# Evaluating trace elements as a conservation concern for Eurasian lynx (Lynx lynx) in Switzerland

Laurie Bedouet, Marie-Pierre Ryser-Degiorgis, Stéphanie Borel, Caroline

Amiot, Eve Afonso, Michaël Coeurdassier

► To cite this version:

Laurie Bedouet, Marie-Pierre Ryser-Degiorgis, Stéphanie Borel, Caroline Amiot, Eve Afonso, et al. Evaluating trace elements as a conservation concern for Eurasian lynx (Lynx lynx) in Switzerland. Ecotoxicology and Environmental Safety, 2025, 298, pp.118300. 10.1016/j.ecoenv.2025.118300. hal-05068062

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# Evaluating trace elements as a conservation concern for Eurasian lynx (*Lynx lynx*) in Switzerland

Laurie Bedouet<sup>a, ID</sup>, Marie-Pierre Ryser-Degiorgis<sup>b</sup>, Stéphanie Borel<sup>b</sup>, Caroline Amiot<sup>a</sup>,
Eve Afonso<sup>a</sup>, Michael Coeurdassier<sup>a, * ID</sup>

ARTICLE INFO

Edited by Dr G Liu

Keywords:

Feline

Wildlife

Metal

Toxicity

Deficiency

Ecotoxicology

A B S T R A C T

The Eurasian lynx, an endangered species in Switzerland, faces major threats including traffic collisions, illegal killing, and low genetic diversity. However, the impact of trace element (TE) exposure on its conservation remains poorly understood. As a top predator primarily feeding on game species, this felid can be exposed to non-essential TEs, including lead and mercury, which can be toxic even at low concentrations. In addition, over-exposure to or deficiency of essential TEs such as copper or zinc can cause adverse health effects. To address this gap, we analysed liver samples from 122 individuals archived in the Swiss national health surveillance program by measuring the concentrations of eight TEs: four non-essential TEs (arsenic, cadmium, lead, and mercury) and four essential TEs (copper, iron, selenium, and zinc). Concentrations were consistent with those reported in other free-ranging *Lynx* populations and remained below toxicity thresholds reported for mammals, while also being above deficiency levels for essential TEs. They varied with age for some TEs, but not with sex, time or environmental variables. Additionally, we used a body condition score to examine the relationship between TE concentrations and Eurasian lynx health. Lower body condition scores were associated with higher concentrations of both non-essential and essential TEs, likely reflecting poor health affecting TE accumulation rather than a direct toxic effect. Overall, our study suggests that the current TE exposure does not significantly threaten Eurasian lynx populations in Switzerland, providing new insights for conservation efforts and long-term health monitoring.

# 1. Introduction

Chemical pollution is one of the five major drivers of biodiversity loss, alongside habitat destruction, overexploitation of natural resources, climate change and invasive alien species (IPBES, 2019; Groh et al., 2022). The threat is likely to increase as the current trend indicates a chemical intensification, with global production expected to triple by 2050 compared to 2010 (Persson et al., 2022). Because of the pervasive and persistent nature of many anthropogenic chemicals, there are no "pristine" ecosystems on Earth unaffected by these pollutants (Sigmund et al., 2023). Among them, trace elements (TEs), especially non-essential metals and metalloids (e.g., arsenic (As), cadmium (Cd), lead (Pb), mercury (Hg)), received much attention as they have no known physiological function, they are non-biodegradable and can be harmful even at low concentrations (Wu et al., 2016). Essential TEs (e.g., copper (Cu), iron (Fe), selenium (Se), zinc (Zn)) are necessary for the growth,

development and physiology of organisms and must be supplied through the diet. While their concentrations are typically regulated by homeostasis, adverse health effects can occur if levels fall outside the required physiological ranges, leading to either toxicity (when concentrations are too high) or deficiency (when they are too low) (Kalisińska, 2019).

Among species exposed to TEs, carnivorous mammals are of particular concern. Due to their position as top predators in food webs and their long lifespan, they are particularly susceptible to some TEs through the consumption of contaminated prey and biomagnification (Gall et al., 2015; Ziętara et al., 2019). Among TEs at risk for these species, the effects of Hg have been largely reported in aquatic ecosystems (Scheuhammer et al., 2015; Ali et al., 2019) and to a lesser extent, in terrestrial ones (Gnamuś et al. 2000). In Florida panthers (*Puma concolor coryi*) for example, increased consumption of raccoons led to elevated levels of toxic Hg, which, combined with low genetic diversity, contributed to physiological impairments, reduced reproductive

<footnote><sup>a</sup> Laboratory Chrono-environnement, University Marie et Louis Pasteur, UMR 6249, 16 route de Gray, Besançon 25000, France</footnote>

<footnote><sup>b</sup> Institute for Fish and Wildlife Health, Vetsuisse Faculty, University of Bern, Postfach, Länggassstrasse 122, Bern 3001, Switzerland</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: michael.coeurdassier@univ-fcomte.fr (M. Coeurdassier).</footnote>
success, and some mortality cases (Roelke et al., 1993; Barron et al., 2004). Moreover, by feeding on game species, some of them can be more exposed to Pb through the ingestion of prey containing Pb ammunition (Burco et al., 2012; North et al., 2015) or by being the target of non-lethal shots in case of conflict with humans, leading to embedded gunshot in tissues (Pérez-López et al., 2016; Chiverton et al., 2022).

The Eurasian lynx (*Lynx lynx*) is a carnivorous felid inhabiting forested mountain ranges of Europe and Asia (von Arx, 2020). By the mid-20th century, the species had disappeared from much of Western Europe due to human persecution, habitat degradation and prey depletion (Breitenmoser, 1998). However, shifting in public attitudes, improved wildlife-management policies, prey recovery, and habitat restoration have facilitated its return. In Switzerland, reintroductions occurred from the 1970s to 2000s (Linnell et al., 2009), yet despite these efforts, the population remains endangered. Major threats include traffic collisions, illegal killing, and low genetic diversity (von Arx et al., 2021; Arlettaz et al., 2021; KORA Foundation, 2022). In addition, cryptic mortality causes such as infectious disease or intoxication may exacerbate population declines by affecting survival and reproduction (Schmidt-Posthaus et al., 2002; Millán and Becker, 2021). For several decades, Switzerland has implemented a health surveillance program to monitor Eurasian lynx populations. This program involves examining both live and deceased individuals, with a primary focus on pathological analysis, while toxicological analysis is conducted only when poisoning is suspected. Additionally, the archiving of multiple organ samples provides valuable opportunities for future research on this rare species (Ryser-Degiorgis et al., 2021).

