Skip to main content
NCBI home page
Conservation Physiology logoLink to Conservation Physiology
. 2026 Oct 6;14(1):coag077. doi: 10.1093/conphys/coag077

Xenobiotic exposure may confound traditional stress biomarkers: evaluating perfluoropentanoic acid and cadmium effects on largemouth bass (Micropterus nigricans) leukocyte profiles

Anthony Ryan Johnson 1, Tyler Steven Coleman 2,✉, Jasmine B Nasser 3, Maggie McGreal 4, Kyle R Piller 5, Christopher M Murray 6
PMCID: PMC13640471  PMID: 42840702

Abstract

Understanding how contaminants influence physiological stress is vital for conserving aquatic organisms in increasingly altered environments. We examined whether exposure to cadmium (Cd) or perfluoropentanoic acid (PFPeA)—a short-chain per- and polyfluoroalkyl substance—altered neutrophil-to-lymphocyte ratios (NLRs) in largemouth bass (Micropterus nigricans) under controlled laboratory conditions. Using NLR as a leukocyte-based biomarker associated with physiological stress responses, we compared five groups (control, Cd low, Cd high, PFPeA low, PFPeA high) across four sampling periods (baseline, post-treatment, 3 h after an abrupt salinity increase and 7 days later). High PFPeA exposure elevated NLR values within 4 days of treatment relative to the other groups. Following salinity exposure, all groups exhibited acute increases in NLR; however, elevated NLR persisted only in the high-PFPeA group 1 week later. Neither Cd treatment nor low PFPeA exposure altered NLR relative to controls. Our findings suggest that high PFPeA exposure may alter leukocyte dynamics and influence the interpretation of leukocyte-based stress biomarkers in freshwater fishes exposed to additional environmental stressors. More broadly, xenobiotic contaminants may complicate the interpretation of physiological biomarkers used in conservation and management contexts.

Keywords: Cadmium, largemouth bass, leukocyte profiles, per- and polyfluoroalkyl substances, perfluoropentanoic acid, stress

Introduction

Physiological biomarkers are increasingly used in conservation physiology to evaluate how organisms respond to environmental perturbations, including habitat degradation, climate change, salinity shifts, and contaminant exposure (Feder, 1987; Wikelski and Cooke, 2006; Cooke et al., 2014). Metrics such as comparative leukocyte profiles (Murray et al., 2013), endocrine markers (Aerts et al., 2015), and relative performance (Kern and Langerhans, 2019) have been used to evaluate disturbance in aquatic systems. Among these biomarkers, leukocyte profiles—particularly neutrophil-to-lymphocyte ratios (NLRs)—have become widely used indicators of vertebrate stress responses because glucocorticoid-mediated stress responses predictably increase circulating neutrophils while decreasing lymphocyte abundance (Davis et al., 2008; Goessling et al., 2015). Elevated NLR values have been associated with acute and chronic environmental stressors across vertebrate taxa and are commonly used to assess stress physiology in ecological and conservation contexts (Watson et al., 2020; Brosset et al., 2021; Mallett et al., 2024).

Environmental contaminants may complicate the interpretation of leukocyte-based stress biomarkers because many xenobiotics can independently alter endocrine and immune function. Per- and polyfluoroalkyl substances (PFASs) are highly persistent anthropogenic compounds (Croteau et al., 2005; Ali et al., 2019; Schymanski et al., 2023; Edo et al., 2024) widely distributed throughout aquatic ecosystems due to decades of industrial and commercial use (Ritter et al., 2002; Lescord et al., 2015; Gaines, 2023). Although long-chain PFAS compounds have historically received the greatest toxicological attention, short-chain replacement compounds are increasingly detected in aquatic systems (Wang et al., 2013; Walsh et al., 2025) and remain comparatively understudied (Brendel et al., 2018; Guillette et al., 2020). Existing evidence suggests PFAS exposure may disrupt endocrine signalling, alter thyroid function, induce oxidative stress, and modify immune responses in fishes and other vertebrates (Fang et al., 2013; Birgersson et al., 2021; Coperchini et al., 2021; Piva et al., 2022). In fishes specifically, PFAS exposure has been associated with altered immune biomarkers, thyroid disruption, and changes in leukocyte abundance (Guillette et al., 2020; Birgersson et al., 2021). Consequently, contaminant exposure may influence leukocyte dynamics and complicate the interpretation of physiological stress biomarkers in response to additional environmental stressors.

In addition to PFAS compounds, heavy metals (e.g. cadmium [Cd]) are widespread aquatic contaminants (Wu et al., 2016; Kahlon et al., 2018) with well-documented physiological and immunological effects in fishes (Javed and Usmani, 2019; Bera et al., 2022; Shahjahan et al., 2022). Exposure to Cd has been linked to oxidative stress, endocrine disruption, altered osmoregulatory function, and immunoregulation across freshwater taxa (Hontela et al., 1992; Jezierska and Witeska, 2006; Jezierska et al., 2009; Atli and Canli, 2010; Liu et al., 2022). PFAS compounds and Cd may alter physiological stress responses through endocrine (Coperchini et al., 2021, 2024; Nayak et al., 2023), immune (Fang et al., 2013, 2026; Guillette et al., 2020), and nervous (Starnes et al., 2022) system disruption. Therefore, xenobiotic exposure may alter how organisms respond to additional environmental challenges (Barton, 2002).

Salinity fluctuations are particularly relevant secondary stressors in many freshwater systems as saltwater intrusion continues to impact our freshwater resources (Barlow and Reichard, 2010; Cao et al., 2024). Abrupt osmotic changes can activate endocrine stress pathways, disrupt ionoregulation, and alter leukocyte dynamics in fishes (Boeuf and Payan, 2001; Barton, 2002; Wang et al., 2019). Evaluating contaminant-associated changes in leukocyte responses following salinity exposure may improve our understanding of how xenobiotic exposure influences the interpretation of stress biomarkers under ecologically relevant multi-stressor conditions.

Although previous studies have demonstrated that contaminants can alter leukocyte profiles and immune function, relatively few studies have evaluated whether xenobiotic exposure modifies leukocyte-based stress responses following secondary environmental perturbations. Understanding these interactions is important because physiological biomarkers are frequently used to assess organismal condition and environmental stress in conservation, fisheries, and ecological monitoring programs (Cooke et al., 2013). Furthermore, while xenobiotics are released into our freshwater ecosystems at unpredictable rates (Pinheiro et al., 2021; Sharma et al., 2025), there is considerable concern about the management of socioeconomically important fishes in freshwater fisheries.

Largemouth bass (Micropterus nigricans; Lacépède, 1802; Lesueur, 1822; Kim et al., 2022) are ecologically and economically valuable freshwater predators widely distributed across North America (Tringali et al., 2015; Taylor et al., 2019) that are commonly used in ecotoxicological and fisheries research (Ludsin and DeVries, 1997; Hanson and Cooke, 2009; Kieffer and Cooke, 2009; Coleman et al., 2024). Since largemouth bass are top-level piscivores that frequently inhabit systems exposed to agricultural runoff, industrial discharge, and saltwater intrusion, they are valuable sentinel organisms for evaluating physiological responses in freshwater ecosystems. Previous studies have demonstrated that largemouth bass exhibit measurable physiological and behavioural responses to environmental disturbance, including contaminant exposure and salinity stress (Sloman and Wilson, 2005; Norris et al., 2010; Yi et al., 2021; Song et al., 2024; Xie et al., 2024). Therefore, largemouth bass are suitable for evaluating how xenobiotic exposure may influence the interpretation of leukocyte-based stress biomarkers following secondary environmental perturbations.

Here, we evaluated whether exposure to cadmium (Cd) and perfluoropentanoic acid (PFPeA; a short-chain PFAS compound commonly used in consumer products) altered leukocyte profiles (NLR; a stress biomarker) in largemouth bass before and after an experimental salinity exposure. Previous studies have evaluated the effects of xenobiotic substances on fishes using stress proxies (e.g. Hontela et al., 1992; Wilson et al., 1994; Baker et al., 2013; Seriani et al., 2015a, 2015b; Corrêa et al., 2017; Correia et al., 2019; Rodgers et al., 2019; Witeska et al., 2023), but none, to our knowledge, have tested interactions between xenobiotics and environmental stressors on biomarker utility. We hypothesized that xenobiotic exposure would both elevate NLR, with stronger responses at higher concentrations, and that NLR would remain elevated following salt exposure (Fig. 1). Understanding these interactions between contaminants and environmental stressors is important for improving freshwater ecosystem management and interpreting stress physiology in natural populations.

Figure 1.

Conceptual graph showing predicted NLRs across four blood samples. Contaminant exposure is expected to increase ratios more at high than low concentrations, followed by further increases in all groups after salinity exposure.

Open in a new tab

Hypothesized relationships among largemouth bass NLRs, low and high levels of cadmium (Cd) and perfluoropentanoic acid (PFPeA), and an environmental stressor (salinity increase). We anticipated that exposure to Cd or PFPeA, indicated by the dashed ‘treatment’ line between blood samples 1 and 2, would lead to elevated NLR values, particularly in groups receiving higher doses of each toxin. Furthermore, we expected the NLR to increase continuously in all fish after exposure to an abruptly introduced environmental stressor, as represented by the dashed ‘salt’ line between blood samples 2 and 3.

Materials and methods

Aquaculture tank design

We assembled 15–37.9 l of rectangular tanks across three shelves, with five tanks per row (Fig. 2). We positioned opaque barriers along the elongated sides of each tank and placed a fine-mesh cover on top. Each tank contained 34.6 l of tap water treated with Seachem Prime concentrated conditioner (Seachem Laboratories, Madison, GA, USA) and a 25-mm aerator (multiport air pump; Aquatic Ecosystems Inc., Apopka, FL, USA). We kept the room under constant low-indirect light throughout the study.

