Auteur moral

Auteur secondaire

Résumé

"Pesticides are mainly used in agroecosystems to control pests. Due to their limited specificity, the resulting widespread contamination may cause unintended effects on non-target organisms that use these habitats. While increasing attention is paid to the relationship between single substances and phenotype on non-target species, their combined impacts are still largely unknown. Since interactions between pesticides may also impact organisms' health, studying them as complex mixtures is the more realistic approach. Here, we present the first experimental study testing the relationship between an environmentally relevant pesticide mixture and health biomarkers on a farmland avian non-target model. To do so, we used 40 semi-captive grey partridges (Perdix perdix) fed for five months with conventional grains. Their plant protection product (PPP) load (i.e., the number of PPPs, the total sum of scaled pesticide concentrations and the total toxicity index) in blood and proxies ofhealth status (evaluated using behavioral and physiological features) were monitored at the end of the exposure period. We demonstrated, for the first time, concerning correlations between PPP load indexes and bird healthrelated features (physical activity, flight initiation distance, eye ring redness and acetylcholinesterase activity). Overall, we highlighted the urgent need to consider environmentally-relevant PPP mixture when biomonitoring non-target vertebrates in ecotoxicological studies."

Editeur

Elsevier

Descripteur Urbamet

Descripteur écoplanete

impact sur l'environnement ;effet sur la santé ;produit phytosanitaire ;faune sauvage

Thème

Environnement - Nature ;Environnement - Paysage ;Ressources - Nuisances ;Santé ;Risques

Texte intégral

First evidence of deleterious effect of pesticide mixture on health status in semi-captive grey partridges Sophie M. Dupont a,b,* , Agathe Gaffard c, Anaïs Rodrigues d, Maurice Millet d , Coraline Bichet c , Maria Teixeira e , Vincent Bretagnolle c,f, Karine Monceau c , Olivier Pays g,h, Jérôme Moreau c a CEFE, Univ Montpellier, CNRS, EPHE, IRD, 34293, Montpellier, cedex 5, France b CIBIO/InBIO, Centro de Investigação Em Biodiversidade e Recursos Genéticos, Campus de Vairão, Universidade do Porto, 4485-661, Vairão, Portugal c Centre d?Etudes Biologiques de Chizé, UMR-CNRS 7372, La Rochelle Université, 79360, Villiers-en-bois, France d Institute of Chemistry and Processes for Energy, Environment and Health (ICPEES), UMR 7515, CNRS & University of Strasbourg, 67087, Strasbourg, France e UMR, CNRS 6282 Biogéosciences, Université Bourgogne Franche-Comté, 21000, Dijon, France f dLTSER ?Zone Atelier Plaine & Val de Sèvre?, 79360, Villiers-en-Bois, France g Univ Angers, BIODIVAG, 49045, Angers, France h REHABS, International Research Laboratory, CNRS-Université Lyon 1-Nelson Mandela University, 6531, George, South Africa A R T I C L E I N F O Keywords: Biomonitoring Farmland bird Plant protection products Health status A B S T R A C T Pesticides are mainly used in agroecosystems to control pests. Due to their limited specificity, the resulting widespread contamination may cause unintended effects on non-target organisms that use these habitats. While increasing attention is paid to the relationship between single substances and phenotype on non-target species, their combined impacts are still largely unknown. Since interactions between pesticides may also impact or- ganisms? health, studying them as complex mixtures is the more realistic approach. Here, we present the first experimental study testing the relationship between an environmentally relevant pesticide mixture and health biomarkers on a farmland avian non-target model. To do so, we used 40 semi-captive grey partridges (Perdix perdix) fed for five months with conventional grains. Their plant protection product (PPP) load (i.e., the number of PPPs, the total sum of scaled pesticide concentrations and the total toxicity index) in blood and proxies of health status (evaluated using behavioral and physiological features) were monitored at the end of the exposure period. We demonstrated, for the first time, concerning correlations between PPP load indexes and bird health- related features (physical activity, flight initiation distance, eye ring redness and acetylcholinesterase activity). Overall, we highlighted the urgent need to consider environmentally-relevant PPP mixture when biomonitoring non-target vertebrates in ecotoxicological studies. 1. Introduction Plant protection products (hereafter PPPs) are mainly used in agro- ecosystems to control pests such as fungi, insects, and viral pathogens (European Commission, 2009). However, besides their limited speci- ficity and their persistence in the environment (Navarro et al., 2007; Cuevas et al., 2018; Giorio et al., 2021), PPPs end up in different envi- ronmental compartments via runoff and aerial deposition notably (Mitchell et al., 2017; Silva et al., 2019; Pelosi et al., 2021). Conse- quently, non-target wildlife is exposed to PPP mixtures (Mineau, 2011; Pelosi et al., 2021; Brodeur et al., 2022; Fritsch et al., 2022; Larras et al., 2022), which may partly explain its decline (IPBES et al., 2019; Groh et al., 2022). By being dependent on agroecosystem for their food and their reproduction, many bird species are particularly sensitive to PPPs contamination (Carson, 2015; Rigal et al., 2023). Specifically, a growing number of studies have highlighted non-negligible alteration of birds? behavior, health-related physiological traits, survival and reproduction through deleterious consequences on endocrine, immunological and neurological systems (Lopez-Antia et al., 2013; Eng et al., 2019; Zeid et al., 2019; Rawi et al., 2019; Moreau et al., 2022). However, most studies were conducted ex situ, and usually tested the effects of single * Corresponding author. CEFE, Univ Montpellier, CNRS, EPHE, IRD, 34293, Montpellier, cedex 5, France. E-mail address: sophie.dupont93@gmail.com (S.M. Dupont). Contents lists available at ScienceDirect Environmental Research journal homepage: www.elsevier.com/locate/envres https://doi.org/10.1016/j.envres.2025.123332 Received 11 July 2025; Received in revised form 26 October 2025; Accepted 12 November 2025 Environmental Research 289 (2026) 123332 Available online 14 November 2025 0013-9351/© 2025 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC license ( http://creativecommons.org/licenses/by- nc/4.0/ ). molecules under controlled conditions (Moreau et al., 2022). This may warn against the sublethal effects of an active molecule individually, but it does not provide an understanding and realistic overview of the multiple chemicals to which individuals are concomitantly exposed by in their natural environment (Fuentes et al., 2025). Concerningly, multiple chemical contamination could increase the probability of deleterious effects on non-target organisms (through synergistic in- teractions, Moreau et al., 2022). How non-target organisms are