally, the long-term persistence of TPs in these systems, considering both current and historical applications, warrants further investigation (Chiaia-Hernandez *et al.*, 2017). As our understanding of TPs has advanced, it has become increasingly essential to monitor both TPs and their parent compounds (Rousis *et al.*, 2017; Menger *et al.*, 2021).

These combined environmental stressors may have acted synergistically, potentially amplifying the physiological challenges faced by the studied gammarids. Hypoxic conditions at sites E and G may have impaired the gammarids' detoxification mechanisms, while elevated temperatures at site A could have heightened metabolism and its demands, increasing their susceptibility to chemical stressors. This environment-contaminant interaction underscores the complexity of assessing health impacts on aquatic organisms in LSWBs.

## 4.2. Gammarid health altered overall

### 4.2.1. Behavioral responses, potential neurotoxicity, and survival outcomes

Survival rates were significantly reduced at sites C and G compared to OS (91.25 %). While mortality is a common indicator of toxicity, investigations focused solely on it often overlook the sublethal effects of pesticides (Palma *et al.*, 2016). Understanding these effects is crucial for grasping the processes leading to mortality of crustaceans (Di Nica *et al.*, 2020; Lebrun *et al.*, 2020; Damasceno *et al.*, 2021). Indeed, the observed declines in survival were linked to behavioral changes, particularly reduced locomotion. Locomotion is a critical endpoint in ecotoxicological studies and is recognized in eco-neurotoxicity research (Legradi *et al.*, 2018; Wlodkowic *et al.*, 2022). Hypoactivity at sites A, C, F, and G may have resulted from energetic reallocation for maintenance (detoxification, compensation; Felten *et al.*, 2008b; Arce Funck *et al.*, 2013) but also from neurotoxic effects associated with elevated
acetylcholinesterase (AChE) activity, especially at site C, where AChE levels increased by 77% (Fig. 4). Although gammarids typically show hypoactivity under AChE inhibitors such as insecticides (Xuereb et al., 2007; Nyman et al., 2013), AChE hyperactivity has also been reported after sublethal pollutant exposure (organophosphorus compounds: Flammarion et al., 2002; Romani et al., 2005; Gagnaire et al., 2008; metals: Romani et al., 2003), although its biological mechanism remains unclear in aquatic organisms. This unexpected AChE induction could be linked to cellular apoptosis (Knorr et al., 2023) or sterile inflammation (Zivkovic et al., 2023), but may also arise from variability in enzymatic activity or rapid adaptation responses (Domingues et al., 2010). Interaction between pesticides can enhance AChE activity through synergistic effects, as seen in *Ceriodaphnia dubia* (Woods et al., 2002). This indicates that even though organisms attempt to manage neurotoxic stress, their detoxification capacity is compromised, as demonstrated by the reduced carboxylesterase (CbE) activity at site C. This imbalance heightens physiological strain and diminishes locomotor function.

The observed ventilation patterns were aligned with survival outcomes: increased pleopod beats at sites D and E suggested compensatory responses of gammarids (to hypoxia or chemical stress), while reduced activity at sites A, C, F, and G indicated close-to-death organisms, particularly at site C (Vellinger et al., 2012). Sublethal contaminant exposure can impair performance, with initial hyperventilation potentially shifting to hypoventilation under prolonged stress (De Lange et al., 2006; Vellinger et al., 2012). Reduced ventilation likely reflects diminished oxygen extraction efficiency, compromising metabolic homeostasis and detoxification capacity (Zhang et al., 2022), with broader implications for survival and health. Taken together, these behavioral responses, coupled with the observed mortality rates, highlight the organisms' inability to maintain homeostasis under the combined pressures of chemical and environmental stressors. Furthermore, TPs, which remain poorly characterized and exhibit uncertain modes of action, may disrupt these behaviors and lead to unforeseen impacts, including endocrine disruption (Ji et al., 2020).

### 4.2.2. Energy gestion and detoxification process

Energy reserves were analyzed to understand how *G. roeseli* managed the metabolic costs of contaminant exposure. Carbohydrates, crucial for rapid energy mobilization, remained stable at most sites, supporting immediate defenses such as detoxification and stress responses (Rothe et al., 2022). However, a significant decrease at site B suggested energy depletion under contamination stress, while increases at sites C and F pointed to possible enhanced storage for detoxification and oxidative stress management (Vellinger et al., 2013). Beyond carbohydrates dynamics, protein levels generally rose across sites, especially at site F, reflecting adaptive synthesis in response to contaminants (De Coen and Janssen, 2003). Elevated protein levels at sites A, C, and F likely supported detoxification and essential physiological functions, emphasizing proteins' role as backup energy sources during stress. The observed levels of carbohydrates and proteins could not be strictly correlated with the production of detoxifying enzymes and oxidative stress indicators. Despite this, similar metabolic shifts concomitant with oxidative stress under agricultural pollutant exposure have been observed in *Procambarus clarkii* (Fernández-Cisnal et al., 2018).

Such associations were also evident in the present study, as significantly increased levels of GST activity, a key enzymatic indicator of oxidative stress (especially against hydrophobic xenobiotics), were observed at sites A, B, E, and F (compared to the control, OS), reflecting active detoxification pathways (Gonçalves et al., 2021). This pattern may be linked to the properties of TPs, particularly those with high log Kow values. For example, chlorothalonil (log Kow 2.94) and flufenacet (log Kow 3.5) (Table S3; PPDB; Lewis et al., 2016) likely share hydrophobic characteristics with their TPs, such as metabolite R471811 and flufenacet-ESA, which were frequently detected in this study. However, specific data on the hydrophobicity of these TPs are currently unavailable. Complementary evidence of oxidative damage was provided by

TBARS levels, which remained significantly elevated at site C, whereas GST activity was comparable to that of, OS-exposed organisms (Fig. 4). This suggests that the detoxification capacity was exceeded without the induction of GST-based compensatory detoxification, which, importantly, is only one component of the enzymatic mechanisms involved in detoxification (e.g., catalase, etc.). These findings underscore the delicate balance *G. roeseli* must maintain to manage oxidative stress and detoxification demands under multi-contamination. Even low levels of contaminants can strain physiological processes, pushing organisms to prioritize survival mechanisms—potentially at the expense of other vital functions.

### 4.3. Differential responses driving site-specific differentiation

Integrating behavioral and biochemical (physiological) markers creates an effective ecotoxicological framework enabling robust assessment of nuanced organismal stress. This dual approach not only highlights survival and behavioral traits as key indicators of health but also differentiates site-specific impacts shaped by unique contamination profiles and environmental factors, reinforcing its value across diverse contaminant types and agroecosystems. In line with this integrative approach, our PCA results revealed complex interactions among biological and environmental parameters, identifying distinct patterns and biomarker clusters that differentiated site conditions. The biplot in Fig. 5A provides an overview of the biochemical, physiological, and environmental factors influencing the health, survival, and stress responses of *G. roeseli* across various LSWBs. The positioning of pesticides alongside proteins and carbohydrates in Dimension 1 suggests that contamination may have disrupted the management of metabolic reserves and energy allocation. Dimension 2 highlights the contributions of temperature and oxygen, which were key influencing factors in detoxification pathways and metabolic stress at different sites. While the PCA remains descriptive, the clustering of markers indicates compensatory mechanisms aimed at mitigating environmental stress. Sites with similar disturbances showed common physiological adaptations to moderate contamination levels, further underscoring the resilience of *G. roeseli* to environmental stress.

The clustering analysis identified 4 distinct response patterns, linking biological responses to environmental and contaminant profiles. Previous studies using the caging approach support these findings, effectively distinguishing natural conditions from anthropogenic impacts (Lacaze et al., 2011; Catteau et al., 2021; Cant et al., 2022; Georgieva et al., 2022). The obtained clusters illustrate the varying impacts of pesticide exposure: Cluster 1, containing highly contaminated sites (C, F, and G), showed elevated mortality, metabolic activity, AChE, and GST, and reduced behavioral activity (with hypoventilation showing that gammarids were close to death: see Vellinger et al., 2012), indicating neurotoxicity, oxidative stress, and high energy reallocation for maintenance. In contrast, cluster 4, which includes OS and site D (one observation), showed lower stress-marker values, reflecting stable physiological responses associated with reduced contaminant exposure. Clusters 2 (sites D and E) and 3 (sites A and B), meanwhile, showed more moderate stress conditions within the LSWBs, suggesting relatively intermediate health states. Cluster 2 showed reduced activity in metabolic and enzymatic markers, with hyperventilation suggesting compensatory mechanisms for respiration and/or osmoregulation alteration. In contrast, cluster 3 displayed a slight metabolic shift (decrease in carbohydrate levels and a slight increase in protein levels), suggesting energy depletion in response to slight environmental stress.