Despite this, knowledge of the exposure of Eurasian lynx to TEs remains scarce. There are only a few studies available for the species in Slovenia (Gnamuš et al. 2000), Norway (Ottemo, 2009), and Croatia (Bilandzić et al. 2012; Lazarus et al., 2017). Additional insights come from studies on related species, such as the Iberian lynx (*Lynx pardinus*; Millán et al., 2008) and the bobcat (*Lynx rufus*; Thomason et al., 2016). However, the often small sample sizes of these studies restrict robust conclusions and limit the ability to account for confounding variables such as age and sex. Given the influence of individual traits on the exposure, absorption and metabolism of TEs (Burger et al., 2007), identifying the factors that make some individuals more susceptible to a particular chemical is critical to protecting and maintaining healthy wildlife populations.

In the present study, we measured the concentrations of TEs in the liver of Eurasian lynx in Switzerland using archived samples from the national health surveillance program. Among other organs, the liver plays a key role in the regulation, bioaccumulation and detoxification of trace elements, making it a widely used tissue in ecotoxicological studies, with most data derived from hepatic tissue (Kalisińska, 2019). We focused on eight elements (i.e., As, Cd, Pb, Hg, Cu, Fe, Se, and Zn) selected based on their relative health importance in terms of essentiality and/or toxicity. Measured concentrations were compared with concentrations published for free-ranging populations of other species of *Lynx sp.* and Felids, and with critical thresholds available for mammals. As a top predator that feeds primarily on game species, such as roe deer (*Capreolus capreolus*) and chamois (*Rupicapra rupicapra*) (Breitenmoser and Haller, 1993; Jobin et al., 2000), and as a target of illegal killing (Arlettaz et al., 2021), we hypothesised that Pb and Hg toxicity may be of particular concern to the Eurasian lynx populations in Switzerland. Moreover, we investigated whether variations in the measured concentrations were related to different variables, including time, age, sex and anthropogenic activities. We also used a body condition score to explore the relationship between TE concentrations and Eurasian lynx health, hypothesising that a low body condition score would be associated with high concentrations of non-essential TEs and/or low concentrations of essential TEs. Finally, we discussed whether TEs could represent an overlooked threat to the conservation of Eurasian lynx, aiming to contribute to their long-term protection.

# 2. Materials and methods

## 2.1. Sample collection and individual traits

Liver samples were collected from 122 carcasses of Eurasian lynx found throughout Switzerland (Fig. 1) from 2014 to 2022 (distribution of samples over the years is provided in Supplementary materials, Table S1), and autopsied at the Institute for Fish and Wildlife Health (Vetsuisse Faculty, University of Bern, Switzerland). Location and date of discovery were reported for every individual. The principal causes of death identified were road collisions (n = 60) followed by culling, euthanasia or death of individuals in poor health condition (n = 39). Other causes of death included trauma of natural (n = 2) or unknown cause (n = 5) or induced by the capture (n = 1), poaching suspicion (n = 4), legal culling following predation on livestock (n = 4), euthanasia after the mother was killed (n = 3), infection with the Feline Immunodeficiency Virus (FIV; n = 1), one case of a 5-month-old lynx shot by an official for displaying abnormal behaviour (n = 1) and undeterminable cause (n = 2). During necropsy, individuals were sexed (65 females and 57 males), and their age was estimated mainly based on dentition, tooth wear and body size, defining three classes: juveniles (< 11 months, n = 78), subadults (between 11 and 24 months, n = 22) and adults (> 24 months, n = 22; Ryser-Degiorgis et al., 2021). Except for four individuals, a radiography was systematically performed, and the presence or absence of radiopaque ammunition fragments was noted without determining the exact composition of the fragment. The necropsy protocol also included the allocation of a body condition score (BCS) based on the general appearance of the carcass, muscle mass and the amount of subcutaneous and visceral fat. The BCS ranged from 1 representing "very poor condition" (cachexia or emaciated) to 5, representing "very good condition", using half-unit increments (Ryser-Degiorgis et al., 2021).

## 2.2. Measurement of TE concentrations in liver tissues

Approximately one gram of fresh liver samples was freeze-dried until constant mass. Samples were weighed again after freeze-drying. The mean ± SD of the wet weight (ww) and dry weight (dw) were 1.18 ± 0.08 g and 0.32 ± 0.05 g, respectively, yielding a ww/dw ratio of 3.7. Acid digestion was then performed using dissolution in 7 mL of nitric acid 67–69 % (Fisher Scientific, OPTIMA™ quality) in a DigiPrep mineralization system (SCP Sciences, Courtaboeuf, France) for 4h30. After digestion, the tubes were filled to 50 mL with ultra-pure water

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Map of Switzerland showing the approximate locations of individual Eurasian lynx carcasses (*Lynx lynx*; n = 122). Their age is indicated by colours (blue for juveniles, yellow for subadults and violet for adults) and their sex is represented by shape (triangle for females, circle for males).</figcaption></figure>
(Millipore Synergy system, Molsheim, France). Finally, they were
filtered and diluted 10 times with ultra-pure water.

Concentrations of the eight TEs (As, Cd, Pb, Hg, Cu, Fe, Se, Zn) were measured by Inductively Coupled Plasma Mass Spectrometry (ICP-MS, ThermoFisher Scientific ICAP RQ Model, Thermo Fisher Scientific, Courtaboeuf, France). Blanks (acid + ultra-pure water) and Certified Reference Materials (CRM) TORT-3 lobster hepatopancreas (National Research Council, Canada) with known concentrations of TEs were prepared and analysed simultaneously with the samples to check the quality and accuracy of the analyses. According to Zhu and Alexandratos (2007), gold (III) chloride was added at a final concentration of 250 µg/L to the rinsing and carrier solutions to limit the memory effect, especially for Hg; the Hg was potentially deposited in the ICP-MS, complexed by Au, and then released. Limits of detection (LOD), blank concentrations and recovery percentages are available in Supplementary materials (Table S2). Concentrations above their corresponding limit of detection were corrected for contamination by deducting the concentration measured in the blank samples. When average recoveries for the CRM ranged between 85 % and 115 %, concentrations were considered acceptable. Otherwise, concentrations were recalculated using the recovery percentage value of the element concerned. All results are expressed in µg/g on a dry weight (dw) basis.