contaminated by chemical mixtures is increasingly reported (Gómez-Ramírez et al., 2014) but the relationship with health status still remains to be demonstrated in both sexes (Woodruff, 2011; Siddig et al., 2016; Brodeur et al., 2022). As a first step, concomitantly measuring individual contamination level and its relationship with physiological and behavioral health parameters should be conducted in semi-controlled conditions mimicking natural ecotoxicological expo- sure. Such methodological approach takes advantage to closely monitor given individuals and control for food and water provided while exposing organisms to natural abiotic environmental contaminants, i.e., air, and soil. Here, 40 semi-captive (females and males) grey partridges (Perdix perdix) were fed on grains from conventionally grown crops. It then mimics the contamination of partridges by pesticides in the grains they naturally eat in winter, even though they also eat other things, such as leaves (Orlowski et al., 2011). The grey partridge is a farmland bird which has undergone a major decline in Europe since 1950, mainly due to agricultural intensification, in which exposure to pesticides is sus- pected to play a role (Sotherton et al., 2014; Bro et al., 2016). They live in crops and feed on seeds, leaves and insects from cultivated fields. Management of this farmland species has benefitted from Europe-wide extensive research (Sotherton et al., 2014; Bro et al., 2016). Among others, experimental studies on semi-captive grey partridges already highlighted sublethal behavioral and physiological effects after inges- tion of conventional grains containing PPP residues (Moreau et al., 2021; Gaffard et al., 2022) but no blood pesticide levels were assessed at that time. To our knowledge, no study has yet assessed the key rela- tionship between PPP load and its organisms? effect. Here, for the first time in an avian species, a multiple analysis of PPP residues in blood (i. e., 94 PPPs belonging to different pesticide families) was used to eluci- date bird contamination and test the link between PPP load indexes and multiple robust health parameters in both sexes. Specifically, to get a clear overview of health affliction, we measured both behavioral and physiological features, namely flight initiation distance, physical activ- ity, body condition, eye ring redness, hematocrit, acetylcholinesterase (AchE) activity, and haptoglobin concentration in both female and male partridges. These monitored parameters were chosen because they are easily measurable, financially affordable, minimally invasive (one unique 160 ?L blood sample allowed the analysis of all physiological parameters and one unique capture event is required, limiting stress experienced by the birds). In addition, their responses to PPPs have already partly been reported in numerous toxicological studies (Moreau et al., 2022). Briefly, flight initiation distance (a proxy of risk-taking) and activity are two informative behaviors about nervous system func- tionality, general individual condition and stress responsiveness when facing a danger (Seltmann et al., 2012). They are sensitive to PPP exposure (Gaffard et al., 2022b), and are either inhibited (e.g., due to AChE inhibition; Mineau and Palmer, 2013) or exacerbated (e.g., to compensate for physiological processes impairment; Moreau et al., 2022) with PPPs contamination. Body condition determines the corpu- lence of individuals according to their body mass and size as a proxy of energy capital accumulated by feeding (Peig and Green, 2009). PPP contamination is associated with a decrease in body condition in red-legged partridges (Lopez-Antia et al., 2013) whereas the opposite pattern, i.e. an increase in body condition, is observed in grey partridge females (Moreau et al., 2021). In Grey Partridge, mate choice is influ- enced by the redness of the patch behind their eyes, the intensity of which is determined by carotenoid reserves (Svobodová et al., 2013). Carotenoids are pigments obtained from diet and are involved in immunocompetence, antioxidant defenses, and secondary sexual trait coloration in birds (see Møller, 2000 for a review). Exposure to PPPs, such as thiram and imidacloprid, has been shown to increase antioxidant defenses (Lopez-Antia et al., 2013, 2015a, 2015b), possibly leading to allocation trade-offs between cellular maintenance and expression of sexual ornaments (Baeta et al., 2008). Hematocrit reflects the nutritional state of individuals and is known to decrease with individual condition in birds (Ots et al., 1998; e.g., Lopez-Antia et al., 2013). Its impairment by pesticide contamination is expected but still needs to be demon- strated. AChE is an enzyme that hydrolyses acetylcholine, which is a major neurotransmitter in the central and peripheral nervous system. Several PPPs have been shown to affect AChE activity (e.g., organo- phosphates and carbamates), with behavioral and body condition alteration (Mitra et al., 2011; Moreau et al., 2022). Haptoglobin is a multifunctional acute phase protein that can increase rapidly in response to health impairment, such as infection or inflammation (Matson et al., 2012; Quaye, 2008). This protein plays an antioxidant role by being responsible for binding free hemoglobin to limit damage caused by reactive oxygen species (ROS) released during inflammation (Quaye, 2008). Thus, in the ecotoxicological context, haptoglobin con- centration may increase to mitigate ROS damage under PPP-induced oxidative stress. Because of differential assimilation and detoxification capacities, we first predicted that our experimental protocol would induce distinct individual patterns of PPP loads in blood. Our second prediction is a negative relationship between blood PPP contamination and health parameters. Finally, we expected sex-specific health re- sponses to PPP contamination due to differential endocrine physiology between females and males notably. 2. Material and methods The experiments carried out in this study were in compliance with animal experimentation French laws. The Committee of Animal Exper- imentations of the Deux-Sèvres French District approved the experi- mental protocol below (APAFIS#9465?201703101551625). 