Figure 2.

Experimental layout showing 15 individually housed largemouth bass assigned to five groups: control and low or high concentrations of cadmium or PFPeA. A timeline shows blood sampling on Days 3, 14, 15, and 22, contaminant addition on Day 10, and salt addition on Day 15.

Open in a new tab

Overview of study design and experimental timeline. We arranged 15 largemouth bass in individual 37.9-l rectangular tanks in three rows, with opaque boundaries along the long sides (indicated by thick solid black bars) and a mesh top (indicated by dashed grey bars). Each tank contained 37.6 l of conditioned tap water (light blue) and was equipped with an aerator (yellow bubbler). We randomized the treatment order across the tanks (five groups, each represented by a different colour). Below the tank design, in connected boxes, we illustrate the chronological order of significant daily events from the start (Day 1) to the conclusion of the trial (Day 22).

Each tank housed a single largemouth bass. Therefore, the individual fish and tank were synonymous experimental units throughout the study. We randomly assigned each tank to one of five groups using a random number generator—control, Cd low (0.034 ppm), Cd high (0.34 ppm), PFPeA low (3.4 mg/l), PFPeA high (34 mg/l)—with three fish per group (Fig. 2).

The PFPeA high concentration (34 mg/l) exceeded PFAS concentrations observed in natural aquatic systems (Pan et al., 2014; Lescord et al., 2015; Mussabek et al., 2023). However, the PFPeA low group (3.4 mg/l) represented concentrations more consistent with reported environmental observations in aquatic systems (Kurwadkar et al., 2022). Similarly, reported Cd concentrations in aquatic systems may range from ~0.2 to 0.4 mg/l (Cossa, 1988; Anzecc, 2000). We used an order-of-magnitude scale to evaluate a range of potential physiological responses under controlled laboratory conditions, including concentrations exceeding environmentally typical levels. Experimental toxicology studies commonly include elevated concentrations when toxicological thresholds and biomarker responses remain poorly understood (Everds et al., 2013; Lewis et al., 2024).

We used 15 individuals (three fish per group) to balance replication with available space, animal-care considerations, and the need for repeated blood sampling. Throughout the study, we monitored the fish daily and did not feed the bass to minimize variation in physiological responses associated with differential feeding activity and digestion during repeated blood sampling.

Experimental timeline

Our study lasted 22 days (Fig. 2). On Day 1, the Louisiana Department of Wildlife and Fisheries supplied bass collected through boat electrofishing from holding ponds at the Huey P. Long Fish Hatchery in Lacombe, LA, USA. Louisiana Department of Wildlife and Fisheries employees promptly transported the fish in an aerated livewell to Southeastern Louisiana University in Hammond, LA, USA. Upon arrival, we recorded the total length and body mass of 15 bass and placed each individual into their assigned tank (aquaculture design described in the Aquaculture tank design section above; Fig. 2).

We allowed the fish to acclimate for 2 days (Days 1–2). On Day 3, we collected the first blood sample from the caudal vein of each fish within 3 min of handling without anaesthetics—minimizing any effect of newly induced anthropogenic stress (Davis, 2005; Lawrence et al., 2020)—using a 1-ml syringe and a 25-gauge needle, then re-recorded total length and body mass. On Day 8, we completed partial water changes in all tanks using a DEKO Tools water pump (model CSP9028) to maintain water quality. We did not conduct any additional water changes following contaminant introduction.

To examine whether differing levels of Cd or PFPeA altered baseline NLR, we applied low and high concentrations of Cd (0.034 ppm and 0.34 ppm, respectively) and PFPeA (3.4 and 34 mg/l, respectively; Sigma Aldrich, Darmstadt, Germany, CAS No. 2706-90-3, CF3(CF2)3COOH) directly to the water on Day 10, while the control tanks remained undisturbed. We dissolved both compounds directly into tank water without the use of a carrier solvent; therefore, a solvent control was unnecessary. We analytically verified the masses of Cd and PFPeA added to each tank to ensure consistent nominal concentrations across treatments, but we did not analytically confirm the aqueous contaminant concentrations during the study. On Day 14, we collected total length, body mass, and a second blood sample as before.

On Day 15, to evaluate whether contaminant exposure altered leukocyte-based stress responses following salinity increase, we abruptly increased salinity in all tanks from 0 to ~5 ppt using fast-dissolving Instant Ocean Sea Salt (Figs 2 and 3). We gently mixed the tanks after adding salt to ensure consistent salinity conditions across the tanks and verified salinity immediately after the salt dissolved. Three hours after salt introduction, we collected a third blood sample, total length and body mass, as before. On Day 22, 12 days post-treatment and 7 days post-salt, we collected a final blood sample as before and euthanized all bass using MS-222. The Southeastern Louisiana University Institutional Animal Care and Use Committee (IACUC) approved all procedures described above (IACUC approval 0093).

Figure 3.

Four panels show tank temperature, acidity, dissolved oxygen, and salinity over time, with points coloured by group. Temperature, acidity, and dissolved oxygen remain broadly similar among groups. Salinity rises from near freshwater levels to approximately five parts per thousand after salt addition.

Open in a new tab

Individual tank water quality data (temperature, pH, dissolved oxygen, and salinity) collected from a YSI Pro DSS on each sampling day (Fig. 2). Colour denotes the treatment group (control and low and high levels of cadmium [Cd] and perfluoropentanoic acid [PFPeA]). The first vertical dashed line indicates the day we added treatments, while the second marks the day we added salt. Note that the reported YSI data on Day 15 are before salt addition.

Neutrophil-to-lymphocyte ratio

Interest in leukocyte profiles as chronic stress biomarkers has been highlighted in the literature because, unlike glucocorticoids, leukocyte profiles do not attenuate when a stressor persists chronically and are less affected by metabolic fluctuations (Davis et al., 2008; Goessling et al., 2015). Thus, we utilized leukocyte profiles herein to evaluate stress-associated physiological responses.

Immediately after blood collection, we prepared smears using ~5–10 μl of whole blood on standard glass microscope slides (75 × 25 mm; 1 mm thick) with a two-slide wedge method (Houwen, 2002; Murray et al., 2013). After air-drying, we fixed and stained slides with Giemsa–Wright (Fisherbrand, Pittsburgh, PA, USA). We examined smears under a light microscope (40× magnification), identified the first ~100 leukocytes, and calculated the NLR by dividing the neutrophil count by the lymphocyte count. One observer, blind to treatment groups, identified all leukocytes to ensure consistency among samples.

Water quality measurements

We measured water quality variables—temperature (°C), dissolved oxygen (mg/l), pH, and salinity (ppt)—using a YSI Pro DSS (Yellow Springs Instruments; Xylem Inc., Washington DC, USA) to ensure consistency among tanks. We collected measurements using the YSI on Days 2, 3, 10, 11, 14, and 15 (before and after salinity increase), and again on Day 17 to verify the consistency of the intentional salinity increase. We double rinsed the YSI probe with tap and reverse-osmosis water between tanks to prevent contamination. We used water-quality data to verify consistent environmental conditions across tanks.

Statistical analyses

We visualized and analysed all data using R within Posit’s RStudio Integrated Development Environment (Posit team, 2025; R Core Team, 2025). For statistical testing, we used an alpha value of 0.05.

Between Days 4 and 7, one fish from the control, Cd high, and PFPeA high groups died. A fish from the PFPeA low group died on Day 14 before we collected the second blood sample. We included all blood and water quality data collected before mortality in subsequent analyses. Table 1 provides sample sizes by group and blood sampling period.

Table 1.

Number of largemouth bass contributing blood samples within each group—control, cadmium [Cd] low (0.034 ppm), Cd high (0.34 ppm), perfluoropentanoic acid [PFPeA] low (3.4 mg/l), and PFPeA high (34 mg/l)—during each sampling period

Group Blood 1 Blood 2 Blood 3 Blood 4
Control 3 2 2 2
Cd low 3 3 3 3
Cd high 3 2 2 2
PFPeA low 3 2 2 2
PFPeA high 3 2 2 2
Open in a new tab

Blood sample 1 was collected before contaminant exposure, blood sample 2 after contaminant exposure, blood sample 3 three hours after salinity exposure, and blood sample 4 seven days after salinity exposure. Mortality reduced sample sizes in several treatment groups following the first sampling period.

First, we qualitatively assessed water quality variables throughout the study (Days 2, 3, 10, 11, 14, 15, 17) to ensure temporal consistency among tanks. We then used the total length and body mass data to calculate each individual’s relative weight (Wr), a commonly used condition metric for freshwater fishes (Neumann and Allen, 2007). We used the regression equation for largemouth bass from Anderson and Neumann (1996) to calculate the standard weight (Ws) required in the relative weight (Wr) equation.

To evaluate whether Cd and PFPeA exposure altered NLRs across sampling periods, we used a generalized linear mixed-effects model (GLMM) fit with the glmmTMB package (McGillycuddy et al., 2025). Since NLR values were continuous and strictly positive, we modelled NLR using a Gamma distribution with a log link function. We evaluated distributional fit using the fitdistrplus package (Delignette-Muller and Dutang, 2015). Fixed effects included group (control, Cd low, Cd high, PFPeA low, PFPeA high), blood sampling period (blood samples 1–4) and their interaction. We included individual fish identity as a random intercept to account for repeated measurements collected from the same individual across time.