These results highlight the value of clustering analysis in revealing health variability across sites and the importance of integrating multiple biomarkers to capture nuanced organismal responses, but a good knowledge of biomarkers' functional significance is required. The 7-day exposure period may have been too short to capture all biological differences, as longer durations generally yield more comprehensive toxicological assessments (Böttger et al., 2012). Future research should
account for this to gain a deeper understanding of environmental impacts.

### 4.4. Integration with current trends in pesticide ecotoxicology

This study engages with several pressing topics in pesticide ecotoxicology, emphasizing the critical importance of TPs by highlighting their potential toxicity, which often exceeds that of their parent pesticides. This reinforces the importance of incorporating TPs into comprehensive risk assessment frameworks to better address their long-term ecological impacts (Löffler et al., 2024; Zahn et al., 2024). Additionally, we address the ecological impact of complex pesticide mixtures at environmental concentrations, suggesting that current assessments may underestimate the risks associated with frequent and combined exposures. This underscores the need to adapt assessments to reflect real-world conditions (Weisner et al., 2021). Furthermore, our findings inform the evolving regulatory landscape regarding the impacts of pesticides on non-target species, emphasizing the importance of empirical data in shaping effective policies. Incorporating a broader diversity of species is essential for achieving more comprehensive and ecologically relevant evaluations (Rosner et al., 2024). A recent study by Soose et al. (2024) strengthened this need, showing that native and invasive amphipod species exhibit differing behavioral responses to neonicotinoid exposure, underscoring the varied impacts pesticides can have across closely related species. In addition, by investigating understudied agroecosystems, this study highlights the need to consider small water bodies, which have been neglected despite their concerning chemical status (Kar et al., 2024; Messager et al., 2024). Overall, this research aligns with and enriches contemporary discussions on pesticide ecotoxicology, reinforcing the need for integrative approaches in environmental monitoring and sustainable pest management.

## 5. Conclusion

The contamination of lentic small water bodies (LSWBs) remains underexplored, particularly from a multi-site perspective. Our findings reveal significant variations in contamination levels linked to agricultural practices, consistent with trends observed in other regions, including European water bodies. This study highlights critical differences between minimally impacted and heavily anthropogenic environments, emphasizing the need to incorporate TPs in environmental monitoring. We demonstrated that contamination levels distinctly affect biomarkers in *G. roeseli*, supporting our hypothesis that these impacts vary with contamination extent. The observed effects underline the implications of complex contaminant mixtures in natural environments, where multiple stressors can interact to influence organismal health. By assessing and categorizing the health status of gammarids, we provide valuable insights into the ecotoxicological effects of pesticides. The transplantation approach used in this study could be adapted for other aquatic species, such as fish or bivalves, in LSWBs.

While this study provides valuable insights into the ecotoxicological impacts of pesticides in LSWBs, it is important to acknowledge its limitations. The absence of a pristine control site means that the results may reflect the cumulative effects of multiple stressors rather than the isolated impacts of pesticides. Nevertheless, the study highlights significant differences between sites with varying contamination levels, supporting the relevance of our approach. Future studies should incorporate more detailed temporal and spatial controls, as well as data on pesticide application, to further refine these findings. Beyond the responses in *G. roeseli*, pesticide contamination likely affects entire aquatic communities and key ecological functions. Such impacts may disrupt trophic interactions and ecosystem processes, with cascading effects on food webs. Future studies should thus include complementary species and functional endpoints to better assess community and ecosystem-level consequences in LSWBs. Future research should focus on extending exposure periods and examining areas with higher pesticide and TP

loads to enhance ecotoxicological risk assessments and deepen our understanding of LSWBs within the hydrographic network. Overall, this study elucidates the *in situ* impacts of TPs and highlights the need for further research, particularly in agriculturally influenced regions.

### CRediT authorship contribution statement

**Huguet-Cizo Marion:** Methodology, Formal analysis, Data curation.
**Pasquini Laure:** Methodology, Data curation.
**Banas Damien:** Writing – review & editing, Validation, Supervision, Resources, Project administration, Investigation, Funding acquisition, Data curation, Conceptualization.
**Milla Sylvain:** Writing – review & editing, Validation, Supervision.
**Cardoso Olivier:** Writing – review & editing, Validation, Project administration, Funding acquisition.
**Conseil Gaspard:** Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.
**Rosin Christophe:** Writing – review & editing, Validation, Methodology, Data curation.
**Felten Vincent:** Writing – review & editing, Validation, Methodology.

### Consent to participate

Not applicable

### Consent to publish

Not applicable

### Ethical approval

Not applicable

### Funding

This study was funded by the "Office Français de la Biodiversité (OFB)" and supported by the French Ministère de l'Enseignement Supérieur de la Recherche et de l'Innovation (MESRI).

### Declaration of Competing Interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Damien BANAS reports financial support was provided by Office Français de la Biodiversité (OFB). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

### Acknowledgements

The authors express their sincere gratitude to A. Iuretig (Université de Lorraine), A. L'Huillier, H. L'Huillier, G. Barthélemy, and T. Schmitt (fish farmers) for their invaluable collaboration. They also wish to acknowledge P. Jacques, M. Duval, and P. Hartmeyer for their significant contributions to the laboratory and field experiments. The authors are particularly grateful to J. Periz and C. Gentilhomme for their fruitful discussions, granting access to the ponds of the Domaine de Lindre, and providing access to rainfall data. Furthermore, the authors extend their thanks to L. Charrois and the Plateforme Expérimentale Phytotronique de Lorraine (PEPLor) for providing access to the climatic chamber.

## Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ecoenv.2025.118143.
# Data availability

Data will be made available on request.

## References

Akhtar, N., Syakir Ishak, M.I., Bhawani, S.A., Umar, K., 2021. Various Natural and Anthropogenic Factors Responsible for Water Quality Degradation: A Review. Water 13, 2660. https://doi.org/10.3390/w13192660.

Albanis, T.A., Hela, D.G., Sakellarides, T.M., Konstantinou, I.K., 1998. Monitoring of pesticide residues and their metabolites in surface and underground waters of Imatha (N. Greece) by means of solid-phase extraction disks and gas chromatography. J. Chromatogr. A 823, 59–71. https://doi.org/10.1016/S0021-9673(98)00304-5.

Anagnostopoulou, K., Nannou, C., Evgenidou, E., Lambropoulou, D., 2022. Overarching issues on relevant pesticide transformation products in the aquatic environment: A review. Sci. Total Environ. 815, 152863. https://doi.org/10.1016/j.scitotenv.2021.152863.

Andrei, J., Pain-Devin, S., Felten, V., Devin, S., Giambérini, L., Mehennaoui, K., Cambier, S., Gutleb, A.C., Guérdol, F., 2016. Silver nanoparticles impact the functional role of *Gammarus roeseli* (Crustacea Amphipoda). Environ. Pollut. 208, 608–618. https://doi.org/10.1016/j.envpol.2015.10.036.

Arce Funck, J., Danger, M., Gismondi, E., Cossu-Leguille, C., Guérdol, F., Felten, V., 2013. Behavioural and physiological responses of *Gammarus fossarum* (Crustacea Amphipoda) exposed to silver. Aquat. Toxicol. 142–143 73–84. https://doi.org/10.1016/j.aquatox.2013.07.012.