2.1. Experimental design The 5-month experimental protocol was conducted from autumn 2020 to spring 2021, i.e., out of the Grey Partridge?s breeding season. It took place in a commercial game farm in an agricultural area in south- western France (La Grossière, Deux-Sèvres - France, Bariod et al., 2024). The site is largely surrounded by cultivated fields, covering about 75 % of the area within a radius of 500 m (including 5 % certified organic practices), mostly composed of cereal crops (~80 %) and pastures (20 %). The remaining portions of this heterogenous landscape consist of forest patches and village areas. The forty 7-month-old wintering immature grey partridges (20 females and 20 males, sexed based on their sexual ornaments appearing after their first molt) monitored in the study are all captive birds (N = 35) from the study of Bariod et al. (2024). Briefly, they were randomly selected from a group of 200 un- related partridges living in the same pen and fed on adequate com- mercial poultry food (STARGIB entretien) since their birth in the game farm in spring 2020. These captive-born grey individuals originated from a wild genetic strain (F3 generation of wild trapped birds, Gaffard et al., 2022). The 40 partridges were individually identified with an alphanumeric metal ring, relocated to a metallic pen (100 m × 10 m × 4 m) with muddy and grassy soil continuous with surrounding area, equipped with feeders, drinkers, metal sheets with wooden structure for shelters and exposed to a natural light cycle. No dogs or cats were allowed inside the aviaries, but it is impossible to be certain that dogs, feral cats, or other animals didn?t come near the fence, as the area was not enclosed. Both sexes were mixed in the pen. From this stage, all individuals were daily fed ad libitum on natural grains from conven- tionally grown crops, i.e., with various PPP sprayed during the cropping S.M. Dupont et al. Environmental Research 289 (2026) 123332 2 season, composed of 25 % wheat, corn, pea and faba bean (see Table S1 for the list of chemical substances detected in grains based on the QuEChERS NF 15662 protocol (C.E.C.F., 2008), using multi-residue liquid and gas chromatography coupled with mass spectrometry ana- lyses (limit of quantification: 0.010 mg kg? 1). Each analytical method was associated with a specific extraction process and solvent used to maximize the range of pesticides searched, based on their polarity and physicochemical properties, GIRPA, Angers, France). No PPPs were added to those present in the food provided to the partridges. To note, the experimental wire aviary is located on the edge of conventional fields and then not protected from aerial and soil pesticide contamina- tion, notably. Thanks to this continuity with environmental surround- ing, we then considered the pen as a semi-field environment for partridges (Bariod et al., 2024). However, no analyses of air, water or soil contamination were conducted for this study. Overall, such logis- tical setup is in accordance with our research objective of mimicking the effects of exposure to pesticide residues in a homogeneous environment, just as partridges are exposed to in natura when there is few organic produce nearby. In other words, the aim of this experiment is not to distinguish between a control (feeding with organic seeds ? i.e., con- taining fewer and lower residues than conventional grains ? associated with total captive abiotic isolation from outdoor environmental to achieve the lowest possible contamination levels) and an experimental group nor to identify the origin of the contamination but rather to examine the possible relationship between contamination levels and health biomarkers. During the experiment, 5 partridges died before being sampled (2 females and 3 males respectively, representing 12.5 % of mortality), which is not unusual in breeding farms (J. Blandin, per- sonal communication). At the end of the experiment (March 2021), grey partridges were one year old and sexually matures. The remaining in- dividuals (n = 35 with 18 females and 17 males) were monitored to assess their blood PPP load and their health status based on behavioral and physiological traits. In detail, after a one-night resting period, we first assessed flight initiation distance and physical activity behaviors for all individuals on a unique morning. Immediately after behavioral tests, we measured physiological traits including body condition, eye ring redness, hematocrit, AChE activity and blood haptoglobin concentra- tion. To do so, 160 ?L (110 ?L for physiological features + 50 ?L for the pesticides analysis) of blood were collected from the brachial vein with a sterile needle (Ø 0.06 mm) and heparinized micro-capillary tubes. Blood was stored in Eppendorf tubes at ? 80 ?C until subsequent laboratory analyses (±3 months between collection and lab analyses). To note, while we do agree that getting baseline values for partridges contami- nation and our health proxies would have been valuable to assess their modulation under the experimental treatment, this protocol decision was guided by ethical considerations. Indeed, grey partridges are highly sensitive to stress and all health metrics of interest required handling the birds. Yet, capturing them from the semi-open aviary already imposes considerable stress to individuals and can even induce mortality (e.g., partridges injuring themselves against the enclosure grid, J. Moreau and J. Blandin personal communication). Therefore, to respect animal wel- fare and ensure their well-being, we minimized as possible stressful procedures and decided to capture and handle the birds only once, i.e., at the very end of the experimental procedure. Here, they were all born, raised under identical conditions, and provided identical conventional food during wintering. Therefore, we would consider that any notice- able correlation highlighted in this study between our individuals to be associated with differential individual pesticide assimilation, tolerance and/or detoxication capacities. 2.2. Multiple PPP residue analyses In total, 94 molecules were searched in each blood sample following the validated method for bird blood and plasma (Rodrigues et al., 2023). Briefly, non-volatile and volatile compounds were analyzed with Liquid Chromatography and Gas Chromatography respectively coupled to tandem Mass Spectrometry (LC-MS/MS and GC-MS/MS respectively). For each PPP, the multiple reaction monitoring (MRM) mode with two mass transitions, one for quantification, and one for qualification, was used. The concentration of each detected PPP was expressed in mg.kg? 1 (see Table S2 for details, limit of quantification: [0.004; 0.500] x 10? 3 mg kg? 1). For both the sum of scaled concentrations and the toxic unit calculation, when a PPP was detected at a level below the limit of quantification (LOQ) but above the limit of detection (LOD), the PPP-specific LOQ/2 value was attributed. When a PPP was not detected in partridge blood (<LOD), the concentration value was set at LOQ/6. This left-censored data treatment is a standard procedure for this type of analysis (Tekindal et al., 2017). A detailed description of contamination data for these 35 partridges is provided in Bariod et al. (2024). To assess the PPP load of partridges, we first determined the number of PPPs (NPPP) detected in the blood of each bird. Although this approach does not consider the toxicity of the compounds, partridges were contaminated by, it corresponds to an informative metric to measure the cumulative risk related to potential additive and/or syn- ergistic effects in PPP mixtures (i.e., an increasing number of PPPs leads to an increased number of potential interactions among molecules, and thus toxicity, Zaller et al., 2022). Then, we calculated the total sum of scaled pesticide concentrations (?