To evaluate group-specific responses across sampling periods, we releveled groups and blood sampling periods to examine targeted model estimates by group and sampling period. Specifically, we evaluated group-associated changes in NLR following contaminant exposure (blood 1 and blood 2), acute salinity exposure (blood 2 and blood 3), and the final post-salinity sampling period (blood 3 and blood 4), including group-specific differences during the final blood sampling period. We assessed model assumptions using residual diagnostics and visually compared the model’s predicted estimates with the observed data distributions using non-parametric bootstrapping.

Results

Largemouth bass

On Day 1, bass had a mean total length of 183.87 mm [±15.92 mm; 95% confidence interval (CI)] and a mean relative weight of 93.67 (±3.13). By Day 22 (conclusion of the study), mean total length remained unchanged, while mean relative weight declined slightly to 87.64 (±4.79). Mean total lengths among groups were similar: Cd low = 164.20 mm (±6.70 mm), Cd high = 204.92 mm (±15.15 mm), PFPeA low = 171.25 (±17.49 mm), PFPeA high = 196.50 mm (±24.35 mm), and control = 184.42 mm (±16.97 mm). We examined 48 blood smears across all groups (12 Cd low, 9 Cd high, 9 PFPeA low, 9 PFPeA high, 9 control). Across all smears, lymphocyte counts ranged from 13 to 70 cells, whereas neutrophil counts ranged from 30 to 86 cells. NLR values ranged from 0.4 to 6.6 across all individuals.

Water quality

Water temperature, dissolved oxygen and pH remained consistent among tanks throughout the study (Table 2 and Fig. 3). Salinity increased only after we added salt, rising from a mean of 0.13 ppt (±0.0024 ppt; 95% CI) across all tanks before salt intrusion to 4.96 ppt (±0.099 ppt) after salt addition. Water quality values confirmed the experimental salinity increase and indicated stable environmental conditions throughout the study (Table 2 and Fig. 3).

Table 2.

Water quality summary statistics [minimum (min), mean, maximum (max) and 95% CI] among aquaculture tanks throughout the study (see Fig. 3)

Variable Min Mean Max 95% CI
Temp 18.83 20.10 22.11 ±0.16
DO 8.22 8.85 9.30 ±0.056
pH 8.02 8.47 8.85 ±0.035
Pre-salt 0.11 0.13 0.16 ±0.0024
Post-salt 4.65 4.96 5.22 ±0.099
Open in a new tab

The water quality variables included temperature (temp; °C), dissolved oxygen (DO; mg/l), pH, and salinity (salt; ppt), measured using a YSI Pro DSS. Note that ‘pre-salt’ refers to all samples collected before the salinity increase (Days 2, 3, 10, 11, 14, and 15), while ‘post-salt’ denotes the samples from Days 15 and 17, which confirmed the intentional salinity increase. All numeric values are maintained to at least two decimal places while preserving two significant figures.

Contaminant exposure and salinity effects on NLRs

Contaminant exposure (blood samples 1 vs 2)

NLR in the control group did not change between blood samples 1 (Day 3) and 2 (Day 14), representing the pre- and post-toxin periods (Z15,48 = 0.28; P = 0.89; Fig. 4). Neither Cd treatment significantly altered NLR (Cd low: Z15,48 = 0.24; P = 0.81; Cd high: Z15,48 = 0.30; P = 0.32; Fig. 4). PFPeA low showed no effect (Z15,48 = 0.27; P = 0.078; Fig. 4). However, NLR in the PFPeA high group increased by 212% [79–444%; 95% confidence limit (CL)] from blood 1 to blood 2 (Z15,48 = 0.28; P < 0.001; Fig. 4).

Figure 4.

Points show individual fish NLRs, and coloured lines show model estimates across four blood samples. Ratios rise after high PFPeA exposure and remain elevated after salinity increases. Other groups show temporary increases following salinity exposure, followed by declines at the final sample.

Open in a new tab

Largemouth bass NLRs from blood smears throughout the study. The five colours represent individual groups: low and high levels of cadmium (Cd) and perfluoropentanoic acid (PFPeA), and the control. Lines dictate the GLMM estimated relationships among the groups and blood samples (slopes can vary due to the group-by-blood-sample interaction). Jittered points represent individual bass NLR at each blood sample. Exposure to Cd or PFPeA is indicated by the dashed ‘treatment’ line between blood samples 1 and 2. Exposure to an environmental stressor is represented by the dashed ‘salt’ line between blood samples 2 and 3.

The PFPeA high bass NLR increased significantly more than all other groups from blood 1 to blood 2: 201% (37–559%; 95% CL), 195% (42–513%), 133% (3–429%), and 407% (134–996%) more than control (Z15,48 = −2.75; P = 0.0059), Cd low (Z15,48 = −2.90; P = 0.0037), Cd high (Z15,48 = −2.03; P = 0.042), and PFPeA low (Z15,48 = −4.13; P < 0.001) groups, respectively (Fig. 4).

Acute salinity exposure (blood samples 2 vs 3)

All groups showed a significant increase in NLR following salt introduction (Table 3 and Fig. 4). However, the NLR increases were smaller in the PFPeA high group than in the other groups. Control NLR rose 78% (−21–301%; 95% CL) more than PFPeA high (Z15,48 = 1.40; P = 0.16), while Cd low (Z15,48 = 1.75; P = 0.080) and Cd high (Z15,48 = 1.95; P = 0.051) groups rose 94% (−8–307%) and 127% (−1–418%) more, respectively (Fig. 4). PFPeA low increased 173% (21–515%) more than the PFPeA high group (Z15,48 = 2.42; P = 0.016; Fig. 4).

Table 3.

The estimated effect sizes of a known environmental stressor (abrupt salinity increase) on largemouth bass NLRs among the five groups (control and low and high levels of cadmium [Cd] and perfluoropentanoic acid [PFPeA]) between blood samples 2 and 3 from the GLMM (Fig. 4)

Group Effect size 95% CL Z P
Control 158% 46, 357 3.2515,48 0.0012
Cd low 180% 76, 347 4.3215,48 <0.001
Cd high 228% 81, 494 3.9315,48 <0.001
PFPeA low 294% 122, 601 4.6715,48 <0.001
PFPeA high 144% 34, 343 2.9115,48 0.0036
Open in a new tab

The effect size is expressed as a percentage increase from blood 2 to blood 3 [e.g. the control bass NLR increased by 158% (46–357%; 95% CL) from blood 2 to blood 3]. The 95% CLs represent the lower and upper bounds, separated by a comma, such that 95% of repeated studies would contain the true effect size. The Z value is reported with the numerator and denominator degrees of freedom. Bolded groups represent statistically significant changes from blood samples 2 to 3.

Post-salinity exposure (blood samples 3 vs 4)

By Day 22, NLR declined in all groups except PFPeA high (Table 4 and Fig. 4). NLR in the PFPeA high group continued to exhibit elevated NLR values, and was 271% (75–688%; 95% CL), 223% (42–635%), 526% (176–1319%), and 123% (−2–407%) greater than Cd low (Z15,48 = 3.42; P < 0.001), Cd high (Z15,48 = 2.80; P = 0.0051), PFPeA low (Z15,48 = 4.40; P < 0.001), and the control (Z15,48 = 1.92; P = 0.054), respectively (Fig. 4).

Table 4.

The estimated effect sizes of xenobiotic substances on largemouth bass 7 days after a known environmental stressor introduction (blood samples 3 to 4) on NLRs among the five groups (control and low and high levels of cadmium [Cd] and perfluoropentanoic acid [PFPeA]) from the GLMM (Fig. 4)

Group Effect size 95% CL Z P
Control −25% −58, 34 −0.9715,48 0.33
Cd low −55% −72, −27 −3.3015,48 <0.001
Cd high −48% −71, −7 −2.2215,48 0.026
PFPeA low −73% −85, −52 −4.5015,48 <0.001
PFPeA high 68% −6, 202 1.7515,48 0.081
Open in a new tab

The effect size is expressed as a percentage change from blood 3 to blood 4 [e.g. the control bass NLR decreased by 25% (−58% to 34%; 95% CL) from blood 3 to blood 4]. The 95% CLs represent the lower and upper bounds, separated by a comma. The Z value is reported with the numerator and denominator degrees of freedom. Bolded groups represent statistically significant changes from blood samples 3 to 4.

At the end of the study, NLR remained significantly higher in the PFPeA high bass than in all other treatments (P < 0.001 for all comparisons; Fig. 4). NLR values in the control, Cd low, Cd high, and PFPeA low groups did not differ from each other (Fig. 4).

Discussion

PFPeA, not Cd, altered leukocyte-based stress

In this study, we evaluated the effects of two concerning and persistent contaminants—cadmium (Cd) and perfluoropentanoic acid (PFPeA)—at different exposure levels on leukocyte-based stress responses in largemouth bass before and after exposure to a known environmental stressor. Our findings are important because little is known about how these contaminants influence physiological biomarkers commonly used in fishes. The control, Cd low, Cd high, and PFPeA low treatments exhibited relatively stable NLR values throughout the study, whereas bass exposed to high PFPeA concentrations exhibited sustained NLR elevation.

We initially hypothesized that Cd and PFPeA would increase NLR, particularly at higher doses, and that all groups would exhibit elevated leukocyte-based stress responses after the salinity increase (Fig. 1). However, only the PFPeA high group showed consistently elevated NLR throughout our study. After salt exposure, NLR in the other four groups declined to near-baseline levels, suggesting that these fish recovered normally from the environmental disturbance, whereas NLR remained elevated in the PFPeA high group.