Concentrations of 11 additional TEs (aluminium (Al), antimony (Sb), chromium (Cr), cobalt (Co), manganese (Mn), molybdenum (Mo), nickel (Ni), strontium (Sr), thallium (Tl), tin (Sn), titanium (Ti)) were also measured. They are not analysed and discussed in this article, but they are reported in Supplementary materials (Table S3) for diffusion to scientific community. As there was no certified value in the CRM used for Al, Sb, Tl and Ti, and the value was only indicative for Co and Sn, the concentrations measured for these elements should be treated with caution.

## 2.3. Statistical analyses

All statistical analyses were computed with R version 4.2.1 (R Core Team, 2022). For TEs with concentrations below the LOD (i.e., As and Hg), we used left-censored data analysis methods described by Helsel (2012).

Descriptive statistics were reported both as mean and median to facilitate comparison with previously published concentrations. Depending on the data distribution, the arithmetic mean was given in the case of a Gaussian distribution while the geometric mean was calculated in the case of a log-normal distribution. For left-censored TEs, mean concentrations were estimated using the *EnvStats* R package (Millard, 2013). The method used was the robust regression on older statistics (rROS) because it is a semi-parametric method that uses the distribution hypothesis on censored data only (Helsel, 2012).

When testing correlations with generalized linear models, the normality of the residuals and homoscedasticity of variances were evaluated. If the assumptions were not met, the concentrations were log-transformed. In cases where the assumptions remained unmet even after log transformation, a permutation test was used to assess the correlations.

### 2.3.1. Difference in TE concentrations according to time and individual variables

We tested whether TE concentrations varied according to time (year of the individual's discovery) and individual variables (age and sex). Non-essential and essential TEs were considered separately due to their distinct biological roles. Following the ordinal methods described by Helsel (2012), TE concentrations were ranked, with those below the LOD being attributed the same lowest rank. To identify temporal trends in TE concentrations, we performed a seriation test (Mantel test) by examining the correlation between the dissimilarity matrix of the years and the dissimilarity matrix of the ranked TE concentrations, using the *vegan* R package (Oksanen et al., 2022). In parallel, to examine

variations in TE concentrations according to individual variables, we conducted a permutational multivariate analysis of variance (PERMANOVA) with the ranked concentrations as response variables, and age and sex as explanatory variables, using the same R package *vegan*. Homogeneity of within-group variances was also tested with this package. In the case where within-group variances were heterogeneous, a biplot of the values was created, including 95 % confidence ellipses. If the confidence ellipses did not or only partially overlap, the centroids were considered significantly different (Anderson and Walsh, 2013). Individual variables showing a significant effect were then selected for univariate analyses.

To account for the potential effect of individual location on TE concentrations, linear models were fitted with significant individual variables and GPS coordinates as explanatory variables. These models were tested for spatial autocorrelation using the *DHARMA* R package (Hartig and Lohse, 2022). If spatial autocorrelation was significant, linear models were re-fitted using the *spaMM* R package (Rousset and Ferdy, 2014). Tukey tests were performed as post-hoc multiple comparisons to identify which levels of a variable were significantly different.

For TEs with left-censored concentrations, a binary variable was created indicating whether the concentration measured was below the LOD (variable set as “TRUE”) or not (variable set as “FALSE”). Linear regression models were performed using the *NADA2* R package (Julian and Helsel, 2023). Spatial autocorrelation was tested on the residuals of the linear models using the *ape* R package (Paradis and Schliep, 2019). Significant differences between the levels of a variable were identified by Tukey tests. If spatial autocorrelation was significant, a permutation test was used.

### 2.3.2. Relationship between environmental variables and TE concentrations

For a subset of TEs, we investigated the relationship between liver concentrations and environmental variables using the European CORINE Land Cover (CLC) 2018 dataset. Considering the wide variety of TE pollution sources, we chose to focus on five land-use variables (CLC code reported in brackets hereafter), to narrow the scope of our study: urban areas (11) for Cd, Pb, and Hg; road (122, 123 and 124) for Pb; industry (121) for As and Hg; arable lands (21) for Cd; and vineyard (221) for Cu. Additionally, for Pb, the hunting pressure was approximated by the number of authorized hunters by Swiss cantons per year (Office fédéral de l'environnement, 2022). For the individuals straddling the French border, the number of hunters from relevant départements, i.e. Haut-Rhin and Doubs, was also used (Fédération Départementale des Chasseurs du Haut-Rhin, 2019; Fédération des chasseurs du Doubs, 2024). The percentage of each land-use variable listed above, as well as the five main types of land-use of the CLC (i.e., artificial surfaces (1), agricultural areas (2), forest and semi-natural areas (3), wetlands (4), water bodies (5)) was calculated within a circular buffer around the GPS location where the individual was found. The radius of the buffer was chosen according to home range estimations from Ripari et al. (2022) based on telemetry data. The radius differed between sex and the population to which the individuals were supposed to belong (i.e., Alpine vs. Jura; details in Supplementary materials, Table S4). We applied the same radius to juveniles as to adult females from the same population since they mostly live with their mothers at this age. Subadults were considered the same as adults, and individuals from the NWS population (North-West of Switzerland) were considered the same as individuals from the Alpine population. The buffer area defined for each individual was subsequently referred to as the 'surrounding area'. The number of hunters per individual was calculated proportionally to the surface area of the canton and département included in the surrounding area. The calculations were done on QGIS version 3.32.2 (QGIS.org, 2023). Linear models were then fitted with the percentage of the land-use variable as an explanatory variable. Individual variables and GPS coordinates were also included as explanatory variables only when previous analyses showed a significant effect of these variables on the relevant TE
concentrations. For As, due to data censoring and significant spatial autocorrelation, the percentage of industrial land was transformed into a binary variable (presence/absence), and a permutation test was used to compare the means between the two groups. We did not explore the relationship between urban areas and As concentrations, as transforming the variable into a binary format resulted in only one individual with no urban areas, making the analysis unfeasible.

