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Effects of large-scale poultry farms on aquatic microbial communities: A molecular investigation
Author(s) -
Joseph A. Ringbauer,
Joseph B. James,
Fred J. Genthner
Publication year - 2006
Publication title -
journal of water and health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.482
H-Index - 59
eISSN - 1996-7829
pISSN - 1477-8920
DOI - 10.2166/wh.2006.0006
Subject(s) - biology , temperature gradient gel electrophoresis , water quality , sampling (signal processing) , microorganism , litter , streams , nutrient , manure , ecology , microbial population biology , fertilizer , community structure , poultry farming , 16s ribosomal rna , veterinary medicine , environmental science , bacteria , medicine , computer network , genetics , filter (signal processing) , computer science , computer vision
The effects of large-scale poultry production operations on water quality and human health are largely unknown. Poultry litter is frequently applied as fertilizer to agricultural lands adjacent to large poultry farms. Run-off from the land introduces a variety of stressors into the surface waters including nutrients, antimicrobials and pathogenic bacteria. The Delaware, Maryland and Virginia (Delmarva) Peninsula has the highest concentration of broiler chickens per farm acre in the United States and provides an ideal location for studying the effects of stressors from poultry farms. We investigated potential effects by characterizing shifts in the structure of aquatic bacterial communities. DNA was isolated from microorganisms in water samples from streams and rivers at varying distances from, or having different frequencies of, litter applications. Fingerprints of 16S rDNA amplicons from bacteria in water samples collected during late summer 2001 to late spring 2002 were produced by denaturing gradient gel electrophoresis (DGGE). A statistical analysis of multiple fingerprints from each sampling location demonstrated that each site harboured a bacterial community significantly different from the communities at other sites. Similarly, the bacterial communities from each sampling time differed significantly from communities at other sampling times. Most importantly, a competitive, library-based analysis showed time of sampling (month) had a greater effect on community structure than did location.

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