To date, PFAS exposure has been associated with diverse physiological disruptions with substantial ecological and health consequences (Mallett et al., 2024). For instance, recent reviews have suggested that increased PFAS exposure increases rates of cancer (Steenland and Winquist, 2021), thyroid disruption (Coperchini et al., 2021), and liver impairment (Costello et al., 2022), and it reduces reproductive potential and juvenile fitness in animals and humans (Chambers et al., 2021). Despite these findings, uncertainties remain because research on PFAS exposure is relatively new, often focuses on a limited subset of PFAS compounds, sometimes yields conflicting results, and remains restricted to a few organisms and exposure scenarios. Our results contribute to this growing body of literature by suggesting that PFPeA, a short-chain PFAS compound, may alter leukocyte dynamics associated with physiological stress responses in vertebrates—a directly relevant component of conservation physiology (Cooke et al., 2013).

Biotic and abiotic consistency

Throughout the study, we took multiple steps to ensure biological and environmental consistency. We intentionally used bass of similar sizes because reducing size variation was important for this experiment, as leukocyte profiles may positively correlate with vertebrate body size (Jaffer et al., 2017; Downs et al., 2020; Naidenko and Alshinetskiy, 2020; Cornelius Ruhs et al., 2021). We restricted food intake during the study, as food consumption can alter metabolic activity, increasing the risk of food-induced changes in leukocyte circulation (Song et al., 2024; Xie et al., 2024). Animals recently introduced to captivity may begin feeding at different times and rates, leading to variability in metabolic activity and immune responses that could confound the effects of contaminant exposure. As expected, we observed a slight decline in relative weight, likely reflecting restricted feeding and confinement, which we deemed acceptable for our study.

Water quality variables remained stable across tanks, confirming consistent environmental conditions. Maintaining consistent abiotic parameters is essential for this type of research, as water conditions can influence the prevalence of various circulating leukocytes in fish species (Corrêa et al., 2017; Shahjahan et al., 2018; Hertika et al., 2022, 2025). By maintaining constant environmental conditions, we reduced the likelihood that observed differences in NLR reflected abiotic variation among tanks.

Contaminant exposure (blood samples 1 vs 2)

Our study provides new evidence that PFPeA exposure may alter leukocyte-based stress responses in freshwater fishes and further supports the utility of NLR as a physiological biomarker associated with stress responses (Davis et al., 2008; Goessling et al., 2015). After introducing the contaminants, we observed sustained NLR elevation in the PFPeA high group, whereas NLR remained comparatively stable in the Cd low, Cd high, PFPeA low, and control groups. As noted earlier, the high PFPeA and Cd doses exceeded concentrations currently detected in natural aquatic systems. We intentionally incorporated an order-of-magnitude dosing scale approach to evaluate physiological responses across a range of contaminant concentrations under controlled laboratory conditions. Such approaches are common in exploratory toxicology because physiological thresholds and biomarker responses are often poorly understood, especially when investigating understudied compounds, such as short-chain PFASs. These order-of-magnitude approaches enhance our understanding for future research.

Our findings align with previous studies indicating that PFAS exposure can alter physiological processes associated with stress responses in fishes. For instance, Schumann et al. (2024) found that freshwater lotic systems with higher PFAS exposure rates were associated with higher plasma cortisol levels. Notably, PFAS compounds’ potential to influence stress-associated physiological processes may pose a significant challenge for fisheries conservation and management, as chronic stress may reduce growth and reproductive rates and increase mortality (Pankhurst and Van Der Kraak, 1997; Schreck, 2010).

Unlike PFPeA exposure, our study suggests that Cd may not induce a stress response in bass. The absence of a Cd effect was unexpected but aligns with previous research on Cd exposure and fish leukocytes, given the duration of our study. For example, the adverse effects of Cd on fishes often emerge with longer exposure durations (Cai et al., 2020; Hu et al., 2021; Liu et al., 2022), and other heavy metals can significantly affect haematological parameters over time (Seriani et al., 2015b). In the freshwater rosy barb (Puntius conchonius), Gill and Pant (1985) discovered that circulating lymphocytes increased after Cd exposure, while neutrophils did not, at 0.63 and 0.84 mg/l of Cd exposure over 90 days. These results suggest that Cd-associated changes in leukocyte profiles may be less detectable over our relatively short 12-day exposure window. Nevertheless, the potential impact of Cd on aquatic organism stress should not be dismissed. Cd remains a major heavy-metal toxicant with detrimental effects in aquatic ecosystems, warranting further exploration.

Acute salinity exposure (blood samples 2 vs 3)

Saltwater intrusion poses a major challenge for coastal communities and ecosystem managers, particularly because it can have additive, synergistic, or antagonistic effects on freshwater, estuarine, and coastal aquatic organisms when combined with other stressors (Barlow and Reichard, 2010; Velasco et al., 2018; Bhattachan et al., 2019; Tully et al., 2019; Cao et al., 2024). We introduced a 5 ppt salinity increase to induce a measurable physiological response and simulate saltwater intrusion, allowing us to assess the potential effects of contaminants interacting with a natural environmental stressor.

We observed that a sudden increase in salinity elevated NLR in all groups. However, the intensity of this response differed among the five groups. NLR increases were smaller in the PFPeA high group compared to the Cd low, Cd high, PFPeA low, and control groups. One possible explanation is that elevated pre-salinity NLR in the PFPeA high group limited the magnitude of subsequent leukocyte redistribution following salt exposure, resulting in a smaller relative change in NLR. Alternatively, PFPeA exposure may have altered physiological pathways associated with leukocyte dynamics, resulting in a different response pattern following the environmental perturbation. The PFPeA low, Cd-exposed, and control bass, which began at lower NLR levels, displayed more substantial—but temporary—NLR increases. Although the direct mechanisms underlying our observed patterns remain unclear, our results suggest that contaminant exposure may influence the interpretation of leukocyte-based stress biomarkers, and potentially other stress biomarkers, when organisms experience new environmental challenges. Such contaminant-associated changes in physiological responses may have implications for resilience in natural populations exposed to chronic contamination.

Post-salinity exposure (blood samples 3 vs 4)

Seven days after the environmental stressor was introduced, NLR values in all groups except PFPeA high declined toward baseline levels. In contrast, NLR remained elevated in the PFPeA high group throughout the study period. The persistent rise of NLR in the PFPeA high group suggests that PFPeA exposure may alter leukocyte dynamics associated with physiological stress responses in largemouth bass. PFPeA, along with other PFAS compounds, may influence an individual’s ability to acclimatize to additional environmental stressors. Our findings suggest that PFAS exposure may contribute to sustained physiological responses and disrupt physiological allostasis. Previous research supports this interpretation, as PFAS exposure has altered fish leukocyte counts (Guillette et al., 2020) and affected other physiological processes, including liver morphology (Piva et al., 2022) and thyroid function (Ask et al., 2021; Birgersson et al., 2021), across different species. Our study extends these findings by suggesting that PFPeA exposure may contribute to sustained NLR elevation following an additional environmental perturbation.

A decrease in NLR across the control, Cd, and PFPeA low groups suggests that a 5 ppt salinity increase may be an acute but recoverable perturbation for bass. This aligns with previous research showing that bass tolerate moderate salinity (5–10 ppt; Yi et al., 2021) and persist at levels below 8.7 ppt (Viadero et al., 2025). However, higher salinity regimes (~15 ppt) can be lethal for bass (Norris et al., 2010). Interestingly, we observed consistent declines in NLR across the control, Cd, and PFPeA low groups, suggesting no evidence that Cd or low-level PFPeA exposure altered post-salinity NLR trajectories relative to controls. Our results suggest that a moderate salinity increase represents a temporary physiological perturbation for largemouth bass under controlled laboratory conditions, although contaminant exposure may influence leukocyte responses following salinity change.

Potential mechanisms, limitations, and future directions

Although the direct mechanisms underlying our observations remain uncertain, several plausible pathways may explain the sustained NLR elevation observed in PFPeA-exposed bass. PFAS compounds have been linked to endocrine disruption, including altered thyroid and glucocorticoid signalling (Ask et al., 2021; Birgersson et al., 2021; Coperchini et al., 2021), immune modulation (Fang et al., 2013; Guillette et al., 2020), and oxidative stress (Piva et al., 2022). Because leukocyte redistribution is closely associated with endocrine and immune regulation, disruption of these pathways may contribute to altered NLR dynamics following PFPeA exposure. These mechanisms remain hypothetical in the context of our study, but provide biologically plausible explanations for our observed patterns.

NLRs are widely used physiological biomarkers associated with stress responses across vertebrate taxa (Davis et al., 2008; Goessling et al., 2015; Watson et al., 2020). One strength of NLR is that leukocyte profiles often remain informative during prolonged perturbations, when glucocorticoid concentrations may fluctuate, attenuate, or become more difficult to interpret over time (Davis et al., 2008; Goessling et al., 2015). Nevertheless, NLR represents only one component of an organism’s physiological response. Additional biomarkers, including cortisol, oxidative stress indicators, and other immune parameters, would provide a more comprehensive understanding of the physiological pathways influenced by contaminant exposure and environmental change.

Several limitations should be considered when interpreting our findings. First, our study involved relatively few individuals per treatment group and should therefore be viewed as an exploratory laboratory investigation aimed at identifying potential physiological responses, warranting further study rather than a definitive assessment. Second, the high PFPeA and Cd concentrations exceeded levels currently reported in natural aquatic systems. We intentionally included elevated concentrations to evaluate physiological responses across an order-of-magnitude scale, but future studies should investigate using finer-scale dosing increments and concentrations that reflect environmentally relevant conditions in greater detail. Additional work incorporating larger sample sizes, longer exposure durations, multiple physiological endpoints (e.g. endocrine, immunological, and metabolic), and environmentally realistic contaminant concentrations would further improve our understanding of xenobiotic influences on physiological biomarkers and help clarify the mechanistic basis of these responses.