Arce-Funck, J., Crenier, C., Danger, M., Billoir, E., Usseglio-Polatera, P., Felten, V., 2018. High stoichiometric food quality increases moulting organism vulnerability to pollutant impacts: An experimental test with *Gammarus fossarum* (Crustacea: Amphipoda). Sci. Total Environ. 645, 1484–1495. https://doi.org/10.1016/j.scitotenv.2018.07.227.

Bahi, A., Sauvage, S., Payraudeau, S., Imfeld, G., Sánchez-Pérez, J.-M., Chaumet, B., Tournebize, J., 2023. Process formulations and controlling factors of pesticide dissipation in artificial plants: A critical review. Ecol. Eng. 186, 106820. https://doi.org/10.1016/j.ecoleng.2022.106820.

Baker, J.E., Fabrick, J.A., Zhu, K.Y., 1998. Characterization of esterases in malathion-resistant and susceptible strains of the pteromalid parasitoid *Anisoplosum calandrae*. Insect Biochem. Mol. Biol. 28, 1039–1050. https://doi.org/10.1016/S0965-1748(98)00095-2.

Bancel, S., Cachot, J., Bon, C., Rochard, É., Geffard, O., 2024. A critical review of pollution active biomonitoring using sentinel fish: challenges and opportunities. Environ. Pollut., 124661 https://doi.org/10.1016/j.envpol.2024.124661.

Baran, N., Surdyk, N., Auterives, C., 2021. Pesticides in groundwater at a national scale (France): Impact of regulations, molecular properties, uses, hydrogeology and climatic conditions. Sci. Total Environ. 791, 148137. https://doi.org/10.1016/j.scitotenv.2021.148137.

Beketov, M.A., Kefford, B.J., Shafer, R.B., Liess, M., 2013. Pesticides reduce regional biodiversity of stream invertebrates. Proc. Natl. Acad. Sci. 110, 11039–11043. https://doi.org/10.1073/pnas.1305618110.

Belfroid, A.C., van Drunen, M., Beek, M.A., Schrap, S.M., van Gestel, C.A.M., van Hattum, B., 1998. Relative risks of transformation products of pesticides for aquatic ecosystems. Sci. Total Environ. 222, 167–183. https://doi.org/10.1016/S0048-9697(98)00298-8.

Bighiu, M.A., Höss, S., Traunsprunguer, W., Kahlert, M., Goedkoop, W., 2020. Limited effects of pesticides on stream macroinvertebrates, biofilm nematodes, and algae in intensive agricultural landscapes in Sweden. Water Res. 174, 115640. https://doi.org/10.1016/j.watres.2020.115640.

Bish, M., Oseland, E., Bradley, K., 2021. Off-target pesticide movement: a review of our current understanding of drift due to inversions and secondary movement. Weed Technol. 35, 345–356. https://doi.org/10.1017/wet.2020.138.

Bötter, R., Schaller, J., Mohr, S., 2012. Closer to reality — the influence of toxicity test modifications on the sensitivity of *Gammarus roeseli* to the insecticide imidacloprid. Ecotoxicol. Environ. Saf. 81, 49–54. https://doi.org/10.1016/j.ecoenv.2012.04.015.

Brodeur, J.C., Poletta, G.L., Simoniello, M.F., Carriquiriborde, P., Cristos, D.S., Pautasso, N., Paravani, E., Poliserpi, M.B., D'Andrea, M.F., Gonzalez, P.V., Aca, V.L., Curto, A.E., 2021. The problem with implementing fish farms in agricultural regions: A trial in a pampean pond highlights potential risks to both human and fish health. Chemosphere 262, 128408. https://doi.org/10.1016/j.chemosphere.2020.128408.

Comejo, G., Wallin, B., Enojárví, M., 1998. Analysis of oxidation and antioxidants using microtiter plates. Methods Mol. Biol. 108, 377–387. https://doi.org/10.1385/0-89603-472-0-377.

Cant, A., Bonnard, M., Porcher, J.-M., Prygiel, J., Catteau, A., Delahaut, L., Palluel, O., Turiés, C., Geffard, A., Bado-Nilles, A., 2022. Integration of Genotoxic Biomarkers in Environmental Biomonitoring Analysis Using a Multi-Biomarker Approach in Three- Spined Stickleback (*Gasterosteus aculeatus* Linnaeus, 1758). Toxics 10, 101. https://doi.org/10.3390/toxics10030101.

Capparelli, M.V., Ponce-Vélez, G., Dzul-Caamal, R., Rodriguez-Cab, E.M., Cabrera, M., Lucas-Solis, O., Moulatlet, G.M., 2023. Multi-level responses of oysters *Crassostrea virginica* for assessing organochlorine pesticides in a Ramsar coastal lagoon in southern Mexico. Chemosphere 320, 138064. https://doi.org/10.1016/j.chemosphere.2023.138064.

Catteau, A., Bado-Nilles, A., Beaudouin, R., Tebby, C., Joachim, S., Palluel, O., Turiés, C., Chrétien, N., Nott, K., Ronkart, S., Geffard, A., Porcher, J.-M., 2021. Water quality of the Meuse watershed: Assessment using a multi-biomarker approach with caged

three-spined stickleback (*Gasterosteus aculeatus* L.). Ecotoxicol. Environ. Saf. 208, 111407. https://doi.org/10.1016/j.ecoenv.2020.111407.

Charron, L., Geffard, O., Chaumot, A., Coulaud, R., Queau, H., Geffard, A., Dedourge-Geffard, O., 2013. Effect of water quality and confounding factors on digestive enzyme activities in *Gammarus fossarum*. Environ. Sci. Pollut. Res 20, 9044–9056. https://doi.org/10.1007/s11356-013-1921-5.

Chaumot, A., Geffard, O., Armengaud, J., Maltby, L., 2015. Chapter 11 - Gammarids as Reference Species for Freshwater Monitoring, in: In: Amiard-Triquet, C., Amiard, J.-C., Mouneyrac, C. (Eds.), Aquatic Ecotoxicology: Academic Press, pp. 253–280. https://doi.org/10.1016/B978-0-12-800949-9.9.0011-5.

Chiaia-Hernandez, A.C., Keller, A., Wächter, D., Steinlin, C., Camenzuli, L., Hollender, J., Krauss, M., 2017. Long-Term Persistence of Pesticides and TPs in Archived Agricultural Soil Samples and Comparison with Pesticide Application. Environ. Sci. Technol. 51, 10642–10651. https://doi.org/10.1021/acs.est.7b02529.

Conseil, G., Milla, S., Cardoso, O., Pasquini, L., Rosin, C., Banas, D., 2024. Occurrence, dispersal, and associated environmental risk assessment of pesticides and their transformation products in small water bodies of Northeastern France. Environ. Sci. Pollut. Res. 31, 66643–66666.

Coulaud, R., Geffard, O., Xuereb, B., Lacaze, E., Quéau, H., Garric, J., Charles, S., Chaumot, A., 2011. In situ feeding assay with *Gammarus pulex* (Crustacea: Amphipoda). Water Res. 45, 6417–6429. https://doi.org/10.1016/j.watres.2011.09.035.

Dabrowski, J., Peall, S., Vanniekierk, A., Reinecke, A., Day, J., Schulz, R., 2002. Predicting runoff-induced pesticide input in agricultural sub-catchment surface waters: linking catchment variables and contamination. Water Res. 36, 4975–4984. https://doi.org/10.1016/S0043-1354(02)00234-8.

Damasceno, J.M., Rato, L.D., Simões, T., Morão, I.F.C., Meireles, G., Novais, S.C., Lemos, M.F.L., 2021. Exposure to the Insecticide Sulfoxaflor Affects Behaviour and Biomarkers Responses of *Carcinus maenas* (Crustacea: Decapoda). Biology 10, 1234. https://doi.org/10.3390/biology10121234.

De Coen, W.M., Janssen, C.R., 2003. The missing biomarker link: Relationships between effects on the cellular energy allocation biomarker of toxicant-stressed *Daphnia magna* and corresponding population characteristics. Enviro Toxic. Chem. 22, 1632–1641. https://doi.org/10.1002/etc.5620220727.

