## 2 Material and Methods
### Statistical Analyses and Risk Assessment  
Statistical analysis was carried out using SPSS v.15. Normality and homogeneity of variances of the data were checked through the Kolmogorov-Smirnov test and Levene's tests, respectively. The effect of the species on the analyzed traits was determined using the non-parametric Mann-Whitney test. Statistically significant differences were set at \(p<0.05\). Data were presented in terms of mean, median, standard deviations, as well as the minimum and maximum values, and they were expressed in milligrams per kilogram of wet weight (mg/kg ww).  
A probabilistic model (@Risk) was developed to estimate the intake levels for Co, Cr, Cu, Fe, Ni, Se, and Zn derived from the consumption of red deer and wild boar meat according to previous studies [21]. The developed model followed a probabilistic approach, where variables were described using probability distributions that were adjusted to the concentration data obtained in our study for each element and to the consumption data of red deer and wild boar meat in hunter-consumers. Data regarding the consumption of deer and wild boar meat, collected from hunters in southern Spain, were obtained from a previously published survey [8] and were expressed in kilograms per person per year (kg/person year), as detailed in Table 3.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Element**} & **LOD** & **LOQ** & \multicolumn{3}{c}{**Mussel Tissue ERM–CE278k**} \\  & **(mg/kg)** & **(mg/kg)** & **Certified** & **Found** & **Recovery (\%)** \\ \hline Co & 0.010 & 0.032 & 0.21 \({}^{*}\) & 0.18 \(\pm\) 0.01 & 86 \\ Cr & 0.006 & 0.022 & 0.73 \(\pm\) 0.22 & 0.77 \(\pm\) 0.12 & 105 \\ Cu & 0.078 & 0.260 & 5.98 \(\pm\) 0.27 & 6.38 \(\pm\) 0.66 & 107 \\ Fe & 1.092 & 3.624 & 161 \(\pm\) 8 & 174 \(\pm\) 7 & 108 \\ Ni & 0.023 & 0.077 & 0.69 \(\pm\) 0.15 & 5.00 \(\pm\) 0.21 & 102 \\ Se & 0.0001 & 0.001 & 1.62 \(\pm\) 0.12 & 1.55 \(\pm\) 0.23 & 97 \\ Zn & 1.203 & 4.841 & 71 \(\pm\) 4 & 74 \(\pm\) 4 & 104 \\ \hline \hline \end{tabular} \({}^{*}\)Indicative value.  
\end{table}
Table 2: Performance characteristics of the analytical method used to measure the content of Co, Cr, Cu, Fe, Ni, Se, and Zn.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{1}{c}{**Statistic**} & **Red Deer** & **Wild Boar** \\ \hline mean & 4.70 & 4.32 \\ standard deviation & 6.15 & 5.88 \\ median & 2.00 & 1.75 \\
95 percentile & 18.7 & 17.7 \\ minimum & 0.13 & 0.13 \\ maximum & 30.0 & 30.0 \\ \hline \hline \end{tabular} \({}^{*}\)Indicative value.  
\end{table}
Table 3: Consumption data of red deer and wild boar meat in hunter-consumers (kg/person per year).  
The exposure model did not incorporate a distinction between the variability and uncertainty of input variables, following a first-order model approach. The goodness-of-fit was evaluated using statistical tests, including the Kolmogorov-Smirnov and Chi-square tests, which offer insights into how effectively the fitted distribution characterizes the observed data. Visual analysis was also considered to evaluate the adequacy of the probability distributions with respect to the concentration data. The model was simulated using @Risk version 7.5 by Palisade@ software in Ithaca, NY, USA and executed with 10,000 iterations for each element using consistent seed values for the Random Number Generator, ensuring that the results are directly comparable.  
Game meat is mostly frozen and consumed throughout the year [8]. Then, the intake data obtained through this probabilistic model were divided by 52 weeks of the year, which accounts for one weekly meal. Intake data were compared to the Spanish DRI for adult population (>20 years of age) [22; 23] (see Table 4). In the case of Cr and Ni, tolerable intakes indicated by the European Food Safety Agency were considered.