CEFAS says that the analyses of multi-cellular benthic communities is frequently used to assess marine environments. As a group, the organisms within these communities are largely sedentary and therefore have to withstand environmental pressures or perish. However, assessing Unicellular Archaea and bacteria in marine environmental impact studies is a new research technique. These organisms are not usually studied even though they play a fundamental role in benthic ecosystem function.
To date, bacteria have been used as indicators for sanitary risks and measures of general water quality in freshwaters. Furthermore, the presence of specific bacteria and viruses is also assessed in animal health surveys, especially to maintain food safety.
Marine environmental research generally focuses on the distribution and abundance of organisms and the interactions both among and between organisms and their environment. These interactions contribute to the functioning of biological systems and processes. In cases where natural or man-made impacts (eg. pollution) are suspected to cause changes in marine populations, different types of impact studies can be conducted to understand the type of effects caused and to assess the relative sensitivities of organisms to such impacts.
Genetic fingerprinting methods are also being applied in these studies to analyse the composition of microbial communities in marine sediments. Techniques include DGGE (Denaturing Gradient Gel Electrophoresis), RISA (Ribosomal Intergenic Spacer Analyses) and T-RFLP (Terminal Restriction Fragment Length Polymorphism). Other techniques will enable phylogenetic analyses and the use of multivariate statistics like nonmetric multidimensional scaling (MDS) or gradient analyses like Canonical Correspondence Analysis (CCA).
Virtual example of a CCA biplot of DGGE fingerprints using organic C (org.C), chlorophyll a (Chl a), depth, macrobenthos and meiobenthos community, grain size, and the nutrients nitrate (NO3), nitrite (NO2). Circles indicate bacterial communities, and numbers near the symbols indicate a sampling station (2-5). Arrows indicate the direction of increasing values of the respective variable, and the length of arrows indicates the degree of correlation of the variable with community data.
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