[pesticides]scaled) for each partridge. Indeed, pesticide concentration in birds? blood do not range on the same scale. Thus, to make them comparable and to assess the intensity of individuals? contamination, we standardized them independently. To do so, we first applied a normal-scale transformation (mean-centering and scaling, [pesticide]individual ? [pesticide]mean [pesticide]standard deviation ) to each detected substance. As a result, negative [pesticides]scaled values correspond to low levels of pesticide contamination, whereas positive values represent substantial ones. Then, we summed all scaled concentrations measured per individual. The resulting composite index provides a quantitative estimate of the total amount of pesticides a bird is contaminated by. A negative value is reflecting lower level of contamination compared to positive value, interpreted as a non-negligible contamination (i.e., an increasing level of PPPs contamination may lead to an increased toxic risk, Tartu et al., 2014; Fritsch et al., 2022 but see Hernández et al., 2017). The third variable representative of partridges PPP load we calculated was the total toxic unit per bird (TUtot), which indicates the potential toxicity of pesticide mixtures an individual was contaminated by. It was deter- mined using a concentration addition method, which implies that indi- vidual components of the mixture contribute to mixture toxicity in proportion to their individual concentration and toxicity (Kortenkamp et al., 2009). As such, TUtot was here defined as the sum of each PPP toxic unit (TU), essentially the ratio between PPP concentration and the corresponding LD50, calculated as follows: TUtot = ?n i=1 TUi,with TUi = PPP concentration ( mg.kg? 1 ) PPP LD50 ( mg.kg? 1 ) TU calculations are based on LD50 data for each substance from the Pesticide Properties Database (Lewis et al., 2016, see Table S2). When the reported available LD50 values exceeded 2000 mg kg? 1, we considered 2000 mg kg? 1 as the LD50 value in the calculation. 2.3. Flight initiation distance and physical activity behaviors All partridges were caught the evening of the last experimental day (i.e., when supplied with conventional grains). They were kept in cardboard boxes overnight (5 birds per box, 66 cm × 38 cm × 17.5 cm at 7? 11 ?C). On the morning, each bird experienced the same sequence of tests, which consisted of a risk-taking test in a cage outside and physical activity measurement in an open-field test. Tests were conducted suc- cessively in the same order for all birds. Each behavioral test was con- ducted by a unique observer (A. G.). Flight initiation distance test was used to assess partridge risk-taking behavior, evaluating the distance (in meters) at which the individual begins to run or fly when a danger, i.e., a S.M. Dupont et al. Environmental Research 289 (2026) 123332 3 human observer here, approaches (Shen et al., 2005). Briefly, a long distance indicates a strong response to danger (the bird reacts even when the threat is far away), whereas a short distance reflects a reduced response to danger (the bird waits until the threat is very close before reacting). To do so, one operator placed the partridge in a square wire cage (46 cm × 32 cm × 36 cm) in a ploughed field. Simultaneously, the observer was hidden behind a hedge, 100 m from the cage, and moni- tored partridge behavior with binoculars. After 3 min of acclimatization, the observer approached the bird and stopped as soon as the bird reacted (any movement). The straight-line distance between the observer and the bird was then measured using an odometer (0.5 cm of accuracy). Then, the bird was caught by the operator, put in a cardboard box (66 cm × 38 cm × 17.5 cm) and brought in a building (5 m × 5.5 m × 1.50 m, 7?11 ?C, 30.5 lux) next to the pen where the physical activity mea- surement was conducted. First, the partridge was left for 3 min of acclimatization in the cardboard box inside the open-field arena. Then, the studied partridge was released for 4 min. The observer remained hidden in a corner behind a sheet during this test period. The physical activity behavior of the partridge was assessed on live, by measuring the time (in seconds) the bird spent moving. Once the tests were completed, partridges were released into their pen. 2.4. Body condition We recorded body mass with a spring scale to the nearest 1 g (Pesola 500g). We measured the left and right tarsus length using a caliper with a 0.1 mm accuracy. Because of the significant morphometric sexual dimorphism in this species, we assessed the body condition separately for females and males, using the scaled mass index (SMI, Peig and Green, 2009). Average tarsus length was positively correlated with body mass (rfemale = 0.392, tfemale = 1.70, p-valuefemale = 0.108; rmale = 0.691, tmale = 3.70, p-valuemale = 0.002). We then calculated the SMI, implemented with the smatr package in the R software, by applying the following formula: SMI = Mi x ( L0 Li )b , with Mi and Li the body mass and the average tarsus length of the individual I respectively; L0 the arithmetic mean value of tarsus length for all females and males respectively (L0, female = 42.7 mm, n = 18 females, L0,male = 44.5 mm, n = 17 males); the exponent b the slope estimate of a standardized major axis regression of log-transformed body mass on log-transformed average tarsus length (bfemale = 2.36, bmale = 2.05). 2.5. Eye ring redness Eye ring redness was assessed following the detailed protocol developed by Lopez-Antia et al. (2013) for red-legged partridge that has been slightly adapted and validated for grey partridge (Moreau et al., 2021). In brief, two high-resolution digital images were taken on each side of the head using the same digital camera (Stylus TG-2; Olympus) under standardized light conditions (no flash, zoom × 2.4, dis- tancecamera-bird = 70 cm, same indoor location). The intensity of eye ring redness was calculated using the RGB color values. To correct inter-image color divergence, the color characteristics of the standard grey card, located in the picture area, were also extracted from all im- ages (see Moreau et al., 2021 for the detailed protocol applied). 2.6. Hematocrit At blood collection, 10 ?L was placed in a micro-heparinized capil- lary. After centrifugation at 5000 rpm for 5 min, the same observer (A. G.) measured the tube height totally filled with liquid and filled with red blood cells only. The hematocrit corresponds to the red blood cells portion divided by the total sample part (Svensson and Merila, 1996). 