Heavy metals are persistent, bioaccumulating pollutants, and assessing their exposure in biota requires indicators that capture spatial variability. This study evaluated fresh bat guano from different sites as a non-invasive matrix for characterising multi-element metal profiles and testing spatial differences among locations within species. Atomic Absorption Spectroscopy (AAS) technique was used to determine the concentrations of Mn, Fe, Ni, Cu, Zn, Cd, Hg, and Pb. Data were analysed after log10 transformation. Descriptive statistics and the Metal Pollution Index (MPI) were calculated, within-species location effects were tested using Welch ANOVA, and profile structure was further explored using hierarchical clustering, Spearman correlations and principal component analysis (PCA). MPI revealed marked spatial heterogeneity, ranging from 0.995 to 1.47, corresponding to an approximately threefold difference between the least and most affected sites. In the lesser horseshoe bat species, location significantly affected Mn, Fe, Ni, Cd, Hg, and Pb whereas in the greater mouse-eared bat the effect persisted for all analysed metals. The strongest positive correlations were Cu-Zn (ρ = 0.958) and Mn-Ni (ρ = 0.786). Together with MPI, fingerprint analysis and correlation structure, PCA supported the interpretation that fresh guano carries a structured spatial signal of metal mixtures and may therefore be useful in non-invasive environmental monitoring.
Świsłowski et al. (2026) studied this question.