Implications from xenobiotic–stress relationships

Our findings have broad implications for understanding how contaminants affect vertebrate physiological biomarkers and the health of aquatic organisms, with relevance to conservation and ecological research. Leukocyte profiles, particularly NLRs, are widely used physiological biomarkers associated with stress responses across vertebrate taxa due to the conservative nature of the stress-related leukocyte response (Davis et al., 2008). Therefore, it is reasonable to suggest that PFPeA, and potentially other xenobiotics, including short-chain PFAS isomers, may alter leukocyte dynamics associated with physiological stress responses in various species.

Studies on mammals have reported that certain PFAS compounds may affect lymphocyte and neutrophil activity differently (Qazi et al., 2009), suggesting that contaminant-associated changes in leukocyte profiles may occur across diverse taxa. Combined with our findings, this evidence indicates that contaminant exposure may extend beyond endocrine disruption to include immune variation.

In the context of conservation physiology, our results highlight an important but often overlooked challenge: contaminant exposure may influence the interpretation of physiological biomarkers used to assess environmental disturbance. Natural populations are increasingly exposed to complex cocktails of exogenous pollutants (Kurwadkar et al., 2022), yet physiological biomarkers are frequently interpreted without considering potential contaminant-associated effects. If xenobiotic exposure alters biomarker responses independently of the environmental perturbations under investigation, researchers and managers may draw inaccurate conclusions regarding organismal condition, environmental stress, or ecosystem health. Clarifying the mechanistic connections underlying xenobiotic interactions with organisms is essential for interpreting physiological indicators and strengthening conservation and management decisions in increasingly altered ecosystems.

Acknowledgements

We thank Gary Vitrano and the Louisiana Department of Wildlife and Fisheries for collecting, transporting, and donating the fish used herein. We thank the Southeastern Louisiana University Vertebrate Museum for supplying resources that made this study possible. The use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the author’s employers.

Contributor Information

Anthony Ryan Johnson, Center for Environmental Research, Department of Biological Sciences, Southeastern Louisiana University, 808 North Pine Street, Hammond, LA 70401, USA.

Tyler Steven Coleman, Center for Environmental Research, Department of Biological Sciences, Southeastern Louisiana University, 808 North Pine Street, Hammond, LA 70401, USA.

Jasmine B Nasser, Center for Environmental Research, Department of Biological Sciences, Southeastern Louisiana University, 808 North Pine Street, Hammond, LA 70401, USA.

Maggie McGreal, Center for Environmental Research, Department of Biological Sciences, Southeastern Louisiana University, 808 North Pine Street, Hammond, LA 70401, USA.

Kyle R Piller, Center for Environmental Research, Department of Biological Sciences, Southeastern Louisiana University, 808 North Pine Street, Hammond, LA 70401, USA.

Christopher M Murray, Center for Environmental Research, Department of Biological Sciences, Southeastern Louisiana University, 808 North Pine Street, Hammond, LA 70401, USA.

Author contributions

A.R.J.: conceptualization, data curation, methodology, formal analysis, and writing—original draft, review and editing. T.S.C.: conceptualization, data curation, methodology, formal analysis, and writing—review and editing. J.B.N.: conceptualization, data curation, methodology, and writing—original draft. M.M.: conceptualization, methodology, and writing—original draft. K.R.P.: methodology, and writing—review and editing. C.M.M.: conceptualization, methodology, and writing—review and editing.

Conflicts of interest

The authors declare no conflicts of interest or competing interests.

Funding

Our work was supported by the Schlieder Endowed Professorship (to C.M.M. and K.R.P.) and Southeastern Louisiana University’s Center for Environmental Research and Department of Biological Sciences. Our research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Data availability

The data and code supporting this study’s findings, following the standards set out by Jenkins et al. (2023), are openly available on GitHub: https://github.com/tscoleman3/bass_stress_pfas_cd_aquaculture.

