Editors: | Kongoli F |
Publisher: | Flogen Star OUTREACH |
Publication Year: | 2014 |
Pages: | 528 pages |
ISBN: | 978-1-987820-09-6 |
ISSN: | 2291-1227 (Metals and Materials Processing in a Clean Environment Series) |
Effects of environmental chemical pollution can be observed at all levels of biological organization. At the population level, genetic structure and diversity may be affected by exposure to metal contamination. This study was conducted in Huautla, Morelos, Mexico in a mining district where the main contaminants are lead and arsenic. Peromyscus melanophrys is a small mammal species that inhabits Huautla mine tailings and has been considered as a sentinel species. Metal bioaccumulation levels were examined by inductively coupled plasma mass spectrometry and genetic analyses were performed using eight microsatellite loci in 100 P. melanophrys individuals from three mine tailings and two control sites. The effect of metal bioaccumulation levels on genetic parameters (population and individual genetic diversity, genetic structure) was analyzed. We found a tissue concentration gradient for each metal (Al, Pb, Cu, As, Cd) and for the bioaccumulation index. The highest values of genetic differentiation (FST = 0.412 and RST = 0.628) and the lowest number of migrants per generation were registered among the exposed populations (Nm=1.0A ± 0.1), compared to the control populations (FST = 0.099 and RST = 0.183; Nm=5.7A ± 1.3). Genetic distance analyses showed that the highest values of genetic distance were registered between the most exposed population and the control sites (0.0793). Moreover, a negative and significant relationship was detected between genetic diversity (He, IR) and each metal concentration and for the bioaccumulation index in P. melanophrys (He; r2= 0.88, P = 0.009; IR; = r2= 0.29, P=0.005). This study highlights that metal stress is a major factor affecting the distribution and genetic diversity levels of P. melanophrys populations living inside mine tailings. We suggest the use of genetic population changes at micro-geographical scales as a population level biomarker (biomarker of permanent effects)