De Lange, H.J., Noordoven, W., Murk, A.J., Lürling, M., Peeters, E.T.H.M., 2006. Behavioural responses of *Gammarus pulex* (Crustacea, Amphipoda) to low concentrations of pharmaceuticals. Aquat. Toxicol. 78, 209–216. https://doi.org/10.1016/j.aquatox.2006.03.002.

Dedourge-Geffard, O., Charron, L., Hofbauer, C., Gaillet, V., Palais, F., Lacaze, E., Geffard, A., Geffard, O., 2013. Temporal patterns of digestive enzyme activities and feeding rate in gammadarids (*Gammarus fossarum*) exposed to inland polluted waters. Ecotoxicol. Environ. Saf. 97, 139–146. https://doi.org/10.1016/j.ecoenv.2013.07.016.

Di Nica, V., González, A.B.M., Lencioni, V., Villa, S., 2020. Behavioural and biochemical alterations by chlorpyrifos in aquatic insects: an emerging environmental concern for pristine Alpine habitats. Environ. Sci. Pollut. Res 27, 30918–30926. https://doi.org/10.1007/s11356-019-06467-2.

Dick, J.T.A., 1995. The cannibalistic behaviour of two *Gammarus* species (Crustacea: Amphipoda). J. Zool. 236, 697–706. https://doi.org/10.1111/j.1469-7998.1995.tb02740.x.

Domingues, I., Agra, A.R., Monaghan, K., Soares, A.M.V.M., Nogueira, A.J.A., 2010. Cholinesterase and glutathione-S-transferase activities in freshwater invertebrates as biomarkers to assess pesticide contamination. Environ. Toxicol. Chem. 29, 5–18. https://doi.org/10.1002/etc.23.

DuBois, Michel, Gilles, K.A., Hamilton, J.K., Rebers, P.A., Smith, Fred, 1956. Colorimetric Method for Determination of Sugars and Related Substances. Anal. Chem. 28, 350–356. https://doi.org/10.1021/ac60111a017.

Ellman, G.L., Courtney, K.D., Andres, V., Featherstone, R.M., 1961. A new and rapid colorimetric determination of acetylcholinesterase activity. Biochem. Pharmacol. 7, 88–95. https://doi.org/10.1016/0006-2952(61)90145-9.

Felten, V., Charmantier, G., Charmantier-Daures, M., Aujoulat, F., Garric, J., Geffard, O., 2008. Physiological and behavioural responses of *Gammarus pulex* exposed to acid stress. Comp. Biochem. Physiol. Part C: Toxicol. Pharmacol. 147, 189–197. https://doi.org/10.1016/j.cbpc.2007.09.006.

Feng, X., Liu, Z., Vo Duy, S., Munoz, G., Parent, L., Sauvé, S., 2024. Pesticides and transformation products in surface waters of western Montérégie, Canada: occurrence, spatial distribution and ecotoxicological risks. 10.1039.D3VA00231D Environ. Sci.: Adv. https://doi.org/10.1039/D3VA00231D.

Fenner, K., Canonica, S., Wackett, L.P., Elsner, M., 2013. Evaluating Pesticide Degradation in the Environment: Blind Spots and Emerging Opportunities. Science 341, 752–758. https://doi.org/10.1126/science.1236281.

Fernández-Cisnal, R., García-Sevillano, M.A., García-Barrera, T., Gómez-Ariza, J.L., Abril, N., 2018. Metabolomic alterations and oxidative stress are associated with environmental pollution in Procambarus clarkii. Aquat. Toxicol. 205, 76–88. https://doi.org/10.1016/j.aquatox.2018.10.005.

Fisher, I.J., Phillips, P.J., Bayraktar, B.N., Chen, S., McCarthy, B.A., Sandstrom, M.W., 2021. Pesticides and their degradates in groundwater reflect past use and current management strategies, Long Island, New York, USA. Science Total Environ. 752, 141895. https://doi.org/10.1016/j.scitotenv.2020.141895.

Flammarion, P., Noury, P., Garric, J., 2002. The measurement of cholinesterase activities as a biomarker in chub (Leuciscus cephalus): the fish length should not be ignored. Barking Essex 1987 Environ. Pollut. 120, 325–330. https://doi.org/10.1016/s0269-7491(02)00137-9.

Farrow, D.M., Maltby, L., 2000. Toward a mechanistic understanding of contaminant-induced changes in detritus processing in streams: Direct and indirect effects on
detritivore feeding. *Environ. Toxicol. Chem.* 19, 2100–2106. https://doi.org/10.1002/etc.5620190820.

Gagnaire, B., Geffard, O., Xuereb, B., Margoum, C., Garric, J., 2008. Cholinesterase activities as potential biomarkers: Characterization in two freshwater snails, *Potamopyrgus antipodarum* (Mollusca, Mollusobiidae, in Smith 1889) and *Valvata piscinalis* (Mollusca, Valvatidae, Müller 1774). *Chemosphere* 71, 553–560. https://doi.org/10.1016/j.chemosphere.2007.09.048.

Gaillard, J., 2014. Rôle des étangs de barrage à vocation piscicole dans la dynamique des micropolluants en têtes de bassins versants. *Sci. Agric. Univ. é D. Lorraineis. FFNT*, 2014LORR0333ff. ffftel-01751570.

Gaillard, J., Thomas, M., Iuretig, A., Pallez, C., Feidt, C., Dauchy, X., Banas, D., 2016. Barrage fishponds: Reduction of pesticide concentration peaks and associated risk of adverse ecological effects in headwater streams. *J. Environ. Manag.* 169, 261–271. https://doi.org/10.1016/j.jenvman.2015.12.035.

Garaud, M., Trapp, J., Devin, S., Cossu-Leguille, C., Pain-Devin, S., Felten, V., Giamberini, L., 2015. Multi biomarker assessment of cerium dioxide nanoparticle (nCeO2) sublethal effects on two freshwater invertebrates, *Dreissena polymorpha* and *Gammarus roeseli*. *Aquatol. Toxicol.* 158, 63–74. https://doi.org/10.1016/j.aquatox.2014.11.004.

Gaullier, C., Baran, N., Dousset, S., Devau, N., Billet, D., Kitzinger, G., Coisy, E., 2019. Wetland hydrodynamics and mitigation of pesticides and their metabolites at pilot-scale. *Ecol. Ecol.* 136, 185–192. https://doi.org/10.1016/j.ecoleng.2019.06.019.

Gauthier, M., Defrance, J., Jumarie, C., Vulliet, E., Garric, J., Boily, M., Geffard, O., 2023. Disruption of oogenesis and molting by methoprene and glyphosate in *Gammarus fossarum*: involvement of retinoic acid? *Environ. Sci. Pollut. Res.* 30, 86060–86071. https://doi.org/10.1007/s11356-023-28327-w.

Georgieva, E., Antal, L., Stoyanova, S., Arnaudova, D., Velcheva, I., Iliev, I., Vasileva, T., Bivolarski, V., Mitkovska, V., Chassovnikarova, T., Todorova, B., Uzochukwu, I.E., Nyeste, K., Yancheva, V., 2022. Biomarkers for pollution in caged mussels from three reservoirs in Bulgaria: A pilot study. *Heliyon* 8, e09069. https://doi.org/10.1016/j.heliyon.2022.e09069.

Gewurtz, S.B., Backus, S.M., Bhavsar, S.P., McGoldrick, D.J., de Solla, S.R., Murphy, E. W., 2011. Contaminant biomonitoring programs in the Great Lakes region: Review of approaches and critical factors. *Environ. Rev.* 19, 162–184. https://doi.org/10.1139/a11-005.

Gismondi, E., Beisel, J.-N., Cossu-Leguille, C., 2012. Influence of gender and season on reduced glutathione concentration and energy reserves of *Gammarus roeseli*. *Environ. Res.* 118, 47–52. https://doi.org/10.1016/j.envres.2012.06.004.

Gonçalves, A.M.M., Rocha, C.P., Marques, J.C., Gonçalves, F.J.M., 2021. Enzymes as useful biomarkers to assess the response of freshwater communities to pesticide exposure – A review. *Ecol. Indic.* 122, 107303. https://doi.org/10.1016/j.ecolind.2020.107303.