References

  1. Aerts  J, Metz  JR, Ampe  B, Decostere  A, Flik  G, De Saeger  S (2015) Scales tell a story on the stress history of fish. PLoS One  10: e0123411. 10.1371/journal.pone.0123411. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Ali  H, Khan  E, Ilahi  I (2019) Environmental chemistry and ecotoxicology of hazardous heavy metals: environmental persistence, toxicity, and bioaccumulation. J Chem  2019: 1–14. 10.1155/2019/6730305. [DOI] [Google Scholar]
  3. Anderson  RO, Neumann  RM (1996) Length, weight, and associated structural indices. In BR  Murphy, DW  Willis, eds, Fisheries Techniques, Ed2nd. American Fisheries Society, Bethesda, Maryland, USA, pp. 447–482. [Google Scholar]
  4. ANZECC (2000) Australian and New Zealand guidelines for fresh and marine water quality. Australian and New Zealand Environment and Conservation Council and Agriculture and Resource Management Council of Australia and New Zealand, Canberra  1: 1–314. [Google Scholar]
  5. Ask  AV, Jenssen  BM, Tartu  S, Angelier  F, Chastel  O, Gabrielsen  GW (2021) Per- and polyfluoroalkyl substances are positively associated with thyroid hormones in an arctic seabird. Environ Toxicol Chem  40: 820–831. 10.1002/etc.4978. [DOI] [PubMed] [Google Scholar]
  6. Atli  G, Canli  M (2010) Response of antioxidant system of freshwater fish Oreochromis niloticus to acute and chronic metal (Cd, Cu, Cr, Zn, Fe) exposures. Ecotoxicol Environ Saf  73: 1884–1889. 10.1016/j.ecoenv.2010.09.005. [DOI] [PubMed] [Google Scholar]
  7. Baker  MR, Gobush  KS, Vynne  CH (2013) Review of factors influencing stress hormones in fish and wildlife. J Nat Conserv  21: 309–318. 10.1016/j.jnc.2013.03.003. [DOI] [Google Scholar]
  8. Barlow  PM, Reichard  EG (2010) Saltwater intrusion in coastal regions of North America. Hydrgeol J  18: 247–260. 10.1007/s10040-009-0514-3. [DOI] [Google Scholar]
  9. Barton  BA (2002) Stress in fishes: a diversity of responses with particular reference to changes in circulating corticosteroids. Integr Comp Biol  42: 517–525. 10.1093/icb/42.3.517. [DOI] [PubMed] [Google Scholar]
  10. Bera  T, Kumar  SV, Devi  MS, Kumar  V, Behera  BK, Das  BK (2022) Effect of heavy metals in fish reproduction: a review. J Environ Biol  43: 631–642. 10.22438/jeb/43/5/MRN-4042. [DOI] [Google Scholar]
  11. Bhattachan  A, Jurjonas  MD, Morris  PR, Taillie  PJ, Smart  LS, Emanuel  RE, Seekamp  EL (2019) Linking residential saltwater intrusion risk perceptions to physical exposure of climate change impacts in rural coastal communities of North Carolina. Nat Hazards  97: 1277–1295. 10.1007/s11069-019-03706-0. [DOI] [Google Scholar]
  12. Birgersson  L, Jouve  J, Jönsson  E, Asker  N, Andreasson  F, Golovko  O, Ahrens  L, Sturve  J (2021) Thyroid function and immune status in perch (Perca fluviatilis) from lakes contaminated with PFASs or PCBs. Ecotoxicol Environ Saf  222: 112495. 10.1016/j.ecoenv.2021.112495. [DOI] [PubMed] [Google Scholar]
  13. Boeuf  G, Payan  P (2001) How should salinity influence fish growth?  Comp Biochem Physiol C Toxicol Pharmacol  130: 411–423. 10.1016/S1532-0456(01)00268-X. [DOI] [PubMed] [Google Scholar]
  14. Brendel  S, Fetter  É, Staude  C, Vierke  L, Biegel-Engler  A (2018) Short-chain perfluoroalkyl acids: environmental concerns and a regulatory strategy under REACH. Environ Sci Eur  30: 9. 10.1186/s12302-018-0134-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Brosset  P, Cooke  SJ, Schull  Q, Trenkel  VM, Soudant  P, Lebigre  C (2021) Physiological biomarkers and fisheries management. Rev Fish Biol Fish  31: 797–819. 10.1007/s11160-021-09677-5. [DOI] [Google Scholar]
  16. Cai  Y, Yin  Y, Yueru  L, Guan  L, Zhang  P, Qin  Y, Wang  Y, Yuehong  L (2020) Cadmium exposure affects growth performance, energy metabolism, and neuropeptide expression in Carassius auratus gibelio. Fish Physiol Biochem  46: 187–197. 10.1007/s10695-019-00709-3. [DOI] [PubMed] [Google Scholar]
  17. Cao  X, Guo  Q, Liu  W (2024) Research on the patterns of seawater intrusion in coastal aquifers induced by sea level rise under the influence of multiple factors. Water  16: 3457. 10.3390/w16233457. [DOI] [Google Scholar]
  18. Chambers  WS, Hopkins  JG, Richards  SM (2021) A review of per- and polyfluorinated alkyl substance impairment of reproduction. Front Toxicol  3: 732436. 10.3389/ftox.2021.732436. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Coleman  TS, Eckelbecker  RW, Carlson  AK, DeVries  DR, Wright  RA, Staton  BA, Parker  SW, Chittam  CR, Lovell  RG, Catalano  MJ (2024) Evaluation of shoreline rotenone application to control largemouth bass recruitment in small impoundments. N Am J Fish Manag  44: 57–69. 10.1002/nafm.10953. [DOI] [Google Scholar]
  20. Cooke  SJ, Blumstein  DT, Buchholz  R, Caro  T, Fernandez-Juricic  E, Franklin  CE, Metcalfe  J, O’Connor  CM, St. Clair  CC, Sutherland  WJ  et al. (2014) Physiology, behavior, and conservation. Physiol Biochem Zool  87: 1–14. 10.1086/671165. [DOI] [PubMed] [Google Scholar]
  21. Cooke  SJ, Sack  L, Franklin  CE, Farrell  AP, Beardall  J, Wikelski  M, Chown  SL (2013) What is conservation physiology? Perspectives on an increasingly integrated and essential science. Conserv Physiol  1: cot001–cot001. 10.1093/conphys/cot001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Coperchini  F, Croce  L, Ricci  G, Magri  F, Rotondi  M, Imbriani  M, Chiovato  L (2021) Thyroid disrupting effects of old and new generation PFAS. Front Endocrinol  11: 612320. 10.3389/fendo.2020.612320. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Coperchini  F, Teliti  M, Greco  A, Croce  L, Rotondi  M (2024) Per-polyfluoroalkyl substances (PFAS) as thyroid disruptors: is there evidence for multi-transgenerational effects?  Expert Rev Endocrinol Metab  19: 307–315. 10.1080/17446651.2024.2351885. [DOI] [PubMed] [Google Scholar]
  24. Cornelius Ruhs  E, Becker  DJ, Oakey  SJ, Ogunsina  O, Fenton  MB, Simmons  NB, Martin  LB, Downs  CJ (2021) Body size affects immune cell proportions in birds and non-volant mammals, but not bats. J Exp Biol  224: jeb241109. 10.1242/jeb.241109. [DOI] [PubMed] [Google Scholar]
  25. Corrêa  SADS, Abessa  DMDS, Santos  LGD, Da Silva  EB, Seriani  R (2017) Differential blood counting in fish as a non-destructive biomarker of water contamination exposure. Toxicol Environ Chem  99: 482–491. 10.1080/02772248.2016.1189554. [DOI] [Google Scholar]
  26. Correia  AT, Rebelo  D, Marques  J, Nunes  B (2019) Effects of the chronic exposure to cerium dioxide nanoparticles in Oncorhynchus mykiss: assessment of oxidative stress, neurotoxicity and histological alterations. Environ Toxicol Pharmacol  68: 27–36. 10.1016/j.etap.2019.02.012. [DOI] [PubMed] [Google Scholar]
  27. Cossa  D (1988) Cadmium in Mytilus spp.: worldwide survey and relationship between seawater and mussel content. Mar Environ Res  26: 265–284. 10.1016/0141-1136(88)90352-2. [DOI] [Google Scholar]
  28. Costello  E, Rock  S, Stratakis  N, Eckel  SP, Walker  DI, Valvi  D, Cserbik  D, Jenkins  T, Xanthakos  SA, Kohli  R  et al. (2022) Exposure to per- and polyfluoroalkyl substances and markers of liver injury: a systematic review and meta-analysis. Environ Health Perspect  130: 046001. 10.1289/EHP10092. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Croteau  M-N, Luoma  SN, Stewart  AR (2005) Trophic transfer of metals along freshwater food webs: evidence of cadmium biomagnification in nature. Limnol Oceanogr  50: 1511–1519. 10.4319/lo.2005.50.5.1511. [DOI] [Google Scholar]
  30. Davis  AK (2005) Effect of handling time and repeated sampling on avian white blood cell counts. J Field Ornithol  76: 334–338. 10.1648/0273-8570-76.4.334. [DOI] [Google Scholar]
  31. Davis  AK, Maney  DL, Maerz  JC (2008) The use of leukocyte profiles to measure stress in vertebrates: a review for ecologists. Funct Ecol  22: 760–772. 10.1111/j.1365-2435.2008.01467.x. [DOI] [Google Scholar]
  32. Delignette-Muller  ML, Dutang  C (2015) Fitdistrplus: an R package for fitting distributions. J Stat Softw  64: 1–34. 10.18637/jss.v064.i04. [DOI] [Google Scholar]
  33. Downs  CJ, Dochtermann  NA, Ball  R, Klasing  KC, Martin  LB (2020) The effects of body mass on immune cell concentrations of mammals. Am Nat  195: 107–114. 10.1086/706235. [DOI] [PubMed] [Google Scholar]
  34. Edo  GI, Samuel  PO, Oloni  GO, Ezekiel  GO, Ikpekoro  VO, Obasohan  P, Ongulu  J, Otunuya  CF, Opiti  AR, Ajakaye  RS  et al. (2024) Environmental persistence, bioaccumulation, and ecotoxicology of heavy metals. Chem Ecol  40: 322–349. 10.1080/02757540.2024.2306839. [DOI] [Google Scholar]
  35. Everds  NE, Snyder  PW, Bailey  KL, Bolon  B, Creasy  DM, Foley  GL, Rosol  TJ, Sellers  T (2013) Interpreting stress responses during routine toxicity studies: a review of the biology, impact, and assessment. Toxicol Pathol  41: 560–614. 10.1177/0192623312466452. [DOI] [PubMed] [Google Scholar]
  36. Fang  C, Huang  Q, Ye  T, Chen  Y, Liu  L, Kang  M, Lin  Y, Shen  H, Dong  S (2013) Embryonic exposure to PFOS induces immunosuppression in the fish larvae of marine medaka. Ecotoxicol Environ Saf  92: 104–111. 10.1016/j.ecoenv.2013.03.005. [DOI] [PubMed] [Google Scholar]
  37. Fang  Q, Yuan  M, Sun  Z, Xue  Y, Chong  C-M, Wang  X (2026) Temporal effects of perfluorononanoic acid (PFNA) exposure on metabolic disorders and gut-liver axis injury in large yellow croaker (Larimichthys crocea). Environ Res  288: 123211. 10.1016/j.envres.2025.123211. [DOI] [PubMed] [Google Scholar]
  38. Feder  ME (1987) New Directions in Ecological Physiology. Cambridge University Press, New York, NY. [Google Scholar]