2.7. AChE activity AChE activity was determined in total blood with a spectropho- tometer using a colorimetric technique derived from Ellman method (Ellman et al., 1961; Fuentes et al., 2023; Patel, 2023). Five microliters of blood were diluted in 100 ?L of 1 % Triton X-100 solution, which hemolyzed the cells, and samples were shaken for 30 min at 4 ?C, then centrifuged at 14,000 rpm for 5 min at 4 ?C to pellet blood cell debris. Ten microliters of hemolyzed blood supernatant were then added to 285 ?L of a 0.25 mM solution of Aldrithiol-4 (Sigma Aldrich) in phosphate buffer and 5 ?L of a 120 mM propionylthiocholine iodide (Sigma Aldrich) solution as AChE substrate. The absorbance was read at 324 nm every minute for 40 min at 37 ?C using a SpectraMax iD3 microplate reader (Molecular Devices, San Jose, CA, USA). AChE activity was calculated using SoftMax Pro7 software as the rate of change of absor- bance per minute (mU.min? 1) during the linear portion of the kinetics. 2.8. Haptoglobin concentration Haptogoblin was quantified in 7.5 ?L plasma samples using a commercially available assay (TP-801l Tri-Delta Diagnostics, Ireland), which colorimetrically measures the heme-binding capacity of plasma. We followed the instructions provided by the manufacturer with slight modifications (Matson et al., 2012). Standards ranging from 0.039 to 2.50 mg mL? 1 were included in duplicate in each plate, as well as a negative control. Samples were randomly distributed across the two plates, and the absorbance was measured by a SpectraMax iD3 spec- trophotometer (Molecular Devices) at 620 nm both before and after addition of the final reagent inducing the colorimetric reaction. These two measures allowed controlling for among-sample differences in color and cloudiness (Matson et al., 2012). Results are given in mg.mL? 1. Using the standards, we calculated the intra-plate (3.06 %) and inter-plate (3.14 %) coefficients of variability. 2.9. Statistical analyses All statistical analyses were performed with the R software (R Core Team, 2022; version 4.0.4). Relationships between partridge PPP load (NPPP, ?[pesticides]scaled and TUtot) and variables reflecting health sta- tus (flight initiation distance, physical activity behavior, body condition, eye ring redness, hematocrit, AChE activity, and haptoglobin concen- tration) were assessed using 21 linear models in total. Following Burn- ham?s recommendation (Burnham et al., 2011), we used AICc model selection and full-model averaging estimate (Symonds and Moussalli, 2011; Bolker, 2024), using the MuMIn package in the R software (see Table S4 for details about AICc model selection). In detail, for the seven dependent variables of health status, three models were performed separately including NPPP, ?[pesticides]scaled or TUtot as predictor respectively. Sex and body condition were also included in models to account for potential between-individuals differences, as well as the two-way interactions (Sex x PPP load and Body condition x PPP load respectively). AChE activity was log-transformed to achieve statistical requirements on the model?s residuals. Before building the models, we found no relationship between sex or body condition and any PPP load index (Table S3) allowing us to concomitantly include these two explanatory variables in the models. Correlation between individual features were assessed and reported in Fig. S1A and B. Model assump- tions were visually checked. For all tests, p-values are given at the 5 % significance level. 3. Results 3.1. Partridge blood PPPs load Among the 94 PPPs assessed in partridge blood, 29 were detected in at least one blood sample, including 12 herbicides, 14 fungicides and 3 S.M. Dupont et al. Environmental Research 289 (2026) 123332 4 insecticides (see Table S2). Partridge NPPP values varied from 1 to 14 molecules detected per blood sample (Table 1). Partridge ?[pestici- des]scaled ranged from ? 8.42 to 43.8 mg kg? 1 (Table 1). Partridge TUtot values ranged from 9.38 × 10? 6 to 3.26 × 10? 3 (Table 1). NPPP was positively correlated with ?[pesticides]scaled (rPearson = 0.867, p < 0.001) but no correlation was found with TUtot (rPearson = 0.141, p = 0.418). ?[pesticides]scaled and TUtot were not related (rPearson = 0.277, p = 0108). 3.2. Relationship between PPPs blood load and health status Physical activity and eye redness were negatively associated with NPPP in both female and male partridges (Fig. 1A and B respectively, Table 2; ? = ? 57.3, p = 0.021; ? = ? 0.062, p = 0.050, respectively). However, these relationships seem to be primarily driven by a single female (Nppp = 14, Fig. 1), as removing this individual from the analyses resulted in the loss of all significant correlations between Nppp and the health biomarkers. The interaction ??[pesticides]scaled x sex? was significantly correlated with flight initiation distance (? = ? 30.4, p = 0.005). In detail, flight initiation distance was negatively correlated with ?[pesticides]scaled in males while no relationship was found in fe- males (Fig. 1C?Table 2). To note, this correlation disappears when the male with a very low flight initiation distance is excluded (Flight initi- ation distance <15, Fig. 1). Moreover, AChE activity was negatively linked to TUtot (Fig. 1D?Table 2; ? = ? 0.147, p = 0.034). Finally, both body condition, hematocrit and haptoglobin were not affected by any of the PPP indexes tested (Table 2). To note, we observed a positive rela- tionship between AchE activity and body condition but a negative link between haptoglobin and body condition (Table 2). 4. Discussion Under semi-controlled conditions, we revealed the ubiquity of PPP contamination in blood and the possible impairment of four out of seven partridge health-related proxies by an environmentally-relevant PPP mixture. Our study highlights the large diversity, as well as the impor- tant inter-individual variability, of PPPs detected in partridge blood, while all individuals were kept under identical conditions, i.e., out of treated crops. Concerningly, partridges with higher NPPP would show lower physical activity and reduced intensity of visual sexual signals. Moreover, partridges contaminated with the higher pesticide levels would have delayed response to danger (shorter flight initiation dis- tance). Finally, partridges with higher TUtot would present lower AChE activity. Importantly, all partridges were born under the same conditions, fed the same food (ground feed mixture followed by conventional grains) and lived in the same environment. Nonetheless, the variability in the number, levels and toxicity of PPPs (i.e., NPPP, ?