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Comparison of microbial and meiofaunal community analyses for determining impact of heavy metal contamination
Authors:Ellis R J  Neish B  Trett M W  Best J G  Weightman A J  Morgan P  Fry J C
Institution:Cardiff School of Biosciences, Cardiff University, PO Box 915, CF10 3TL, Cardiff, UK. r.ellis@ic.ac.uk
Abstract:The impact of long-term heavy metal contamination on soil communities was assessed by a number of methods. These included plate counts of culturable bacteria, community level physiological profiling (CLPP) by analysis of the utilization of multiple carbon sources in BIOLOG plates, community fatty acid methyl ester (C-FAME) profiling and dehydrogenase enzyme activity measurements. These approaches were complemented with microscopic assessments of the diversity of the nematode community. Samples from two sites with different histories of heavy-metal input were assessed. Major differences in microbial and meiofaunal parameters were observed both between and within the sites. There was a large degree of congruence between each of the microbiological approaches. In particular, one sample appeared to be distinguished by a reduction in culturable bacteria (especially pseudomonads), limited response to carbon sources in CLPP, and major differences in extracted fatty acid profiles. The use of multivariate analysis to examine the relationship between microbial and physicochemical measurements revealed that CLPP and plate counts were useful for determining the gross effect of metals on soil microbial communities, whereas proportions of metal-resistant bacteria and dehydrogenase activity differentiated between the two sites. Copper and zinc concentrations and pH all showed significant correlation with the microbial parameters. Nematode community structure was affected to a greater extent by soil pH than by metal content, but the within-site rankings were the same as those achieved for microbiological analyses. The use of these methods for field evaluation of the impact of industrial pollution may be possible provided care is taken when interpreting the data.
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