### 2.3.3. Relationship between body condition and TE concentrations

To reduce the complexity of the data and to identify the main concentration gradients, we synthesised TE concentrations separately in a single variable for non-essential and essential TEs, using the first axis of a principal component analysis (PCA1 non-essential; PCA1 essential) of the ranked concentrations. These variables were then fitted in linear models as explanatory variables, along with the significant individual variables and the cause of death (i.e., road collision (n = 60), starvation (n = 30) or diverse (n = 32)) to control for their confounding effect. Interaction between the cause of death and PCA1 score was tested. BCS was used as a health indicator and included in the models as the response variable. Spatial autocorrelation was checked as described previously and Tukey tests were performed as post-hoc multiple comparisons.

## 3. Results

### 3.1. TE concentrations in Eurasian lynx liver

Liver concentrations measured for the eight TEs are presented in

<caption>**Table 1**</caption>

Descriptive statistics of the eight trace element concentrations (µg/g dry weight) measured in Eurasian lynx liver from Switzerland. Only the median was given for the different age classes.

<table><thead><tr><th rowspan="2">Trace element</th><th>All individuals (n = 122)</th><th>All individuals (n = 122)</th><th>Juvenile (n = 78)</th><th>Subadult (n = 22)</th><th>Adult (n = 22)</th></tr><tr><th>Mean ± SD (95 % confidence interval)</th><th>Median (min - max)</th><th></th><th></th><th></th></tr></thead><tbody><tr><td>As<sup>a</sup></td><td>0.03 ± 0.04 (0.02 - 0.04)<sup>b</sup></td><td>0.02 (&lt; LOD - 0.34)</td><td>0.02 (&lt; LOD - 0.34)</td><td>0.02 (&lt; LOD - 0.20)</td><td>0.01 (&lt; LOD - 0.07)</td></tr><tr><td>Cd</td><td>0.09<sup>c</sup> ± 2.6 (0.08 - 0.11)</td><td>0.09 (0.01 - 1.10)</td><td>0.06 (0.01 - 1.10)</td><td>0.14 (0.05 - 0.26)</td><td>0.27 (0.09 - 0.81)</td></tr><tr><td>Pb</td><td>0.27<sup>c</sup> ± 3.9 (0.21 - 0.34)</td><td>0.31 (0.01 - 5.76)</td><td>0.51 (0.03 - 5.76)</td><td>0.07 (0.01 - 3.32)</td><td>0.10 (0.01 - 1.16)</td></tr><tr><td>Hg<sup>a</sup></td><td>0.14 ± 0.31 (0.09 - 0.20)<sup>b</sup></td><td>0.04 (&lt; LOD - 2.43)</td><td>0.03 (&lt; LOD - 2.43)</td><td>0.05 (&lt; LOD - 1.14)</td><td>0.03 (&lt; LOD - 0.16)</td></tr><tr><td>Cu</td><td>42.5<sup>c</sup> ± 2.1 (37.4 - 48.3)</td><td>40.1 (9.10 - 205.5)</td><td>62.0 (13.0 - 205.5)</td><td>23.9 (9.43 - 73.9)</td><td>21.8 (9.09 - 74.6)</td></tr><tr><td>Fe</td><td>765.0<sup>c</sup> ± 1.8 (690.0 - 848.0)</td><td>716.0 (214.7 - 3149.2)</td><td>806.1 (214.7 - 3149.2)</td><td>667.7 (287.2 - 1773.9)</td><td>592.1 (286.6 - 1540.5)</td></tr><tr><td>Se</td><td>1.56<sup>d</sup> ± 0.34 (1.50 - 1.62)</td><td>1.58 (0.82 - 2.54)</td><td>1.51 (0.82 - 2.29)</td><td>1.61 (1.10 - 2.54)</td><td>1.63 (0.92 - 2.30)</td></tr><tr><td>Zn</td><td>245.7<sup>c</sup> ± 1.9 (218.4 - 275.6)</td><td>256.9 (49.4 - 1223.2)</td><td>322.8 (93.8 - 991.2)</td><td>129.7 (80.6 - 1223.2)</td><td>150.4 (49.4 - 599.0)</td></tr></tbody></table>

**Table 1.** The mean concentrations, listed from highest to lowest, were as follows: Fe > Zn > Cu > Se > Pb > Hg > Cd > As. Essential TEs were 10–10,000 times more abundant than non-essential TEs. Concentrations below the detection limit were found in 12 % of samples for As and 37 % for Hg.

Among the 118 Eurasian lynx that underwent radiographic examination, ammunition fragments were found in 32 carcasses. Out of them, 27 were legally shot and three were found dead due to suspected poaching. Thus, the presence of ammunition fragments in the carcass was unexpected in only two individuals, which were both killed in a road collision. Their liver Pb concentrations were 0.12 and 1.38 µg/g dw, respectively, placing these values in the first and fourth quartiles of the concentrations measured in our sample.

### 3.2. Difference in TE concentrations according to time and individual variables

Liver concentrations of both non-essential and essential TEs showed no significant temporal trend over the sampling years (R = -0.01, P = 0.751, permutations = 999 for non-essential; R = -0.01, P = 0.803, permutations = 999 for essential). While significant differences were found across age classes (PERMANOVA; F = 19.22, df = 2 and 119, P = 0.001 for non-essential; F = 14.41, df = 2 and 119, P = 0.001 for essential), no variation was observed between sexes (F = 0.08, df = 1 and 119, P = 0.988 for non-essential; F = 0.33, df = 1 and 119, P = 0.797 for essential), leading us to include only age in further analyses.

Spatial autocorrelation was detected and accounted for in the subsequent analyses for five TEs: As (0.11, P < 0.001), Cd (0.09, P = 0.003), Pb (Moran's I = 0.09, P = 0.003), Cu (0.19, P < 0.001), and Zn (0.07, P = 0.026), while no spatial autocorrelation was detected for Hg (0.02, P = 0.343), Fe (0.02, P = 0.484), and Se (0.02, P = 0.334).