[pesticides]scaled and TUtot) present in partridge blood highlighted a gradient of PPP load between individuals. Considering our experimental setup, it supports inter-individual differences in PPP assimilation, and/or detoxification capacities. Interestingly, the pesticide mixture patterns (compounds and concentrations) found in semi-captive partridges are similar to those found in wild grey partridge eggs (Bro et al., 2016, the only available paper we found in this species at the time of publication). In a nutshell, among the 15 pesticides found in partridges eggs collected in north-central France, 5 of them (33 %) were also detected at comparable levels in partridges? blood in south-western France (i.e., Diphenylamine, Fenpropidin, Diflufenican, Thiametoxam, Tebuconazole). Such obser- vation then suggests that our experimental setup may be trustfully mimicking the environmental ecotoxicological context and encourages to pursue the investigation in such semi-captive configuration. To note, the detection and quantification of these 5 compounds were not ex- pected in both regions, given the locally implemented potential expo- sure assessment method (Bro et al., 2015) and the official governmental pesticide purchase records for 2019?2021 in this department respec- tively. Such unexplained observation is also true for the two other main compounds (Nitempyram and Tolylfluanid) quantified in a large pro- portion of birds in our study. Yet, Diphenylamine (i.e., the most frequently detected PPP in our partridges) is one of the most used PPPs worldwide and is often found as residues in soils (EFSA, 2012). Addi- tionally, several PPPs, including Tolylfluanid and Carbendazim which are banned and/or not approved by EC regulation 1107/2009 for many years, are also known to be highly persistent in water (Singer et al., Table 1 Descriptive information for all variables used in this study. Proxies of grey partridge health status were considered as variables to explain. PPP load features (NPPP, ?[pesticides]scaled, TUtot) were included as explanatory variables in the models. Body condition Eye ring redness All birds Females Males All birds Females Males Min - Max 323.10?416.80 323.10?416.80 331.70?410.40 Min - Max 1.26?1.84 1.26?1.64 1.61?1.84 Mean ± SE 371.70 ± 3.71 375.80 ± 5.58 367.40 ± 4.78 Mean ± SE 1.58 ± 0.02 1.47 ± 0.03 1.70 ± 0.01 Hematocrit Flight Initiation Distance ? All birds Females Males ? All birds Females Males Min - Max 33.01?50.90 33.01?50.65 34.66?50.90 Min - Max 12.00?62.00 20.90?60.20 12.00?62.00 Mean ± SE 43.37 ± 0.66 42.20 ± 0.98 44.61 ± 0.79 Mean ± SE 45.50 ± 1.82 46.06 ± 2.30 44.90 ± 2.93 log AchE activity Haptoglobin ? All birds Females Males ? All birds Females Males Min - Max 3.49?4.46 3.53?4.46 3.49?4.17 Min - Max 0.09?0.43 0.09?0.40 0.19?0.43 Mean ± SE 3.90 ± 0.04 3.89 ± 0.06 3.90 ± 0.05 Mean ± SE 0.28 ± 0.02 0.25 ± 0.02 0.32 ± 0.02 Physical activity ? ? ? ? ? All birds Females Males ? ? ? ? Min - Max 1.00?240.00 1.00?240.00 24.00?240.00 ? ? ? ? Mean ± SE 132.10 ± 12.50 123.50 ± 18.63 141.20 ± 16.81 ? ? ? ? NPPP ?[pesticide]scaled ? All birds Females Males ? All birds Females Males Min - Max 1.00?14.00 1.00?14.00 3.00?7.00 Min - Max ? 8.42 - 43.78 ? 8.42 - 43.78 ? 6.24 - 10.57 Mean ± SE 5.14 ± 0.40 5.89 ± 0.69 4.35 ± 0.30 Mean ± SE 0.00 ± 1.57 1.92 ± 2.84 ? 2.04 ± 1.11 TUtot x10¡3 ? ? ? ? ? All birds Females Males ? ? ? ? Min - Max 0.009?3.261 0.009?2.413 0.028?3.261 ? ? ? ? Mean ± SE 0.701 ± 0.135 0.573 ± 0.138 0.837 ± 0.238 ? ? ? ? S.M. Dupont et al. Environmental Research 289 (2026) 123332 5 2010; Reemtsma et al., 2013). In addition, the various PPP loads re- ported in the partridges differ from the PPPs detected in the conven- tional grains they were fed with (Table S1). Indeed, none of the pesticides quantified in grains were present in the blood (only Tebuco- nazole was both found in grains and blood of a single bird, see Bariod et al., 2024). Such result might actually be explained by the difference in measurement protocol and detection/quantification sensitivity (LODg- rain = 0.001 mg kg? 1 vs LODpartridge blood = 0.015 x 10? 3 mg kg? 1). In other words, grains can be contaminated by additional pesticides, un- detected with the lab technique employed here, that can become quantifiable in partridge blood because of their chronic exposure to these compounds. However, such hypothesis is only minimally sup- ported as pesticides were searched for in blood, i.e., a biological matrix mostly capturing immediate pesticide contamination rather than accu- mulable compounds (which requires tissue biopsies on muscle or liver, an invasive procedure for animals). Based on PPDB information, we also reported that most compounds quantified in grains and blood were low persistent. Altogether, it raises questions about the source(s) of contamination in our current experimental setup. Indeed, semi-captive partridges were under partially protected conditions from PPPs (i.e., not living directly in treated fields but with air and soil continuity). However, because of the numerous contamination possible pathways (i. e., food, water, respiratory system, dermal contact) and contamination spatial range (i.e., contamination may originate from aviary items but also because some pollutants can spread over 1000 km in the atmo- sphere and through clouds, Shen et al., 2005; Bianco et al., 2025), we can?t explain the actual PPP mixtures found in partridges. Overall, the only element that can be pointed out from such result is the (potential) limited ingestion pathway in the individual PPP contamination. By examining the interplay of multiple pesticide contamination on partridges? health, our study indicates, in accordance with our predic- tion, some potential associations between PPP load and key avian bio- markers. First, the negative relationship between AChE activity and TUtot may suggest that PPPs can affect the avian nervous system, which corroborates the literature showing that several families of PPP, spe- cifically insecticides, can induce neurological alterations in birds (Casida and Bryant, 2017; Casida, 2018). For instance, neonicotinoids (e.g., Nitempyram and Thiametoxam found in partridge blood) may induce neuronal degeneration, affecting AChE activity (Zeid et al., 2019; Brodeur et al., 2022). Our result then suggests that the partridges with the higher TUtot would experience significant physiological stress impacting the physical activity of birds, as neurotoxicity may lead to decreased activity (Lopez-Antia et al., 2013). However, changes in TUtot were not correlated with physical activity but the higher the NPPP in the blood, the less active the partridges seem to be. In addition, the higher the contamination level (?[pesticides]scaled), the higher risk-taking (estimated here by flight initiation distance) the partridges would be, further highlighting the potential neurotoxicity of PPP mixtures. In addition, higher NPPP seemed to decrease partridge?s eye ring redness. Interestingly, the coloration of the eye ring depends on the concentra- tion of carotenoids in plasma. These pigments, essentially provided by food, are involved in both immunocompetence and secondary sexual trait coloration in birds, including grey partridges (Svobodová et al., 2013). As carotenoids may be in limited quantities in the environment and required for both sexual ornamentation and self-maintenance (Baeta et al., 2008), they may be robust integumentary markers of trade-off in their allocation when birds are contaminated by PPPs. Regarding our results, we can thus expect that under physiological stress induced by PPP mixtures, carotenoids could be involved in cellular functions such as immune defense rather than in eye ring redness with a Fig. 1. Relationship between (A) eye ring redness, (B) physical activity and the number of pesticides an individuals is contaminated by (NPPP); (C) flight initiation distance and the scaled sum of pesticides an individuals is contaminated by (?