Grabner, D., Rothe, L.E., Sures, B., 2023. Parasites and Pollutants: Effects of Multiple Stressors on Aquatic Organisms. *Enviro Toxic. Chem.* 42, 1946–1959. https://doi.org/10.1002/etc.5689.

Henry, K.S., Danielopol, D.L., 1998. Oxygen dependent habitat selection in surface and hyporheic environments by *Gammarus roeseli* Gervais (Crustacea, Amphipoda): experimental evidence. *Hydrobiologia* 390, 51–60. https://doi.org/10.1023/A:1003541300460.

Hernández, F., Ibáñez, M., Pozo, O.J., Sancho, J.V., 2008. Investigating the presence of pesticide transformation products in water by using liquid chromatography-mass spectrometry with different mass analyzers. *J. Mass Spectrom.* 43, 173–184. https://doi.org/10.1002/jms.1279.

Hervant, F., Mathieu, J., Messana, G., 1997. Motomotory, ventilatory and metabolic responses of the subterranean *Stenaeusellus virei* (Crustacea, Isopoda) to severe hypoxia and subsequent recovery. *Comptes Rendus De l'Acad. émie Des. Sci. - Ser. III - Sci. de la Vie* 320, 139–148. https://doi.org/10.1016/S0764-4469(97)85005-6.

Hijosa-Valsero, M., Béces, E., Fernández-Áldez, C., Fernández-Áldez, M., Mayo, R., Jiménez, J.J., 2016. Chemical pollution in inland shallow lakes in the Mediterranean region (NW Spain): PAHs, insecticides and herbicides in water and sediments. *Sci. Total Environ.* 544, 797–810. https://doi.org/10.1016/j.scitotenv.2015.11.160.

Hintze, S., Cochand, F., Glauser, G., Hunkeler, D., 2024. Soil and unsaturated zone as a long-term source for pesticide metabolites in groundwater. *Water Res* 261, 121901. https://doi.org/10.1016/j.watres.2024.121901.

Hu, C., Tao, Y., 2023. Spatial-temporal occurrence and sources of organochlorine pesticides in the sediments of the largest deep lake (Lake Fuxian) in China. *Environ. Sci. Pollut. Res.* 30, 31157–31170. https://doi.org/10.1007/s11356-022-24394-7.

Hvězdová, M., Kosubová, P., Košíková, M., Scherr, K.E., Šínek, Z., Brodský, L., Sudoma, M., Skulová, L., Sánka, M., Svobodová, L., Krkošková, L., Vašičková, N., Neuwirthová, N., Bielská, L., Hofman, J., 2018. Currently and recently used pesticides in Central European arable soils. *Sci. Total Environ.* 613–614 361–370. https://doi.org/10.1016/j.scitotenv.2017.09.049.

Jáždzewski, K., 1980. Range extensions of some Gammaridean species in European inland waters caused by human activity. *Crustac. B*, 6, 84–107. (http://www.jstor.org/stable/25027516).

Ji, C., Song, Q., Chen, Y., Zhou, Z., Wang, P., Liu, J., Sun, Z., Zhao, M., 2020. The potential endocrine disruption of pesticide transformation products (TPs): The blind spot of pesticide risk assessment. *Environ. Int.* 137, 105490. https://doi.org/10.1016/j.envint.2020.105490.

Kar, A., Deole, S., Nayak, R.R., Gupta, A.K., Gadratagi, B.G., Patil, N., Guru-Pirasanna-Pandi, G., Mahapatra, B., Mahantay, A., Adak, T., 2024. Distribution and risk assessment of pesticide pollution in small streams adjoining paddy fields. *J. Hazard. Mater.* 469, 133852. https://doi.org/10.1016/j.jhazmat.2024.133852.

Karaman, G.S., Pinkster, S., 1977. Freshwater *Gammarus* species from Europe, North Africa and adjacent regions of Asia (Crustacea-Amphipoda). Part II. *Gammarus roeseli*-group and related species. Bijdr. Tot Dierkld. 47, 165–196.

Kiefer, K., Müller, A., Singer, H., Hollender, J., 2019. New relevant pesticide transformation products in groundwater detected using target and suspect screening for agricultural and urban micropollutants with LC-HRMS. Water Res. 165, 114972. https://doi.org/10.1016/j.watres.2019.114972.

Kinzler, W., Kley, A., Mayer, G., Waloszek, D., Maier, G., 2009. Mutual predation between and cannibalism within several freshwater gammarids: *Dikerogammarus villosum* versus one native and three invasives. *Aquat. Ecol.* 43, 457–464. https://doi.org/10.1007/s10452-008-9206-7.

Knorr, D.Y., Demirbas, D., Heinrich, R., 2023. Multifaceted promotion of apoptosis by acetylcholinesterase. *Front. Cell Death 2*. https://doi.org/10.3389/fceld.2023.1169966.

Köhler, H.-R., Triebskorn, R., 2013. Wildlife Ecotoxicology of Pesticides: Can We Track Effects to the Population Level and Beyond? *Science* 341, 759–765. https://doi.org/10.1126/science.1237591.

Kinz, P., Kienle, C., Gerhardt, A., 2010. *Gammarus* spp. in Aquatic Ecotoxicology and Water Quality Assessment: Toward Integrated Multilevel Tests. *Rev. Environ. Contam. Toxicol.* 205, 1–76. https://doi.org/10.1007/978-1-4419-5623-1_1.

Lacaze, E., Devaux, A., Mons, R., Bony, S., Garric, J., Geffard, A., Geffard, O., 2011. DNA damage in caged *Gammarus fossarum* amphipods: A tool for freshwater genotoxicity assessment. *Environ. Pollut.* 159, 1682–1691. https://doi.org/10.1016/j.envpol.2011.02.038.

Le Cor, F., Slaby, S., Dufour, V., Iuretig, A., Feidt, C., Dauchy, X., Banas, D., 2021. Occurrence of pesticides and their transformation products in headwater streams: Contamination status and effect of ponds on contaminant concentrations. *Sci. Total Environ.* 788, 147715. https://doi.org/10.1016/j.scitotenv.2021.147715.

Lebrun, J.D., De Jesus, K., Rouillac, L., Ravelli, M., Guenne, A., Tournebize, J., 2020. Single and combined effects of insecticides on multi-level biomarkers in the non-target amphipod *Gammarus fossarum* exposed to environmentally realistic levels. *Aquat. Toxicol.* 218, 105357. https://doi.org/10.1016/j.aquatox.2019.105357.

Lebrun, J.D., Gismondi, E., 2020. Behavioural and biochemical alterations in gammarids as induced by chronic metallic exposures (Cd, Cu and Pb): Implications for freshwater biomonitoring. *Chemosphere* 257, 127253. https://doi.org/10.1016/j.chemosphere.2020.127253.

Legradi, J.B., Di Paolo, C., Kraak, M.H.S., Van Der Geest, H.G., Schymanski, E.L., Williams, A.J., Dingemans, M.M.L., Massei, R., Brack, W., Cousin, M., Begout, M.-L., Van Der Oost, R., Carion, A., Suarez-Ulloa, V., Silvestre, F., Escher, B.I., Engwall, M., Nilén, G., Keiter, S.H., Pollet, D., Waldmann, P., Kienle, C., Werner, I., Haigis, A.-C., Knapen, D., Vergauwen, L., Spehr, M., Schulz, W., Busch, W., Leuthold, D., Scholz, S., Vom Berg, C.M., Basu, N., Murphy, C.A., Lampert, J., Kuckelkorn, J., Grumm, T., Hollert, H., 2018. An ecotoxicological view on neurotoxicity assessment. *Environ. Sci. Eur.* 30, 46. https://doi.org/10.1186/s12302-018-0173-x.

Lewis, K.A., Tzilivakis, J., Warner, D.J., Green, A., 2016. An international database for pesticide risk assessments and management. *Hum. Ecol. Risk Assess.: Int. J.* 22, 1050–1064. https://doi.org/10.1080/10807039.2015.1133242.

Li, Q., Wang, M., Duan, L., Qiu, Y., Ma, T., Chen, L., Breitholtz, M., Bergman, Å., Zhao, J., Hecker, M., Wu, L., 2018. Multiple biomarker responses in caged benthic gastropods *Bellamya aeruginosa* after in situ exposure to Taihu Lake in China. *Environ. Sci. Eur.* 30, 34. https://doi.org/10.1186/s12302-018-0164-y.