Comparing the age classes, juveniles had higher concentrations of Pb (F = 41.56, df = 2 and 62, P < 0.001), Cu (F = 39.82, df = 2 and 114, P < 0.001), and Zn (F = 21.13, df = 2 and 114, P < 0.001) than sub-adults and adults. In contrast, Hg concentrations were significantly higher in subadults compared to juveniles and adults (χ² = 8.73, df = 2, P = 0.01). Adults had higher Cd concentrations than subadults, and subadults had higher concentrations than juveniles (permutation test, P = 0.001). No significant age-related differences were found for As (permutation test, P = 0.32), Fe (F = 2.33, df = 2 and 119, P = 0.101), and Se (F = 2.47, df = 2 and 119, P = 0.089) (Table 1).

### 3.3. Relationship between environmental variables and TE concentrations

The surrounding areas of individuals were predominantly covered by forest and semi-natural areas (mean: 48.5 %, range: 10.6 – 96.2), closely followed by agricultural areas (mean: 39.4 %, range: 3.0 – 74.8), then artificial areas (mean: 7.3 %, range: 0 – 19.8), water bodies (mean: 4.4 %, range: 0 – 43.3) and wetlands (mean: 0.13 %, range: 0 – 2.4). Concerning the five selected land-use variables, the mean percentages were as follows, in descending order: 18.9 % (0 – 62.7) for arable lands, 6.4 % (0 – 17.6) for urban areas, 0.6 % (0 – 3.8) for industry, 0.5 % for vineyards (0 – 5.8) and 0.04 % (0 – 0.4) for roads. Additionally, the mean number (min-max) of hunters per surrounding area was 104 (0 – 416).

Univariate analyses did not reveal any significant relationship between TE concentrations and land-use or other environmental variables tested. Specifically, no significant associations were found between Pb and urban areas (F = 1.29, df = 1 and 107, P = 0.26), hunting (F = 1.39, df = 1 and 23, P = 0.25), and road (F = 0.95, df = 1 and 115, P = 0.33); Hg and urban areas (z = 0.91, P = 0.36), and industry (z = 0.97, P = 0.33); Cd and urban areas (F = 0.69, df = 1 and 115, P = 0.41), and arable lands (F = 0.01, df = 1 and 118, P = 0.92), As and industry (permutation test, P = 0.45), and Cu and vineyards (F = 0.59, df = 1 and 78, P = 0.77).

<footnote><sup>a</sup> Trace element for which some individuals had concentrations below the limit of detection (LOD; left-censored data).</footnote>

<footnote><sup>b</sup> Mean, standard deviation (SD) and 95 % confidence interval calculated according to the data distribution (i.e., Gaussian or log-normal) using the functions from the EnvStats R package (Millard, 2013).</footnote>

<footnote><sup>c</sup> Geometric mean.</footnote>

<footnote><sup>d</sup> Arithmetic mean.</footnote>
### 3.4. Relationship between body condition and TE concentrations

The first axis of the PCA (PCA1 non-essential, PCA1 essential) explained 36 % and 57 % of the total variation in the non-essential and essential TE concentrations, respectively. The matrices of variable loadings are provided in Supplementary materials (Table S5). PCA1 score was interpreted as a gradient of TE concentrations, where negative values indicated low concentrations of TEs, while positive values corresponded to high concentrations. The BCS used as a health indicator had a mean value of 2.8 for juveniles and 3.8 for both subadults and adults.

For non-essential TEs, a significant negative correlation was found between the BCS and PCA1 score, which was modulated by the age and an interaction between PCA1 score and the cause of death (F = 33.89, df = 7 and 114, P < 0.001) (Fig. 2a). Individuals that died of starvation had a lower BCS for a given PCA1 value compared to others, while those that died of diverse causes had a steeper decline in BCS. Additionally, juveniles had a lower BCS than adults for a given PCA1 value (Supplementary materials, Figure S1a).

For essential TEs, the BCS was also negatively correlated with PCA1 score, with this relationship being modulated by the cause of death (F = 45.97, df = 5 and 116, P < 0.001) (Fig. 2b, S1b). Individuals that died of starvation had the lowest BCS for a given PCA1 value compared to other causes of death.

### 4. Discussion

To date, this is the first published study on TE concentration data in Eurasian lynx with such a large sample size. For the eight TEs analysed, we found that the mean concentrations measured in Eurasian lynx from Switzerland were consistent with those reported for other Eurasian lynx populations or related species, including the Iberian lynx and bobcat (Table 2).

The physiological significance of such TE concentrations in wildlife remains challenging due to the lack of established thresholds values for free-ranging animals in the existing literature. Therefore, data were compared with ranges established for domestic animals, focusing on species within the same family (i.e. Felis catus, domestic cats) or other carnivores (i.e. Canis lupus familiaris, domestic dogs) (Table 3). For non-essential TEs, the concentrations measured in this study were far below toxicity thresholds reported for the above-mentioned domestic species, suggesting limited risk of adverse health effects. In particular, the maximum Pb concentration measured (5.76 µg/g dw) was seven times lower than the lowest toxicity threshold for felines (between 37 and 270 µg/g dw; WVDL, 2015). This value was also well below the

concentrations reported in two fatal poisoning cases in felines. After ingestion of Pb shot pellets, a free-ranging cougar in Oregon had a liver Pb concentration of 1391 µg/g dw (376 µg/g ww; Burco et al., 2012), while a captive cheetah with neurological signs had a liver Pb concentration of 63 µg/g dw (17 µg/g ww; North et al., 2015). These concentrations are 240 and 11 times higher than the maximum Pb concentration we measured in Eurasian lynx, respectively. Additionally, we identified two individuals with unexpected ammunition fragments embedded in their tissue, representing 2 % of the sample. While their composition was unknown, lead ammunition remains widely used in Switzerland (Ganz et al., 2018). However, their liver Pb concentrations were 30–300 times below the toxicity threshold for felines. Although it is acknowledged that illegal killing still represents a significant threat to the conservation of Eurasian lynx in Switzerland (Arlettaz et al., 2021), our results do not support the hypothesis that Pb diffusion from embedded ammunition fragments contributes to the intoxication of a significant part of the population, at least at the time-scale of our study. For the other non-essential TE of interest to top predators, Hg, the highest concentration we measured (2.43 µg/g dw) was 44 times lower than the lowest toxicity threshold for domestic cats (between 111 and 370 µg/g dw; Puls, 1994). For the other two non-essential TEs, As and Cd, the highest measured concentrations were 24 and 109 times lower than their respective toxicity threshold (Table 3). Combined with the liver concentrations published previously for different *Lynx* species (Table 2), the present results do not indicate that Eurasian lynx are overexposed to Pb, Hg, Cd and As. It is therefore reasonable to assume that these non-essential TEs are unlikely to pose a significant threat to the Eurasian lynx populations in Switzerland.