[pesticides]scaled) and (D) log-transformed acetylcholinesterase activity and the toxic unit index (TUtot) respectively. Each dot represents one individual. The blue line corresponds to the whole-population linear regression with shaded region showing the 95 % confidence interval range. Red and green dots represent females and males respectively. Red and green lines correspond to sex-specific linear regressions (females and males respectively) with shaded regions showing the 95 % confidence interval range. S.M. Dupont et al. Environmental Research 289 (2026) 123332 6 Table 2 Proxies of grey partridge health status according to PPP load, sex, body condition and their interactions. Tests were performed using linear models. The best models were selected using AICc criteria followed by a model averaging approach. All variables from the models with a ?AICc <2 are presented here. Significant effects are in bold type. Parameters estimates, standard errors, z-value and p-value are provided here with the 95 % confident interval. The information provided for the associations between log-transformed acetylcholinesterase activity and NPPP and ?[pesticides]scaled respectively are from the linear regression test directly (no other model with a ?AICc <2). NPPP Body condition ? Estimate SE adjusted SE z-value p-value 2,5 % 97,5 % NPPP ? 0.92 3.81 3.92 0.23 0.815 ? 20.25 10.62 Sex ? 2.49 5.55 5.66 0.44 0.661 ? 23.30 6.69 Eye ring redness ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % NPPP ¡0.06 0.03 0.03 1.96 0.050 ¡0.12 0.07 x 10¡3 Sex 0.21 0.03 0.03 6.83 < 0.001 0.15 0.28 BC 0.01 0.02 0.02 0.52 0.607 ? 0.02 0.10 ? ? ? ? ? ? ? ? log AchE activity (mU.min? 1) ? Estimate SE F-value t-value p-value ? ? BC 3.51 x 10¡3 1.56 x 10¡3 5.04 2.25 0.031 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? Haptoglobin (mg.mL? 1) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % Sex 0.04 0.03 0.04 1.18 0.239 2.46 x 10? 3 0.11 BC ¡0.10 0.03 0.03 3.39 < 0.001 ¡0.16 ¡0.04 ? ? ? ? ? ? ? ? Hematocrit (%) ? Estimate SE adjusted SE z-value p-value 2.50 % 97.50 % NPPP ? 1.78 1.58 1.61 1.11 0.27 ? 5.16 0.23 Sex 1.18 1.43 1.46 0.81 0.42 ? 0.66 4.76 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? Flight Initiation Distance (m) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % NPPP ? 1.21 2.75 2.80 0.43 0.67 ? 11.72 3.28 BC ? 0.81 2.32 2.37 0.34 0.73 ? 11.05 4.04 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? Physical activity (s) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % NPPP ¡57.32 23.86 24.78 2.31 0.021 ¡105.89 ¡8.76 BC ? 8.10 17.94 18.36 0.44 0.659 ? 73.29 24.13 ? ? ? ? ? ? ? ? ?[pesticide]scaled Body condition ? Estimate SE adjusted SE z-value p-value 2,5 % 97,5 % Sex ? 3.07 6.02 6.15 0.50 0.617 ? 23.35 6.69 ? ? ? ? ? ? ? ? Eye ring redness ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % ?[pesticide]scaled ? 0.03 0.03 0.04 0.87 0.386 ? 0.12 0.01 Sex 0.23 0.03 0.03 7.27 < 0.001 0.17 0.29 BC 0.02 0.03 0.03 0.74 0.458 ? 0.02 0.10 ?[pesticide]scaled x BC 0.02 0.06 0.06 0.33 0.745 ? 0.06 0.35 log AchE activity (mU.min? 1) ? Estimate SE F-value t-value p-value ? ? BC 3.51 x 10¡3 1.56 x 10¡3 5.04 2.25 0.031 ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? Haptoglobin (mg.mL? 1) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % Sex 0.04 0.03 0.04 1.18 0.239 2.46 x 10? 3 0.11 BC ¡0.10 0.03 0.03 3.39 < 0.001 ¡0.16 ¡0.04 ? ? ? ? ? ? ? ? Hematocrit (%) ? Estimate SE adjusted SE z-value p-value 2.50 % 97.50 % ?[pesticide]scaled ? 0.42 0.98 1.00 0.42 0.673 ? 4.17 1.28 Sex 1.62 1.55 1.58 1.03 0.303 ? 0.22 5.04 BC 0.22 0.73 0.74 0.30 0.766 ? 1.35 3.98 ? ? ? ? ? ? ? ? Flight Initiation Distance (m) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % ?[pesticide]scaled ¡17.23 5.07 5.27 3.27 0.001 ¡27.56 ¡6.90 Sex ? 5.42 3.50 3.64 1.49 0.136 ? 12.56 1.71 BC ? 2.10 3.26 3.32 0.63 0.526 ? 11.66 1.95 ?[pesticide]scaled x Sex ¡30.36 10.31 10.74 2.83 0.005 ¡51.41 ¡9.32 Physical activity (s) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % ?[pesticide]scaled ? 20.43 26.63 27.10 0.75 0.451 ? 90.07 11.21 BC ? 5.56 16.13 16.57 0.34 0.737 ? 71.01 31.98 ? ? ? ? ? ? ? ? TUtot Body condition ? Estimate SE adjusted SE z-value p-value 2,5 % 97,5 % TUtot ? 1.14 4.09 4.20 0.27 0.786 ? 21.02 9.78 Sex ? 2.45 5.52 5.63 0.44 0.663 ? 23.36 6.69 Eye ring redness ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % Sex 0.24 0.03 0.03 7.64 < 0.001 0.18 0.30 BC 0.02 0.03 0.03 0.71 0.478 ? 0.01 0.11 (continued on next page) S.M. Dupont et al. Environmental Research 289 (2026) 123332 7 potentially deleterious effect on partridge reproductive success through reduced attractiveness (Baeta et al., 2008). To go further in our under- standing of this carotenoid-pesticides relationship, it is now necessary to quantify carotenoids content in grains provided as well as in all potential sources of food in their environment (e.g., grass covering the aviary floor) and in partridge blood. Finally, contrary to our prediction, we only highlighted limited sex-specific phenotypical responses on PPP load indexes (i.e., risk taking behavior). Such lack of effect could potentially be explained by the age of studied birds during the experi- ment (?1-year-old) as well as by the observed lack of sex-specific PPP load difference itself (Table S3). Overall, the limited robustness of the correlations we obtained may be attributed to the small sample size of this study. While some might recommend excluding the two individual outliers, it is important to note that, in ecotoxicology studies in partic- ular, extreme values are not uncommon (Barron et al., 2021; Hughes et al., 2021). They may actually represent individuals with exceptional pesticide resistance or detoxification capacities. It is then important to retain these individuals in the analyses, while remaining cautious with biological interpretations of observed correlations. The effect of PPPs on individuals depends on complex combinations of multiple factors such as exposure pathways, PPP mode of actions, their toxicity, their concentration, and the repetition of exposure (acute vs chronic), and many variables which are difficult to control even under experimental conditions. Here, the biological processes underpinning the detrimental relationships between PPP mixtures and health status remain to be elucidated especially since NPPP, ?