Liebmann, L., Schreiner, V.C., Vormeyer, P., Weisner, O., Liess, M., 2024. Combined effects of herbicides and insecticides reduce biomass of sensitive aquatic invertebrates. *Sci. Total Environ.* 946, 174343. https://doi.org/10.1016/j.scitotenv.2024.174343.

Link, S., Schreiner, V.C., Graf, N., Szöcs, E., Bundschuh, M., Battes, K.P., Cîmpean, M., Sures, B., Grabner, D., Buse, J., Schäfer, R.B., 2022. Pesticide effects on macroinvertebrates and leaf litter decomposition in areas with traditional agriculture. *Sci. Total Environ.* 828, 154549. https://doi.org/10.1016/j.scitotenv.2022.154549.

Ljungquist, A., Augustinsson, K.-B., 1971. Purification and Properties of Two Carboxylesterases from Rat-Liver Microsomes. *Eur. J. Biochem* 23, 303–313. https://doi.org/10.1111/j.1432-1033.1971.tb01622.x.

Löffler, P., Lai, A., Henschel, H., Spilsbury, F., Deviller, G., Tarazona, J.V., Lai, F.Y., 2024. Enhanced Risk Assessment of Transformation Products through Chemical Similarity Analysis. ACS EST Water 4, 1949–1951. https://doi.org/10.1021/acsestwater.4c00204.

Lomartire, S., Marques, J.C., Gonçalves, A.M.M., 2021. Biomarkers based tools to assess environmental and chemical stressors in aquatic systems. *Ecol. Indic.* 122, 107207.

Lorenz, S., Rasmussen, J.J., Süß, A., Kalettka, T., Golla, B., Horney, P., Stähler, M., Hommel, B., Schäfer, R.B., 2017. Specifics and challenges of assessing exposure and effects of pesticides in small water bodies. *Hydrobiologia* 793, 213–224. https://doi.org/10.1007/s10750-016-2973-6.

Ma, Y., Xu, T., Mao, Q., Zhou, X., Wang, R., Sun, J., Zhang, A., Zhou, S., 2021. Distribution and flux of organochlorine pesticides in sediment from Prydz Bay, Antarctic: Implication of sources and trends. *Sci. Total Environ.* 799, 149380. https://doi.org/10.1016/j.scitotenv.2021.149380.

MacNeil, C., Elwood, R.W., Dick, J.T.A., 2000. Factors influencing the importance of *Gammarus* spp. (Crustacea: Amphipoda) in riverine salmonid diets. *Fundam. Appl. Limnol.* 149, 87–107. https://doi.org/10.1127/archiv-hydrobiol/149/2000/87.

Mahler, B.J., Nowell, L.H., Sandstrom, M.W., Bradley, P.M., Romanok, K.M., Konrad, C. P., Van Metre, P.C., 2021. Inclusion of Pesticide Transformation Products Is Key to Estimating Pesticide Exposures and Effects in Small U.S. Streams. *Environ. Sci. Technol.* 55, 4740–4752. https://doi.org/10.1021/acs.est.0c06625.

Masuko, T., Minami, A., Iwasaki, N., Majima, T., Nishimura, S.-I., Lee, Y.C., 2005. Carbohydrate analysis by a phenol-sulfuric acid method in microplate format. *Anal. Biochem.* 339, 69–72. https://doi.org/10.1016/j.ab.2004.12.001.
Matthies, M., Klasmeier, J., Beyer, A., Ehling, C., 2009. Assessing Persistence and Long-Range Transport Potential of Current-Use Pesticides. Environ. Sci. Technol. 43, 9223-9229. https://doi.org/10.1021/es900773u.

Menger, F., Boström, G., Jonsson, O., Ahrens, L., Wiberg, K., Kreuger, J., Gago-Ferrero, P., 2021. Identification of Pesticide Transformation Products in Surface Water Using Suspect Screening Combined with National Monitoring Data. Environ. Sci. Technol. 55, 10343-10353. https://doi.org/10.1021/acs.est.1c00466.

Messager, M.L., Pella, H., Datry, T., 2024. Inconsistent Regulatory Mapping Quietly Threatens Rivers and Streams. Environ. Sci. Technol. https://doi.org/10.1021/acs.est.4c01859.

Milinkovitch, T., Geffard, O., Geffard, A., Mouneyrac, C., Chaumot, A., Xuereb, B., Fisson, C., Minier, C., Auffret, M., Perceval, O., Egea, E., Sanchez, W., 2019. Biomarkers as tools for monitoring within the Water Framework Directive context: concept, opinions and advancement of expertise. Environ. Sci. Pollut. Res 26, 32759-32763. https://doi.org/10.1007/s11356-019-06434-x.

Mottier, A., Kientz-Bouchart, V., Dubreule, C., Serpentini, A., Lebel, J.M., Costil, K., 2014. Effects of acute exposures to necoprop, necoprop-p and their biodegradation product (2-MCP) on the larval stages of the Pacific oyster, *Crassostrea gigas*. Aquat. Toxicol. 146, 165-175. https://doi.org/10.1016/j.aquatox.2013.11.008.

Ng, C.A., Scheringer, M., Fenner, K., Hungerbuhler, K., 2011. A Framework for Evaluating the Contribution of Transformation Products to Chemical Persistence in the Environment. Environ. Sci. Technol. 45, 111-117. https://doi.org/10.1021/es1010237.

Nørum, U., Frederiksen, M.A.T., Bjerregaard, P., 2011. Locomotory behaviour in the freshwater amphipod *Gammarus pulex* exposed to the pyrethroid cypermethrin. Chem. Ecol. 27, 569-577. https://doi.org/10.1080/02757540.2011.596831.

Nyman, A.-M., Hintermeister, A., Schirmer, K., Ashauer, R., 2013. The Insecticide Imidacloprid Causes Mortality of the Freshwater Amphipod *Gammarus pulex* by Interfering with Feeding Behavior. PLoS ONE 8, e62472. https://doi.org/10.1371/journal.pone.0062472.

Ohkawa, H., Ohishi, N., Yagi, K., 1978. Reaction of linoleic acid hydroperoxide with thiobarbituric acid. J. Lipid Res 19, 1053-1057.

Osano, O., Admiraal, W., Klamer, H.J.C., Pastor, D., Bleeker, E.A.J., 2002. Comparative toxic and genotoxic effects of chloroacetanilides, formamidines and their degradation products on *Vibrio fischeri* and *Chironomus riparius*. Environ. Pollut. 119, 195-202. https://doi.org/10.1016/S0269-7491(01)00334-7.

Palma, P., Ledo, L., Alvarenga, P., 2016. Ecotoxicological endpoints, are they useful tools to support ecological status assessment in strongly modified water bodies? Sci. Total Environ. 541, 119-129. https://doi.org/10.1016/j.scitotenv.2015.09.014.

Pasquini, L., Lardy-Fontan, S., Rosin, C., 2025. Pesticide transformation products: a potential new source of interest for drinking water. Environ. Sci. Pollut. Res. 32, 4619-4635. https://doi.org/10.1007/s11356-025-35979-3.

Pöckl, M., Humpesch, U.H., 1990. Intra- and inter-specific variations in egg survival and brood development time for Austrian populations of *Gammarus fossarum* and *G. roeseli* (Crustacea: Amphipoda). Freshw. Biol. 23, 441-455. https://doi.org/10.1111/j.1365-2427.1990.tb00286.x.

Pöckl, M., Webb, B.W., Sutcliffe, D.W., 2003. Life history and reproductive capacity of *Gammarus fossarum* and *G. roeseli* (Crustacea: Amphipoda) under naturally fluctuating water temperatures: a simulation study: Natural thermal regimes and reproductive capacity of Gammarus spp. Freshw. Biol. 48, 53-66. https://doi.org/10.1046/j.1365-2427.2003.00967.x.