Although necessary for organisms, essential TEs can be toxic in high concentrations. While most of them were below toxicity thresholds reported for domestic animals (Table 3), six individuals exceeded the threshold for Fe for canine species (i.e., 1850 µg/g dw; WVDL, 2015) by up to 1.7 times. Excessive Fe can damage multiple organs, including the liver, heart, pancreas, thyroid, and central nervous system (Kalisinska, 2019). All six individuals were juveniles. Four were found dead or in poor health, one was euthanised after a road collision but was reported to be in good body condition, and the last, also in good condition, was euthanised with two siblings after their mother was killed. Interestingly, the siblings did not have elevated Fe concentrations. Except for the two individuals in good condition, while adverse health effects due to excessive Fe concentrations cannot be ruled out, their poor condition was probably more a consequence of weakness and starvation. Essential TEs can also cause adverse health effects in case of deficiencies. Only Cu exhibited concentrations below the proposed threshold for deficiency in domestic cats (88.8 µg/g dw; WVDL, 2015) in 98 Eurasian lynx (80 % of

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Correlation between body condition score (BCS) and (a) non-essential and (b) essential trace element (TE) concentrations in the liver of Eurasian lynx from Switzerland, grouped by cause of death (road collision in pink, starvation in green, and diverse in blue). TE concentrations are synthesised by the coordinates on the first axis of a principal component analysis (PCA1), with separate analyses for essential and non-essential TEs. For both, negative PCA1 values indicate low concentrations, while positive values indicate high concentrations. Lines represent the model fit for each cause of death category.</figcaption></figure>
<caption>**Table 2**</caption>

Summary of published mean trace element concentrations (µg/g dry weight) measured in the liver of *Lynx* species. Sample size and location were also reported for comparison purposes. All studies collected data opportunistically from free-ranging animals.

<table><thead><tr><th>Species</th><th>As</th><th>Cd</th><th>Pb</th><th>Hg</th><th>Cu</th><th>Fe</th><th>Se</th><th>Zn</th><th>Sample size</th><th>Location</th><th>Reference</th></tr></thead><tbody><tr><td>Eurasian lynx (Lynx lynx)</td><td>0.03<br>0.03<br>0.05<sup>a</sup></td><td>0.09<br>0.54<br>1.20<sup>a</sup></td><td>0.27<br>0.56<br>0.02<sup>a</sup></td><td>0.14<br>0.52<br>0.15<sup>a</sup></td><td>42.5<br>18.7<br>31.2<sup>a</sup></td><td>765<br>715<br>-</td><td>1.56<br>1.79<br>-</td><td>246<br>137<br>-</td><td>122<br>136<br>2</td><td>Switzerland<br>Norway<br>Croatia</td><td>This study<br>(Ottemo, 2009)<br>(Bilandžić et al. 2012)</td></tr><tr><td>Iberian lynx (Lynx pardinus)</td><td>0.05<sup>a</sup></td><td>0.03<sup>a</sup></td><td>1.32<sup>a</sup></td><td>0.04<sup>a</sup></td><td>32.6<sup>a</sup></td><td>60.3<sup>a</sup></td><td>0.81<sup>a</sup></td><td>254<sup>a</sup></td><td>1</td><td>Croatia</td><td>(Lazarus et al. 2017)</td></tr><tr><td>Bobcat (Lynx rufus)</td><td>nd,<br>0.04</td><td>0.12,<br>0.06</td><td>0.04,<br>0.25</td><td>0.23,<br>0.14</td><td>18.2,<br>35.4</td><td>-</td><td>1.54,<br>1.52</td><td>115,<br>153</td><td>3, 2</td><td>Spain (two different locations)</td><td>(Millán et al. 2008)</td></tr><tr><td></td><td>-</td><td>-</td><td>-</td><td>-</td><td>106<sup>b</sup></td><td>-</td><td>5<sup>b</sup></td><td>120<sup>b</sup></td><td>From<br>103–118</td><td>United States of America (four different locations)</td><td>(Thomason et al. 2016)</td></tr></tbody></table>

the sample). A study on captive cheetahs and lions linked Cu deficiency to neurological signs, with liver Cu concentrations ranging from 8.0 to 34.8 µg/g dw (2.2 and 9.4 µg/g ww; Kaiser et al., 2014). In the present study, 55 individuals (45%) had Cu concentrations lower than 34.8 µg/g dw, with the majority having died from road collision rather than starvation. While these results suggest that a significant proportion of the Eurasian lynx population in Switzerland may suffer from Cu deficiency, the mean Cu concentrations reported for Eurasian and Iberian lynx in previous studies were lower than those found in the current study, with no associated health problems reported (Table 2). This questions whether such relatively low Cu concentrations compared to domestic or captive animals can be interpreted as a deficiency or correspond to normal physiological levels for *Lynx* species. Other studies already pointed out that domestic or captive animals may have limited relevance in reflecting the real-world exposure of wildlife and predicting adverse health effects (Rodríguez-Estival and Mateo, 2019; Morrissey et al., 2023). In addition to our results, this reinforces the need for further research to determine normal ranges of TEs in free-ranging animals and to better understand the significance of the TE concentrations measured in their tissues.

