Environmental and organ distribution of copper in Cervids from regions with different levels of human activity

Environmental Cu levels may be influenced by local human activity, whereas tissue accumulation also reflects organ-specific metabolism. This study compared Cu concentrations in environmental samples and red-deer (Cervus elaphus) tissues from two regions in Bulgaria.

Samples originated from hunting grounds, one form Northern Bulgaria, away from enterprises and mines, labeled as non-industrial and one from Southern Bulgarian in a mining region, treated as industrial. Composite samples form grass, bark, soil, water and sediment, n=6 for each, were analyzed by ICP-OES. Muscle, liver and kidney from 16 red deer (7 industrial and 9 non-industrial animals) were analyzed by ICP-MS.

Industrial soil, grass and bark contained more Cu than the non-industrial samples: 84.10 vs 0.477, 16.625 vs 0.0695 and 13.925 vs 0.230 mg kg-1 d.w. (p = 0.0381; effect size = 1.000). Sediment showed the same direction but did not reach significance after Holm’s correction (73.35 vs 0.358 mg kg-1 d.w.; p = 0.0571). Water showed the opposite pattern (0.0648 vs 3.000 mg L-1; p = 0.0238; effect size = -1.000).

No significant between-region differences were found in the organs. Mean concentrations (industrial vs non-industrial) were 2.137 vs 2.016 mg kg-1 w.w. in muscle, 19.761 vs 16.439 in liver and 5.486 vs 6.433 in kidney. Liver showed a large regional effect size (0.587), but the difference was not significant (p = 0.1647). Muscle, liver and kidney represented 7.47%, 72.01% and 20.52% of the relative tissue concentration in the industrial region and 8.64%, 59.86% and 31.50% in the non-industrial region. Within both regions, tissue concentrations differ (p < 0.001) and followed the order liver > kidney > muscle.

Regional Cu variation was more evident in environmental and vegetation samples than in tissues. Tissue data better reflected organ partitioning, particularly liver accumulation, supporting the use of environmental and biological indicators for Cu exposure assessment.