ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2014-01-04
    Description: This study examined seasonal differences in microbial community structure in the sediment of three streams in North Carolina’s Neuse River Basin. Microbes that reside in sediment are at the base of the food chain and have a profound influence on the health of freshwater stream environments. Terminal-Restriction Fragment Length Polymorphism (T-RFLP), molecular fingerprint analysis of 16S rRNA genes was used to examine the diversity of bacterial species in stream sediment. Sediment was sampled in both wet and dry seasons from an agricultural (Bear), mixed urban (Crabtree) and forested (Marks) Creek, and the microbiota examined. Gamma, Alpha and Beta proteobacteria were prevalent species of microbial taxa represented among all sites. Actinobacteria was the next most prevalent species observed, with greater occurrence in dry compared to the wet season. Discernable clustering was observed of Marks and Bear Creek samples collected during the wetter period (September–April), which corresponded with a period of higher precipitation and cooler surface water temperatures. Although not statistically significant, microbial community structure appeared different between season (ANOSIM, R = 0.60; p 〈 0.10). Principal components analysis confirmed this pattern and showed that the bacterial groups were separated by wet and dry seasonal periods. These results suggest seasonal differences among the microbial community structure in sediment of freshwater streams and that these communities may respond to changes in precipitation during wetter periods.
    Electronic ISSN: 1424-2818
    Topics: Biology
    Published by MDPI Publishing
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...