Regarding the differences in TE concentrations associated with age, we found that they varied depending on the specific TE analysed. For non-essential TEs, no clear pattern emerged from the literature, except for Cd which tends to accumulate with age due to its low excretion rate and long biological half-life (Kalisińska, 2019). Higher liver Cd concentrations in old animals were commonly found in wildlife, including Eurasian lynx (present study; Ottemo, 2009), red foxes (*Vulpes vulpes*; Millán et al., 2008; Pérez-López et al., 2016), grey wolves (*Canis lupus*) and brown bears (*Ursus arctos*; Lazarus et al., 2017), and other free-ranging terrestrial mammals (Medvedev, 1999; Falandysz et al., 2005; Srebočan et al., 2012). One explanation for this accumulation of Cd with age in long-lived mammals is the increased expression of metallothionein genes and proteins, which protect organisms from metal toxicity, among other functions (Pabis et al., 2021). For Pb, the higher concentrations we found in juveniles compared to subadults and adults were also evidenced for grey wolves (Lazarus et al., 2017), but this difference remained unexplained by the authors. Furthermore, two studies indicated a contrasting trend for Pb in other carnivores, namely brown bears and red foxes, with older animals having higher concentrations. This pattern was attributed to Pb accumulation from environmental sources, throughout their lifespan (Pérez-López et al., 2016; Lazarus et al., 2017). Thus, the trend we evidenced for the Eurasian lynx in Switzerland strengthens the assumption that this population does not undergo chronic exposure to Pb from their environment. The higher Hg concentrations observed in subadults compared to juveniles and adults in the present study remain unexplained and warrant further investigation. For essential TEs, only Cu and Zn exhibited differences associated with age, with higher concentrations in juveniles. Similar results

were found in the Eurasian lynx (Ottemo, 2009) and other carnivores such as the golden jackal (*Canis aureus*; Farkas et al., 2021). In some species, including the domestic cat, young animals are born with a reserve of essential TEs, which is further alimented by increased intestinal absorption (Puls, 1994; Kalisińska, 2019). Although no concentration measured outranged any deficiency or toxicity thresholds, it appears that age is an important factor to consider when assessing the exposure of Eurasian lynx to TEs.

Even though ecological and metabolic differences between males and females may influence pollutant exposure and susceptibility (Burger et al., 2007), no differences were found between males and females for either non-essential or essential TEs. Similar results for bobcat and Eurasian lynx were found by Thomason et al. (2016) and Ottemo (2009), respectively. One explanation could be that gender-related differences remain hidden at low to moderate environmental exposure levels, and the concentrations of essential elements are maintained in a narrow range (i.e., homeostasis) (Beernaert et al., 2007). This is further supported by the lack of temporal trends in the years sampled, despite sampling spanning eight years.

Spatial autocorrelation was detected for several TEs, with the primary aim of statistically controlling for possible clustering of individuals with similar characteristics and isolating the true effects of the variables tested (i.e., individual and environmental variables). With this objective in mind, we simply used inverse distance weighted (IDW) interpolation in QGIS to map the concentrations of each TE concerned and found no substantial spatial pattern, suggesting that TE concentrations were not strongly clustered or influenced by local environmental factors (see example in Supplementary materials, Figure S2). As a more detailed spatial analysis was beyond the scope of this study, we chose to focus on a restricted list of land-use and anthropogenic variables (i.e., urban areas, industry, roads, arable lands, vineyard, hunting), known to be source of TEs. Our results indicated that none of them influenced TE concentrations in the Eurasian lynx liver. The lack of such correlations could be due to limited variation in certain environmental variables across the study area, as indicated by the low mean percentage of these variables in the individual's surrounding areas, or to other unmeasured confounding factors, such as dietary exposure. In contrast, for an urban-adapted species, the caracal (*Caracal caracal*), a similar approach using higher resolution data found that animals living in human-altered landscapes (i.e., urban areas, roads, vineyards) were more likely to be exposed to several toxic metals and metalloids (Parker et al., 2023). We did not observe similar trends between urban areas and concentrations of Cd, Pb, and Hg in Eurasian lynx. This species primarily inhabits forested areas, driven by prey availability and the avoidance of intensive human activity and settlements (Zimmermann and Breitenmoser, 2002; Basille et al., 2008). However, our estimates of landscape composition revealed that agricultural areas accounted for, on average, 39.5% of the Eurasian lynx surrounding areas in Switzerland. This observation aligns

<footnote><sup>a</sup> Expressed in wet weight in the original publication, approximated in dry weight using a factor of 3.7 as found in this study and recommended by Puls (1994); between 3.5 and 4 for most tissues).</footnote>

<footnote><sup>b</sup> Estimated from Thomason et al. (2016).</footnote>
<table><caption>**Table 3**
Published toxic, deficient and normal ranges of trace element concentrations (µg/g dry weight) in the liver of domestic carnivores. All values were expressed in wet weight in the original publication and approximated in dry weight using a factor of 3.7 as found in this study and recommended by Puls (1994); between 3.5 and 4 for most tissues).</caption><thead><tr><th>Species</th><th>As</th><th>Cd</th><th>Pb</th><th>Hg</th><th>Cu</th><th>Fe</th><th>Se</th><th>Zn</th><th>Reference</th></tr></thead><tbody><tr><td>Eurasian lynx (Lynx lynx)</td><td>0.03</td><td>0.09</td><td>0.27</td><td>0.14</td><td>42.5</td><td>765</td><td>1.56</td><td>245.7</td><td>This study</td></tr><tr><td>Domestic cat (Felis catus)</td><td>-</td><td>-</td><td>-</td><td>111-370</td><td>29.6-88.8</td><td>-</td><td>Normal range: 0.96-2.00</td><td>-</td><td>Puls. (1994)</td></tr><tr><td>Feline species</td><td>Normal range: &lt; 1.85</td><td>Normal range: &lt; 1.85</td><td>Normal range: &lt; 3.7</td><td>Normal range: 0.037-0.37</td><td>Deficient range: 29.6-88.8</td><td>Normal range:315-925</td><td>High range:7.40-17.0</td><td>Normal range:92.5-296</td><td>WVDL. (2015)</td></tr><tr><td>Domestic dog (Canis lupus familiaris)</td><td>Toxic range: &gt; 37.0</td><td>High range:3.7-25.9</td><td>Toxic range:185-740</td><td>-</td><td>Deficient range: 136.9-166.5</td><td>Deficient range: &lt; 74</td><td>Deficient range: &lt; 92.5</td><td>Deficient range:0.37-1.11</td><td>Puls. (1994)</td></tr><tr><td>Canine species</td><td>Toxic range: &gt; 37.0</td><td>Normal value:0.14</td><td>Toxic range:185-740</td><td>Normal range: &lt; 0.37</td><td>Deficient range: 1480-11100</td><td>Deficient range: &lt; 74</td><td>Deficient range: 74-222</td><td>Deficient range: &lt; 55.5</td><td>WVDL. (2015)</td></tr></tbody></table>

with growing evidence that, in a world dominated by human presence, Eurasian lynx can tolerate relatively high levels of anthropogenic activity, by adapting their behaviour (Basille et al., 2009; Bouyer et al., 2015). While no environmental variable was associated with increasing TE concentrations, the substantial presence of agricultural areas within the Eurasian lynx environment suggests potential exposure to various anthropogenic pollutants, including pesticides, which may pose greater risks to the species (Berny, 2007; Leighton et al., 2022).