  39. Gaines  LGT (2023) Historical and current usage of per- and polyfluoroalkyl substances (PFAS): a literature review. Am J Ind Med  66: 353–378. 10.1002/ajim.23362. [DOI] [PubMed] [Google Scholar]
  40. Gill  TS, Pant  JC (1985) Erythrocytic and leukocytic responses to cadmium poisoning in a freshwater fish, Puntius conchonius ham. Environ Res  36: 327–337. 10.1016/0013-9351(85)90028-3. [DOI] [PubMed] [Google Scholar]
  41. Goessling  JM, Kennedy  H, Mendonça  MT, Wilson  AE (2015) A meta-analysis of plasma corticosterone and heterophil : lymphocyte ratios—is there conservation of physiological stress responses over time?  Funct Ecol  29: 1189–1196. 10.1111/1365-2435.12442. [DOI] [Google Scholar]
  42. Guillette  TC, McCord  J, Guillette  M, Polera  ME, Rachels  KT, Morgeson  C, Kotlarz  N, Knappe  DRU, Reading  BJ, Strynar  M  et al. (2020) Elevated levels of per- and polyfluoroalkyl substances in Cape Fear River Striped Bass (Morone saxatilis) are associated with biomarkers of altered immune and liver function. Environ Int  136: 105358. 10.1016/j.envint.2019.105358. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Hanson  KC, Cooke  SJ (2009) Nutritional condition and physiology of paternal care in two congeneric species of black bass (Micropterus spp.) relative to stage of offspring development. J Comp Physiol B  179: 253–266. 10.1007/s00360-008-0309-1. [DOI] [PubMed] [Google Scholar]
  44. Hertika  AMS, Arfiati  D, Lusiana  ED, Putra  RB (2022) Effect of environmental factors on blood counts of Gambusia affinis caught at brantas river watershed, Indonesia. F1000Res  10: 1169. 10.12688/f1000research.74117.2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Hertika  AMS, Musa  M, Amron  K, Putra  RBDS, Alfarisi  MA, Putra  AFR, Halimah  MF, Wijanata  IBP (2025) Analysis of fish hematological profiles as bioindicators of water pollution in fish conservation areas, East Java, Indonesia. Water Environ Res  97: e70126. 10.1002/wer.70126. [DOI] [PubMed] [Google Scholar]
  46. Hontela  A, Rasmussen  JB, Audet  C, Chevalier  G (1992) Impaired cortisol stress response in fish from environments polluted by PAHs, PCBs, and mercury. Arch Environ Contam Toxicol  22: 278–283. 10.1007/BF00212086. [DOI] [PubMed] [Google Scholar]
  47. Houwen  B (2002) Blood film preparation and staining procedures. Clin Lab Med  22: 1–14. 10.1016/S0272-2712(03)00064-7. [DOI] [PubMed] [Google Scholar]
  48. Hu  F, Yin  L, Dong  F, Zheng  M, Zhao  Y, Fu  S, Zhang  W, Chen  X (2021) Effects of long-term cadmium exposure on growth, antioxidant defense and DNA methylation in juvenile Nile tilapia (Oreochromis niloticus). Aquat Toxicol  241: 106014. 10.1016/j.aquatox.2021.106014. [DOI] [PubMed] [Google Scholar]
  49. Jaffer  NS, Rabee  AM, Al-Chalabi  SMM (2017) Biochemical and hematological parameters and histological alterations in fish Cyprinus carpio L. as biomarkers for water pollution with chlorpyrifos. Hum Ecol Risk Assess  23: 605–616. 10.1080/10807039.2016.1261626. [DOI] [Google Scholar]
  50. Javed  M, Usmani  N (2019) An overview of the adverse effects of heavy metal contamination on fish health. Proc Natl Acad Sci, India, Sect B Biol Sci  89: 389–403. 10.1007/s40011-017-0875-7. [DOI] [Google Scholar]
  51. Jenkins  GB, Beckerman  AP, Bellard  C, Benítez-López  A, Ellison  AM, Foote  CG, Hufton  AL, Lashley  MA, Lortie  CJ, Ma  Z  et al. (2023) Reproducibility in ecology and evolution: minimum standards for data and code. Ecol Evol  13: e9961. 10.1002/ece3.9961. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Jezierska  B, Ługowska  K, Witeska  M (2009) The effects of heavy metals on embryonic development of fish (a review). Fish Physiol Biochem  35: 625–640. 10.1007/s10695-008-9284-4. [DOI] [PubMed] [Google Scholar]
  53. Jezierska  B, Witeska  M (2006) The metal uptake and accumulation in fish living in polluted waters. In I Twardowska, HE Allen, MM Häggblom, S Stefaniak, eds, Soil and Water Pollution Monitoring, Protection and Remediation. Springer Netherlands, Dordrecht, pp. 107–114. [Google Scholar]
  54. Kahlon  SK, Sharma  G, Julka  JM, Kumar  A, Sharma  S, Stadler  FJ (2018) Impact of heavy metals and nanoparticles on aquatic biota. Environ Chem Lett  16: 919–946. 10.1007/s10311-018-0737-4. [DOI] [Google Scholar]
  55. Kern  EM, Langerhans  RB (2019) Urbanization alters swimming performance of a stream fish. Front Ecol Evol  6: 229. 10.3389/fevo.2018.00229. [DOI] [Google Scholar]
  56. Kieffer  JD, Cooke  SJ (2009) Physiology and organismal performance of centrarchids. In S Cooke, DP Philipp, eds, Centrarchid Fishes: Diversity, Biology, and Conservation. Blackwell Publishing Ltd., West Sussex, UK. [Google Scholar]
  57. Kim  D, Taylor  AT, Near  TJ (2022) Phylogenomics and species delimitation of the economically important Black Basses (Micropterus). Sci Rep  12: 9113. 10.1038/s41598-022-11743-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Kurwadkar  S, Dane  J, Kanel  SR, Nadagouda  MN, Cawdrey  RW, Ambade  B, Struckhoff  GC, Wilkin  R (2022) Per- and polyfluoroalkyl substances in water and wastewater: a critical review of their global occurrence and distribution. Sci Total Environ  809: 151003. 10.1016/j.scitotenv.2021.151003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Lacépède  BGE (1802) Histoire Naturelle Des Poissons V 4. Plassan, Paris. [Google Scholar]
  60. Lawrence  MJ, Raby  GD, Teffer  AK, Jeffries  KM, Danylchuk  AJ, Eliason  EJ, Hasler  CT, Clark  TD, Cooke  SJ (2020) Best practices for non-lethal blood sampling of fish via the caudal vasculature. J Fish Biol  97: 4–15. 10.1111/jfb.14339. [DOI] [PubMed] [Google Scholar]
  61. Lescord  GL, Kidd  KA, De Silva  AO, Williamson  M, Spencer  C, Wang  X, Muir  DCG (2015) Perfluorinated and polyfluorinated compounds in lake food webs from the Canadian High Arctic. Environ Sci Technol  49: 2694–2702. 10.1021/es5048649. [DOI] [PubMed] [Google Scholar]
  62. Lesueur  CA (1822) Descriptions of the five new species of the genus Cichla of Cuvier. J Acad Nat Sci Phila  2: 214–221. [Google Scholar]
  63. Lewis  RW, Andrus  AK, Arroyo  J, Brescia  S, Botham  PA, Corvaro  M, Daston  GP, Hofmann  T, Rodriguez  C, Sewell  F  et al. (2024) Considerations for the development of guidance on dose level selection for developmental and reproductive toxicity studies. RTP  148: 105585. 10.1016/j.yrtph.2024.105585. [DOI] [PubMed] [Google Scholar]
  64. Liu  Y, Chen  Q, Li  Y, Bi  L, Jin  L, Peng  R (2022) Toxic effects of cadmium on fish. Toxics  10: 622. 10.3390/toxics10100622. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Ludsin  SA, DeVries  DR (1997) First-year recruitment of largemouth bass: the interdependency of early life stages. Ecol Appl  7: 1024–1038. 10.1890/1051-0761(1997)007[1024:FYROLB]2.0.CO;2. [DOI] [Google Scholar]
  66. Mallett  MC, Thiem  JD, Butler  GL, Kennard  MJ (2024) A systematic review of approaches to assess fish health responses to anthropogenic threats in freshwater ecosystems. Conserv Physiol  12: coae022. 10.1093/conphys/coae022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. McGillycuddy  M, Warton  DI, Popovic  G, Bolker  BM (2025) Parsimoniously fitting large multivariate random effects in glmmTMB. J Stat Softw  112: 1–19. 10.18637/jss.v112.i01. [DOI] [Google Scholar]
  68. Murray  CM, Easter  M, Merchant  M, Cooper  A, Crother  BI (2013) Can reproductive allometry assess population marginality in crocodilians? A comparative analysis of Gulf Coast American Alligator (Alligator mississippiensis) populations. Ichthyol Herpetol  2013: 268–276. 10.1643/CH-11-136. [DOI] [Google Scholar]
  69. Mussabek  D, Söderman  A, Imura  T, Persson  KM, Nakagawa  K, Ahrens  L, Berndtsson  R (2023) PFAS in the drinking water source: analysis of the contamination levels, origin, and emission rates. Water  15: 137. 10.3390/w15010137. [DOI] [Google Scholar]
  70. Naidenko  SV, Alshinetskiy  MV (2020) Size matters: zoo data analysis shows that the white blood cell ratio differs between large and small felids. Animals  10: 940. 10.3390/ani10060940. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Nayak  S, Sahoo  G, Das  II, Mohanty  AK, Kumar  R, Sahoo  L, Sundaray  JK (2023) Poly- and perfluoroalkyl substances (PFAS): do they matter to aquatic ecosystems?  Toxics  11: 543. 10.3390/toxics11060543. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Neumann  RM, Allen  MS (2007) Chapter 9: Size structure. In CS  Guy, ML  Brown, eds, Analysis and Interpretation of Freshwater Fisheries Data. American Fisheries Society, Bethesda, USA, pp. 375–421. [Google Scholar]
  73. Norris  AJ, DeVries  DR, Wright  RA (2010) Coastal estuaries as habitat for a freshwater fish species: exploring population-level effects of salinity on largemouth bass. Trans Am Fish Soc  139: 610–625. 10.1577/T09-135.1. [DOI] [Google Scholar]
  74. Pan  C-G, Ying  G-G, Zhao  J-L, Liu  Y-S, Jiang  Y-X, Zhang  Q-Q (2014) Spatiotemporal distribution and mass loadings of perfluoroalkyl substances in the Yangtze River of China. Sci Total Environ  493: 580–587. 10.1016/j.scitotenv.2014.06.033. [DOI] [PubMed] [Google Scholar]
  75. Pankhurst  N, Van Der Kraak  G (1997) Effects of stress on reproduction and growth of fish. In GK Iwama, AD Pickering, JP Sumpter, CB Schreck, eds, Fish Stress and Health in Aquaculture, Cambridge University Press, New York, NY, pp. 73–93. [Google Scholar]
  76. Pinheiro  JPS, Windsor  FM, Wilson  RW, Tyler  CR (2021) Global variation in freshwater physico-chemistry and its influence on chemical toxicity in aquatic wildlife. Biol Rev  96: 1528–1546. 10.1111/brv.12711. [DOI] [PubMed] [Google Scholar]