Raudonyté-Svirbutavičienė, E., Joksas, K., Stakėnienė, R., Rybakovas, A., Nalivaikienė, R., Visišinskienė, G., Arbačiauskas, K., 2023. Pollution patterns and their effects on biota within lotic and lentic freshwater ecosystems: How well contamination and response indicators correspond? Environ. Pollut. 335, 122294. https://doi.org/10.1016/j.envpol.2023.122294.

Riascos-Flores, L., Bruneel, S., Van Der Heyden, C., Deknock, A., Van Echelpoel, W., Forio, M.A.E., De Saeyer, N., Vanden Berghe, W., Spanoghe, P., Bermudez, R., Dominguez-Granda, L., Goethals, P., 2021. Polluted paradise: Occurrence of pesticide residues within the urban coastal zones of Santa Cruz and Isabela (Galapagos, Ecuador). Sci. Total Environ. 763, 142956. https://doi.org/10.1016/j.scitotenv.2020.142956.

Riedo, J., Wettstein, F.E., Rösch, A., Herzog, C., Banerjee, S., Büchi, L., Charles, R., Wächter, D., Martin-Laurent, F., Bucheli, T.D., Walder, F., Van Der Heijden, M.G.A., 2021. Widespread Occurrence of Pesticides in Organically Managed Agricultural Soils—the Ghost of a Conventional Agricultural Past? Environ. Sci. Technol. 55, 2919-2928. https://doi.org/10.1021/acs.est.0c06405.

Rocco, K., Margoum, R., Richard, L., Coquery, M., 2022. Enhanced database creation with in silico workflows for suspect screening of unknown tebuconazole transformation products in environmental samples by UHPLC-HRMS. J. Hazard. Mater. 440, 129706. https://doi.org/10.1016/j.jhazmat.2022.129706.

Rodrigues, P., Oliva-Teles, L., Guimarães, L., Carvalho, A.P., 2022. Occurrence of Pharmaceutical and Pesticide Transformation Products in Freshwater: Update on Environmental Levels, Toxicological Information and Future Challenges. Rev. Env. Contam. (formerly:Residue Rev. 260, 14. https://doi.org/10.1007/s44169-022-00014-w.

Romani, R., Antognelli, C., Baldracchini, F., De Santis, A., Isani, G., Giovannini, E., Rosi, G., 2003. Increased acetylcholinesterase activities in specimens of *Sparus auratus* exposed to sublethal copper concentrations. Chem. Interact. 145, 321-329. https://doi.org/10.1016/S0009-2797(03)00058-9.

Romani, R., Isani, G., De Santis, A., Giovannini, E., Rosi, G., 2005. Effects of chlorpyrifos on the catalytic efficiency and expression level of acetylcholinesterases in the bivalve mollusk Scapharca inaequivalis. Environ. Toxicol. Chem. 24, 2879-2886. https://doi.org/10.1897/04-555R3.1.

Rosner, A., Ballarin, L., Barnay-Verdier, S., Borisenko, I., Drago, L., Drobne, D., Concetta Eliso, M., Harbuzov, Z., Grimaldi, A., Guy-Haim, T., Karahan, A., Lynch, I., Giulia

Lionetto, M., Martinez, P., Mehennaoui, K., Oruc Ozcan, E., Pinsino, A., Paz, G., Rinkevich, B., Spagnuolo, A., Sugni, M., Cambier, S., 2024. A broad-taxa approach as an important concept in ecotoxicological studies and pollution monitoring. Biol. Rev. 99, 131-176. https://doi.org/10.1111/brv.13015.

Rothe, L.E., Loeffler, F., Gerhardt, A., Feld, C.K., Stift, R., Weyand, M., Grabner, D., Sures, B., 2022. Parasite infection influences the biomarker response and locomotor activity of *Gammarus fossarum* exposed to conventionally-treated wastewater. Ecotoxicol. Environ. Saf. 236, 113474. https://doi.org/10.1016/j.ecoenv.2022.113474.

Rousis, N.I., Bade, R., Bijlsma, L., Zuccato, E., Sancho, J.V., Hernandez, F., Castiglioni, S., 2017. Monitoring a large number of pesticides and transformation products in water samples from Spain and Italy. Environ. Res. 156, 31-38. https://doi.org/10.1016/j.envres.2017.03.013.

Rumschlag, S.L., Mahon, M.B., Hoverman, J.T., Raffel, T.R., Carrick, H.J., Hudson, P.J., Rohr, J.R., 2020. Consistent effects of pesticides on community structure and ecosystem function in freshwater systems. Nat. Commun. 11, 6333. https://doi.org/10.1038/s41467-020-20192-2.

Schreiner, V.C., Link, M., Kunz, S., Szöcs, E., Scharmüller, A., Vogler, B., Beck, B., Busses, K.P., Cimpean, M., Singer, H.P., Hollender, J., Schäfer, R.B., 2021. Paradise lost? Pollution control in a European region with considerable amount of traditional agriculture. Water Res. 188, 116528. https://doi.org/10.1016/j.watres.2020.116528.

Schuij, L.M., Peng, F.-J., Van Den Berg, S.J.P., Dingemans, M.M.L., Van Den Brink, P.J., 2021. Eco)toxicological tests for assessing impacts of chemical stress to aquatic ecosystems: Facts, challenges, and future. Sci. Total Environ. 795, 148776. https://doi.org/10.1016/j.scitotenv.2021.148776.

Slaby, S., Catteau, A., Le Cor, F., Cant, A., Dufour, V., Iurétig, A., Turiés, C., Palluel, O., Bado-Nilles, A., Bonnard, M., Cardoso, O., Dauchy, X., Porcher, J.-M., Banas, D., 2023. Chemical occurrence of pesticides and transformation products in two small lentic waterbodies at the head of agricultural watersheds and biological responses in caged *Gasterosteus aculeatus*. Sci. Total Environ., 166326 https://doi.org/10.1016/j.scitotenv.2023.166326.

Slaby, S., Geffard, A., Fisson, C., Bonnevalle-Normand, M., Allonier-Fernandes, A.-S., Amara, R., Bado-Nilles, A., Bonnard, I., Bonnard, M., Burlion-Giorgi, M., Cant, A., Catteau, A., Chaumot, A., Costil, K., Coulaud, R., Delahaut, L., Diop, M., Duflot, A., Geffard, O., Jestin, A., Le Foll, F., Le Guernic, A., Lopes, C., Palos-Ladeiro, M., Peignot, Q., Poret, A., Serpentini, A., Tremolet, G., Turiés, C., Xuereb, R., 2024. Advancing environmental monitoring across the water continuum combining biomarker analysis in multiple sentinel species: A case study in the Seine-Normandie Basin (France). J. Environ. Manag. 358, 120784. https://doi.org/10.1016/j.jenvman.2024.120784.

Slaby, S., Le Cor, F., Dufour, V., Auger, L., Pasquini, L., Cardoso, O., Curtet, L., Baudoin, J.-M., Wiest, L., Vulliet, E., Feidt, C., Dauchy, X., Banas, D., 2022. Distribution of pesticides and some of their transformation products in a small lentic waterbody: Fish, water, and sediment contamination in an agricultural watershed. Environ. Pollut. 292, 118403. https://doi.org/10.1016/j.envpol.2021.118403.

Soose, L.J., Rex, T., Oehlmann, J., Schiwy, A., Krauss, M., Brack, W., Klimpel, S., Hollert, H., Jourdan, J., 2024. One like all? Behavioral response range of native and invasive amphipods to neonicotinoid exposure. Environ. Pollut. 356, 124235. https://doi.org/10.1016/j.envpol.2024.124235.

Sornom, P., Felten, V., Médoc, V., Sroda, S., Rousselle, P., Beisel, J.-N., 2010. Effect of gender on physiological and behavioural responses of *Gammarus roeseli* (Crustacea: Amphipoda) to salinity and temperature. Environ. Pollut. 158, 1288-1295. https://doi.org/10.1016/j.envpol.2010.01.022.

Szöcs, E., Brinke, M., Karaoglan, B., Schäfer, R.B., 2017. Large Scale Risks from Agricultural Pesticides in Small Streams. Environ. Sci. Technol. 51, 7378-7385. https://doi.org/10.1021/acs.est.7b009333.