The relationship between TE concentrations and body condition has rarely been investigated in felines. To our knowledge, only Thomason et al. (2016) investigated this relationship between Cu, Se, Ag and Zn concentrations in bobcat liver and body weight (as an indicator of body condition) and did not find any association. In the present study, the body condition was approximated by a score estimated by experienced veterinarians, based on the general appearance of the carcass and necropsy observations. The calculation of a body score index (e.g., based on body length and mass) was not possible as some of the carcasses were incomplete or in an advanced state of decomposition. In line with our hypothesis, we found that individuals with low BCS had higher concentrations of non-essential TEs. However, given the low concentrations of non-essential TEs compared to toxicity thresholds, it is unlikely that the observed low BCS is due to adverse health effects associated with these elements. Moreover, contrary to our initial hypothesis, individuals with low BCS also exhibited higher concentrations of essential TEs. For both non-essential and essential TEs, these relationships were modulated by the cause of death, but in all cases, individuals with low BCS had higher concentrations. The existing literature questions whether the observed relationships we found in Eurasian lynx result from TE concentrations affecting body condition, as initially presumed, or the reverse. Studies showed that essential TE concentrations increased in tissues of emaciated vertebrates, i.e., those with a low body condition. Proposed mechanisms include liver mass reduction due to catabolism in starving birds, leading to increased hepatic TE concentrations without altering total content (Roman et al., 2020). In reindeer, starvation leads to the catabolism of blood and lean tissue, releasing Fe further stored in the liver (Borch-Iohnsen and Nilssen, 1987). Additionally, histological changes in the intestinal epithelium induced by starvation may enhance nutrient absorption, including Fe, Cu, and Zn (Quartermann and Morrison, 1981). Although poorly studied for non-essential TEs, similar mechanisms could also explain increases in their concentrations. This highlights the need to interpret TE concentrations in the context of health and nutritional status.

## 5. Conclusion

This study provides the first comprehensive assessment of TE concentrations in the liver of Eurasian lynx in Switzerland. The concentrations do not appear to pose a significant threat to the species in Switzerland, as they were consistent with those reported in other free-ranging *Lynx* populations and were well below the toxicity thresholds proposed for domestic species, while also being above the deficiency levels for essential TEs. Liver concentrations varied with age for some TEs but not with sex, time, or environmental variables, possibly due to the relatively low level of pollution in the Eurasian lynx habitat. This suggests that age is important to consider when monitoring exposure of Eurasian lynx to TEs, while the influence of other variables should be investigated in similar studies conducted in other lynx populations. Furthermore, the observed relationship between body condition and TE concentrations is likely to be a result of poor health influencing TE internal concentrations rather than the reverse, as supported by the literature.

We acknowledge that the reliance on carcass sampling introduces certain limitations, such as potential biases related to cause of death, physiological state or geographical location at the time of collection (Ciucci et al., 2007). Nonetheless, such samples remain valuable for studying threatened and elusive species living at low density such as the
Eurasian lynx. Moreover, the absence of evidence of harmful effects from TEs in our samples suggests that similar outcomes are likely for live animals. Future studies should aim to establish species-specific thresholds for TE toxicity and deficiency in free-ranging carnivores, which would provide more precise tools for evaluating environmental risks. Expanding the scope to include pollutants such as pesticides or persistent chemicals is also critical, as they may present greater threats than TEs.

Overall, our results indicate that TE exposure is unlikely to be a threat to Eurasian lynx populations in Switzerland. However, continued monitoring is essential to detect emerging threats and ensure the species' long-term viability.

### CRediT authorship contribution statement

**Borel Stéphanie:** Writing – review & editing, Data curation, Conceptualization. **Amiot Caroline:** Resources. **Bedouet Laurie:** Writing – original draft, Formal analysis, Conceptualization. **Ryser-Degiorgis Marie-Pierre:** Data curation, Conceptualization. **Afonso Eve:** Writing – review & editing. **Coeurdassier Michael:** Writing – original draft, Supervision, Funding acquisition, Conceptualization.

### Declaration of Generative AI and AI-assisted technologies in the writing process

During the preparation of this work the authors used ChatGPT (OpenAI) in order to improve the readability of the manuscript. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.

### Funding

This work was supported by the Zone Atelier Arc Jurassien, the University of Franche-Comté (APR Chrysalide 2020) and the OSU Theta.

### 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.

### Acknowledgements

This article is dedicated to the memory of Marie-Pierre Ryser, who devoted a large part of her professional life to improving knowledge of the health of the lynx and its conservation. We gratefully thank Dennis Helsel and Paul Julian for answering our questions about the methods used to analyse left-censored data. We acknowledge the PEA²t platform of the Chrono-environnement laboratory which manages the equipment used to analyse trace elements in Eurasian lynx liver samples. We also thank Yuji Kato and Lise Pinault for helping with the spatial analyses. The photo of Eurasian lynx by Martin Mecnarowski (http://www.photomecan.eu/) and used in the graphical abstract is under licence CC BY-SA 3.0. Finally, we acknowledge Dominique Polito and Sarah Pierre for assisting us with the procedure for obtaining import permits for samples under the CITES convention.

### Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ecoenv.2025.118300.

### Data availability

Data will be available on request from the following link: https://doi.org/10.25666/DATAUBFC-2025-04-10.

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