  77. Piva  E, Schumann  S, Dotteschini  S, Brocca  G, Radaelli  G, Marion  A, Irato  P, Bertotto  D, Santovito  G (2022) Antioxidant responses induced by PFAS exposure in freshwater fish in the Veneto region. Antioxidants (Basel)  11: 1115. 10.3390/antiox11061115. [DOI] [PMC free article] [PubMed] [Google Scholar]
  78. Posit team (2025) RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA. [Google Scholar]
  79. Qazi  MR, Bogdanska  J, Butenhoff  JL, Nelson  BD, DePierre  JW, Abedi-Valugerdi  M (2009) High-dose, short-term exposure of mice to perfluorooctanesulfonate (PFOS) or perfluorooctanoate (PFOA) affects the number of circulating neutrophils differently, but enhances the inflammatory responses of macrophages to lipopolysaccharide (LPS) in a similar fashion. Toxicology  262: 207–214. 10.1016/j.tox.2009.06.010. [DOI] [PubMed] [Google Scholar]
  80. R Core Team (2025) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. [Google Scholar]
  81. Ritter  L, Solomon  K, Sibley  P, Hall  K, Keen  P, Mattu  G, Linton  B (2002) Sources, pathways, and relative risks of contaminants in surface water and groundwater: a perspective prepared for the Walkerton inquiry. J Toxicol Environ Health  65: 1–142. [DOI] [PubMed] [Google Scholar]
  82. Rodgers  EM, Poletto  JB, Gomez Isaza  DF, Van Eenennaam  JP, Connon  RE, Todgham  AE, Seesholtz  A, Heublein  JC, Cech  JJ, Kelly  JT  et al. (2019) Integrating physiological data with the conservation and management of fishes: a meta-analytical review using the threatened green sturgeon (Acipenser medirostris). Conserv Physiol  7: coz035. 10.1093/conphys/coz035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  83. Schreck  CB (2010) Stress and fish reproduction: the roles of allostasis and hormesis. Gen Comp Endocrinol  165: 549–556. 10.1016/j.ygcen.2009.07.004. [DOI] [PubMed] [Google Scholar]
  84. Schumann  S, Negrato  E, Piva  E, Pietropoli  E, Bonato  M, Irato  P, Marion  A, Santovito  G, Bertotto  D (2024) Cortisol levels reveal species-specific stress condition in fish from PFAS polluted rivers. Chemosphere  363: 142925. 10.1016/j.chemosphere.2024.142925. [DOI] [PubMed] [Google Scholar]
  85. Schymanski  EL, Zhang  J, Thiessen  PA, Chirsir  P, Kondic  T, Bolton  EE (2023) Per- and polyfluoroalkyl substances (PFAS) in PubChem: 7 million and growing. Environ Sci Technol  57: 16918–16928. 10.1021/acs.est.3c04855. [DOI] [PMC free article] [PubMed] [Google Scholar]
  86. Seriani  R, Abessa  DMS, Moreira  LB, Cabrera  JPG, Sanches  JQ, Silva  CLS, Amorim  FA, Rivero  DHRF, Silva  FL, Fitorra  LS  et al. (2015a) In vitro mucus transportability, cytogenotoxicity, and hematological changes as non-destructive physiological biomarkers in fish chronically exposed to metals. Ecotoxicol Environ Saf  112: 162–168. 10.1016/j.ecoenv.2014.11.003. [DOI] [PubMed] [Google Scholar]
  87. Seriani  R, França  JG, Lombardi  JV, Brito  JM, Ranzani-Paiva  MJT (2015b) Hematological changes and cytogenotoxicity in the tilapia Oreochromis niloticus caused by sub-chronic exposures to mercury and selenium. Fish Physiol Biochem  41: 311–322. 10.1007/s10695-014-9984-x. [DOI] [PubMed] [Google Scholar]
  88. Shahjahan  M, Taslima  K, Rahman  MS, Al-Emran  M, Alam  SI, Faggio  C (2022) Effects of heavy metals on fish physiology – a review. Chemosphere  300: 134519. 10.1016/j.chemosphere.2022.134519. [DOI] [PubMed] [Google Scholar]
  89. Shahjahan  M, Uddin  MH, Bain  V, Haque  MM (2018) Increased water temperature altered hemato-biochemical parameters and structure of peripheral erythrocytes in striped catfish Pangasianodon hypophthalmus. Fish Physiol Biochem  44: 1309–1318. 10.1007/s10695-018-0522-0. [DOI] [PubMed] [Google Scholar]
  90. Sharma  M, Kant  R, Sharma  AK, Sharma  AK (2025) Exploring the impact of heavy metals toxicity in the aquatic ecosystem. Int J Energy Water Resour  9: 267–280. 10.1007/s42108-024-00284-1. [DOI] [Google Scholar]
  91. Sloman  KA, Wilson  RW (2005) Anthropogenic impacts upon behaviour and physiology. Fish Physiol  24: 413–468. 10.1016/S1546-5098(05)24010-4. [DOI] [Google Scholar]
  92. Song  R, Yao  X, Jing  F, Yang  W, Wu  J, Zhang  H, Zhang  P, Xie  Y, Pan  X, Zhao  L  et al. (2024) Effects of five lipid sources on growth, hematological parameters, immunity and muscle quality in juvenile largemouth bass (Micropterus salmoides). Animals  14: 781. 10.3390/ani14050781. [DOI] [PMC free article] [PubMed] [Google Scholar]
  93. Starnes  HM, Rock  KD, Jackson  TW, Belcher  SM (2022) A critical review and meta-analysis of impacts of per- and polyfluorinated substances on the brain and behavior. Front Toxicol  4: 881584. 10.3389/ftox.2022.881584. [DOI] [PMC free article] [PubMed] [Google Scholar]
  94. Steenland  K, Winquist  A (2021) PFAS and cancer, a scoping review of the epidemiologic evidence. Environ Res  194: 110690. 10.1016/j.envres.2020.110690. [DOI] [PMC free article] [PubMed] [Google Scholar]
  95. Taylor  AT, Long  JM, Tringali  MD, Barthel  BL (2019) Conservation of black bass diversity: an emerging management paradigm. Fisheries  44: 20–36. 10.1002/fsh.10187. [DOI] [Google Scholar]
  96. Tringali  MD, Long  JM, Birdsong  TW, Allen  MS (eds) (2015) Black Bass Diversity: Multidisciplinary Science for Conservation. American Fisheries Society, Bethesda, Maryland, USA. [Google Scholar]
  97. Tully  K, Gedan  K, Epanchin-Niell  R, Strong  A, Bernhardt  ES, BenDor  T, Mitchell  M, Kominoski  J, Jordan  TE, Neubauer  SC  et al. (2019) The invisible flood: the chemistry, ecology, and social implications of coastal saltwater intrusion. Bioscience  69: 368–378. 10.1093/biosci/biz027. [DOI] [Google Scholar]
  98. Velasco  AM, Pérez-Ruzafa  A, Martínez-Paz  JM, Marcos  C (2018) Ecosystem services and main environmental risks in a coastal lagoon (mar Menor, Murcia, SE Spain): the public perception. J Nat Conserv  43: 180–189. 10.1016/j.jnc.2017.11.002. [DOI] [Google Scholar]
  99. Viadero  NM, Massie  JA, Eggenberger  CW, James  WR, Boucek  RE, Rezek  RJ, Santos  RO, Rehage  JS (2025) Between a dry marsh and a salty place: estuarine habitat suitability for a freshwater fish (Florida bass) and implications for ecosystem restoration and climate change. Estuaries Coast  48: 124. 10.1007/s12237-025-01561-w. [DOI] [Google Scholar]
  100. Walsh  HL, Blazer  VS, Lord  E, Hurley  ST, LeBlanc  DR (2025) Occurrence and tissue distribution of per- and polyfluoroalkyl substances (PFAS) in fishes from waterbodies with point and non-point sources in Massachusetts, USA. Aquat Toxicol  287: 107499. 10.1016/j.aquatox.2025.107499. [DOI] [PubMed] [Google Scholar]
  101. Wang  D, Cao  Q, Zhu  W, Hu  Y, Zhang  X, Yin  S, Wang  T (2019) Individual and combined effects of salinity and lipopolysaccharides on the immune response of juvenile Takifugu fasciatus. Fish Physiol Biochem  45: 965–976. 10.1007/s10695-018-0607-9. [DOI] [PubMed] [Google Scholar]
  102. Wang  Z, Cousins  IT, Scheringer  M, Hungerbühler  K (2013) Fluorinated alternatives to long-chain perfluoroalkyl carboxylic acids (PFCAs), perfluoroalkane sulfonic acids (PFSAs) and their potential precursors. Environ Int  60: 242–248. 10.1016/j.envint.2013.08.021. [DOI] [PubMed] [Google Scholar]
  103. Watson  JW, Hyder  K, Boyd  R, Thorpe  R, Weltersbach  MS, Ferter  K, Cooke  SJ, Roy  S, Sibly  R (2020) Assessing the sublethal impacts of anthropogenic stressors on fish: an energy-budget approach. Fish Fish  21: 1034–1045. 10.1111/faf.12487. [DOI] [Google Scholar]
  104. Wikelski  M, Cooke  SJ (2006) Conservation physiology. Trends Ecol Evol  21: 38–46. 10.1016/j.tree.2005.10.018. [DOI] [PubMed] [Google Scholar]
  105. Wilson  RW, Bergman  HL, Wood  CM (1994) Metabolic costs and physiological consequences of acclimation to aluminum in juvenile rainbow trout (Oncorhynchus mykiss) gill morphology, swimming performance, and aerobic scope. Can J Fish Aquat Sci  51: 536–544. 10.1139/f94-056. [DOI] [Google Scholar]
  106. Witeska  M, Kondera  E, Bojarski  B (2023) Hematological and hematopoietic analysis in fish toxicology—a review. Animals (Basel)  13: 2625. 10.3390/ani13162625. [DOI] [PMC free article] [PubMed] [Google Scholar]
  107. Wu  X, Cobbina  SJ, Mao  G, Xu  H, Zhang  Z, Yang  L (2016) A review of toxicity and mechanisms of individual and mixtures of heavy metals in the environment. Environ Sci Pollut Res  23: 8244–8259. 10.1007/s11356-016-6333-x. [DOI] [PubMed] [Google Scholar]
  108. Xie  Y, Shao  X, Zhang  P, Zhang  H, Yu  J, Yao  X, Fu  Y, Wei  J, Wu  C (2024) High starch induces hematological variations, metabolic changes, oxidative stress, inflammatory responses, and histopathological lesions in largemouth bass (Micropterus salmoides). Metabolites  14: 236. 10.3390/metabo14040236. [DOI] [PMC free article] [PubMed] [Google Scholar]
  109. Yi  H, Chen  X, Liu  S, Han  L, Liang  J, Su  Y, Lai  H, Bi  S, Liu  X, Zhang  Y  et al. (2021) Growth, osmoregulatory and hypothalamic–pituitary–somatotropic (HPS) axis response of the juvenile largemouth bass (Micropterus salmoides), reared under different salinities. Aquacult Rep  20: 100727. 10.1016/j.aqrep.2021.100727. [DOI] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data and code supporting this study’s findings, following the standards set out by Jenkins et al. (2023), are openly available on GitHub: https://github.com/tscoleman3/bass_stress_pfas_cd_aquaculture.

Articles from Conservation Physiology are provided here courtesy of Oxford University Press

RESOURCES