Tao, Y., Liu, J., Xu, Y., Liu, H., Yang, G., He, Y., Xu, J., Lu, Z., 2022. Suspecting screening "known unknown" pesticides and transformation products in soil at pesticide manufacturing sites. Sci. Total Environ. 808, 152074. https://doi.org/10.1016/j.scitotenv.2021.152074.

Taylor, E.J., Rees, E.M., Pascoe, D., 1994. Mortality and a drift-related response of the freshwater amphipod *Gammarus pulex* (L.) exposed to natural sediments, acidification and copper. Aquat. Toxicol. 29, 83-101. https://doi.org/10.1016/0166-445X(94)90050-7.

Techer, D., Banas, D., 2018. Contrasted effects of an anti-cyanobacterium ultrasound device on the non-target freshwater invertebrate species *Gammarus roeseli*. Environ. Sci. Pollut. Res. 25, 1998-2004. https://doi.org/10.1007/s11356-017-0980-4.

Ulrich, U., Hörmann, G., Unger, M., Pfannerstill, M., Steinmann, F., Fohrer, N., 2018. Lentic small water bodies: Variability of pesticide transport and transformation patterns. Sci. Total Environ. 618, 26-38. https://doi.org/10.1016/j.scitotenv.2017.11.032.

Ulrich, U., Lorenz, S., Hörmann, G., Stähler, M., Neubauer, L., Fohrer, N., 2022. Multiple pesticides in lentic small water bodies: Exposure, ecotoxicological risk, and contamination origin. Sci. Total Environ. 816, 151504. https://doi.org/10.1016/j.scitotenv.2021.151504.

Ulrich, U., Pfannerstill, M., Ostendorp, G., Fohrer, N., 2021. Omnipresent distribution of herbicides and their transformation products in all water body types of an agricultural landscape in the North German Lowland. Environ. Sci. Pollut. Res 28, 44183-44199. https://doi.org/10.1007/s11356-021-13626-x.

Van Der Oost, R., Beyer, J., Vermeulen, N.P.E., 2003. Fish bioaccumulation and biomarkers in environmental risk assessment: a review. Environ. Toxicol. Pharmacol. 13, 57-149. https://doi.org/10.1016/S1382-6689(02)00126-6.

Velisek, J., Stara, A., Zuskova, E., Kubec, J., Buric, M., Kouba, A., 2018. Chronic toxicity of metolachlor OA on growth, ontogenetic development, antioxidant biomarkers and
histopathology of early life stages of marbled crayfish. *Sci. Total Environ.* 643, 1456–1463. https://doi.org/10.1016/j.scitotenv.2018.06.309.

Vellinger, C., Felten, V., Sornom, P., Rousselle, P., Beisel, J.-N., Usseglio-Polatera, P., 2012. Behavioural and Physiological Responses of *Gammarus pulex* Exposed to Cadmium and Arsenate at Three Temperatures: Individual and Combined Effects. *PLoS ONE* 7, e39153. https://doi.org/10.1371/journal.pone.0039153.

Vellinger, C., Gismondi, E., Felten, V., Rousselle, P., Mehennaoui, K., Parant, M., Usseglio-Polatera, P., 2013. Single and combined effects of cadmium and arsenate in *Gammarus pulex* (Crustacea, Amphipoda): Understanding the links between physiological and behavioural responses. *Aquat. Toxicol.* 140–141, 106–116. https://doi.org/10.1016/j.aquatox.2013.05.010.

Vobis, H., 1973. Rheotaktisches Verhalten einiger Gammarus-Arten bei verschiedenem Sauerstoff- gehalt des Wassers. *Helgoländer wiss. Meeresunters.* 25, 495–508.

Weisner, O., Frische, T., Liebmann, L., Reemtsma, T., Roß-Nickoll, M., Schäfer, R.B., Schäffer, A., Scholz-Starke, B., Vormeier, P., Knillmann, S., Liess, M., 2021. Risk from pesticide mixtures – The gap between risk assessment and reality. *Sci. Total Environ.* 796, 149017. https://doi.org/10.1016/j.scitotenv.2021.149017.

Wigh, A., Geffard, O., Abbaci, K., François, A., Noury, P., Bergé, A., Vulliet, E., Domenjoud, B., Gonzalez-Ospina, A., Bony, S., Devaux, A., 2017. *Gammarus fossarum* as a sensitive tool to reveal residual toxicity of treated wastewater effluents. *Sci. Total Environ.* 584 1012–1021. https://doi.org/10.1016/j.scitotenv.2017.01.154.

Wijewardene, L., Wu, N., Qu, Y., Guo, K., Messyasz, B., Lorenz, S., Riis, T., Ulrich, U., Fohrer, N., 2021. Influences of pesticides, nutrients, and local environmental variables on phytoplankton communities in lentic small water bodies in a German lowland agricultural area. *Sci. Total Environ.* 780, 146481. https://doi.org/10.1016/j.scitotenv.2021.146481.

Włodkowic, D., Bownik, A., Leitner, C., Stengel, D., Braunbeck, T., 2022. Beyond the behavioural phenotype: Uncovering mechanistic foundations in aquatic eco-neurotoxicology. *Sci. Total Environ.* 829, 154584. https://doi.org/10.1016/j.scitotenv.2022.154584.

Woods, M., Kumar, A., Correll, R., 2002. Acute Toxicity of Mixtures of Chlorpyrifos, Profenofos, and Endosulfan to Ceriodaphnia dubia. *Bull. Environ. Contam. Toxicol.* 68, 801–808. https://doi.org/10.1007/s00128-002-0026-5.

Wu, B., Tian, F., Zhang, M., Piao, S., Zeng, H., Zhu, W., Liu, J., Elnashar, A., Lu, Y., 2022. Quantifying global agricultural water appropriation with data derived from earth observations. *J. Clean. Prod.* 358, 131891. https://doi.org/10.1016/j.jclepro.2022.131891.

Xuereb, B., Chaumot, A., Mons, R., Garric, J., Geffard, O., 2009a. Acetylcholinesterase activity in *Gammarus fossarum* (Crustacea Amphipoda). *Aquat. Toxicol.* 93, 225–233. https://doi.org/10.1016/j.aquatox.2009.05.006.

Xuereb, B., Lefèvre, E., Garric, J., Geffard, O., 2009b. Acetylcholinesterase activity in *Gammarus fossarum* (Crustacea Amphipoda): Linking AChE inhibition and behavioural alteration. *Aquat. Toxicol.* 94, 114–122. https://doi.org/10.1016/j.aquatox.2009.06.010.

Xuereb, B., Noury, P., Felten, V., Garric, J., Geffard, O., 2007. Cholinesterase activity in *Gammarus pulex* (Crustacea Amphipoda): Characterization and effects of chlorpyrifos. *Toxicology* 236, 178–189. https://doi.org/10.1016/j.tox.2007.04.010.

Zahn, D., Arp, H.P.H., Fenner, K., Georgi, A., Hafner, J., Hale, S.E., Hollender, J., Letzel, T., Schymanski, E.L., Sigmund, G., Reemtsma, T., 2024. Should Transformation Products Change the Way We Manage Chemicals? *Environ. Sci. Technol.*, acs.est.4c00125 https://doi.org/10.1021/acs.est.4c00125.

Zhang, L., Song, Z., Zhong, S., Gan, J., Liang, H., Yu, Y., Wu, G., He, L., 2022. Acute hypoxia and reoxygenation induces oxidative stress, glycometabolism, and oxygen transport change in red swamp crayfish (*Procambarus clarkii*): Application of transcriptome profiling in assessment of hypoxia. *Aquac. Rep.* 23, 101029. https://doi.org/10.1016/j.aqrep.2022.101029.

Zivkovic, A.R., Paul, G.M., Hofer, S., Schmidt, K., Brenner, T., Weigand, M.A., Decker, S. O., 2023. Increased Enzymatic Activity of Acetylcholinesterase Indicates the Severity of the Sterile Inflammation and Predicts Patient Outcome following Traumatic Injury. *Biomolecules* 13, 267. https://doi.org/10.3390/biom13020267.