[pesticides]scaled and TUtot do not allow to understand the potential interactions among molecules. In other words, the observed effects may therefore be due either to the action of a single molecule or to overall impregnation levels reaching an unknown threshold that disrupts organismal homeostasis, with consequences for physiology and behavior, or to the combined synergistic, antagonistic and additive effects of all the pesticides to which an individual is exposed. However, there are no existing models to assess potential synergism or antagonism in PPP mixtures (Cedergreen, 2014; Larras et al., 2022). Concentration addition models are often proposed for risk assessment of chemical mixtures (Panizzi et al., 2017; Schell et al., 2018; Brodeur et al., 2022) but their use is still debated. First, they are considered to be more parsimonious and more conservative than independent action models (Panizzi et al., 2017; Kortenkamp et al., 2009), neglecting possible synergism and antagonism that potentially increase with the number of chemicals. Second, they are less data-demanding as they utilize existing data like Lethal Dose 50 (LD50) by applying the concept of toxic units (Verbruggen and Van den Brink, 2010; Nicholson et al., 2024). The LD50 is the most widely used value for expressing the (acute) toxicity of a substance for wildlife fauna. But in our case, chronic No-Observed Effect Level (NOEL) might have been more consistent with our 5-months exposure setup. However, these chronic indexes are not available for all PPPs (see Table S2 for the NOEL associated with PPPs found in partridge blood for instance). In any case, there are no concrete methods to date that allow assessing efficiently the toxic effects of PPP mixture (Erickson and Rattner, 2020; Moreau et al., 2022). We then chose the approach that permits an estimation based on the available toxicity data for birds. Altogether, our study highlighted the negative effects of environmentally-relevant PPP mixtures number, cumulative levels and toxic unit on the health status of a non-target model organism. Because of the inter-individual differences in PPP contamination, our study emphasizes the need to assess assimilation, tolerance and detoxification capacities in ecotoxicology studies. Our result is particularly important to consider as the studied partridges present a common genetic back- ground and are more specifically the F3 generation from wild in- dividuals. Effects reported with our experimental setup on these birds can then concerningly be transposed to wild partridges (Gaffard et al., 2022). Negative biological effects highlighted in this study could be potentially critical to the survival and reproduction of birds and may translate into altered population dynamics, explaining the observed species decline in agroecosystems (Sotherton et al., 2014). Applying the multiple PPP residue analysis in the blood of wild vertebrates would then be the next step to conduct at the global scale, as one recent study (Bariod et al., 2024) highlighted that wild grey partridges in our study area are exposed to a wider variety and higher concentration of PPPs than semi-captive birds. Such an approach will be crucial to account for the contamination of their environment at the individual level but also anticipate health risks for individuals and the associated consequences at the population level. Overall, questioning the health effects of a PPPs mixture on a non-target vertebrate species will provide us some insights into the impacts on humans? health ? another critical non-target verte- brate species ? as part of the One Health concept (Xie et al., 2017). CRediT authorship contribution statement Sophie M. Dupont: Writing ? original draft, Formal analysis. Agathe Gaffard: Writing ? review & editing, Methodology, Data cura- tion, Conceptualization. Anaïs Rodrigues: Writing ? review & editing, Table 2 (continued ) TUtot ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? log AchE activity (mU.min? 1) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % TUtot ¡0.15 0.07 0.07 2.12 0.034 ¡0.28 ¡0.01 Sex 0.01 0.04 0.04 0.30 0.766 ? 0.08 0.19 BC 0.11 0.08 0.08 1.28 0.199 3.78 x 10? 3 0.27 Haptoglobin (mg.mL? 1) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % TUtot 0.01 0.02 0.03 0.55 0.582 ? 0.02 0.10 Sex 0.04 0.03 0.04 1.02 0.308 ? 1.30 x 10? 3 0.11 BC ¡0.10 0.03 0.03 3.36 < 0.001 ¡0.16 ¡0.04 Hematocrit (%) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % TUtot 2.30 1.57 1.61 1.43 0.152 ? 0.03 5.44 Sex 1.53 1.48 1.51 1.01 0.313 ? 0.31 4.84 BC 0.77 1.46 1.48 0.52 0.604 ? 1.44 5.59 TUtot x BC 0.97 3.22 3.27 0.30 0.766 ? 2.99 19.00 Flight Initiation Distance (m) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % TUtot ? 2.47 3.78 3.86 0.64 0.522 ? 12.72 3.95 BC ? 0.80 3.51 3.61 0.22 0.824 ? 11.94 8.40 TUtot x BC 4.45 11.75 11.90 0.37 0.709 ? 5.52 58.05 ? ? ? ? ? ? ? ? Physical activity (s) ? Estimate SE adjusted SE z-value p-value 2.5 % 97.5 % Sex 3.87 13.87 14.26 0.27 0.786 ? 33.57 68.93 BC ? 3.98 14.13 14.52 0.27 0.784 ? 70.05 33.89 ? ? ? ? ? ? ? ? S.M. Dupont et al. Environmental Research 289 (2026) 123332 8 Methodology, Data curation. Maurice Millet: Writing ? review & edit- ing, Methodology, Conceptualization. Coraline Bichet: Writing ? re- view & editing, Methodology. Maria Teixeira: Writing ? review & editing, Methodology. Vincent Bretagnolle: Writing ? review & edit- ing, Methodology. Karine Monceau: Writing ? original draft, Method- ology, Funding acquisition, Formal analysis, Conceptualization. Olivier Pays: Writing ? review & editing, Supervision, Funding acquisition, Conceptualization. Jérôme Moreau: Writing ? original draft, Supervi- sion, Methodology, Data curation, Conceptualization. Funding sources This research was funded by the French National Centre for Scientific Research (CNRS), by the French National Research Institute for Agri- culture, Food and the Environment (INRAE), by the ANR JCJC Pesti- Stress (#19-CE34-0003-01), by the BioBird project funded by the regional government of Nouvelle-Aquitaine, and by the French National program EC2CO (Ecosphère Continentale et Côtière). Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgment We thank Julien Blandin for allowing us to work on his farm, and for taking care of partridges during the course of this study. We are grateful to the Fédération des Chasseurs (79), its president Guy Guédon, Frédéric Audurier and Simon Billon for their help and support during experi- mental setup. We also would like to thank Landry Boussac for his assistance during part of the monitoring. We are indebted to Juliette Rabdeau for her help in adapting laboratory techniques to partridges. This research was funded by the French National Centre for Scientific Research (CNRS), by the French National Research Institute for Agri- culture, Food and the Environment (INRAE), by the ANR JCJC Pesti- Stress (#19-CE34-0003-01), by the BioBird project funded by the regional government of Nouvelle-Aquitaine, and by the French National program EC2CO (Ecosphère Continentale et Côtière). Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.envres.2025.123332. Data availability The data and R script will be made available on request. References Baeta, R., et al., 2008. Carotenoid trade-off between parasitic resistance and sexual display: an experimental study in the blackbird (Turdus merula). Proc. R. Soc. A B. 275, 427?434. https://doi.org/10.1098/rspb.2007.1383. Bariod, L., et al., 2024. Comparison of pesticide contamination between captive-reared and wild grey partridges: insights into environmental exposure disparities. 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