Bacterial Response Variables

FIGURE 1 Potential relationships between bioavailable DOM and bulk DOM. The lower curve assumes increases in bulk DOM are largely driven by the addition of relatively refractory material the upper curve assumes increases in bulk concentration are due to the addition of either novel compounds or compounds similar to those already present. The space between the two curves allows microbial metabolism to vary widely within a narrow range of bulk DOM concentration. 

The effects of variation in DOM concentration and/or composition can be examined via comparative studies of systems known (or suspected) to vary in the type of DOM being supplied or by direct manipulation (usually addition) of specific dissolved compounds. 

FIGURE 2 Schematic of independent (DOM quantity and composition) and dependent variables (nutrient demand, bacterial production and respiration, and degradative activity). 

FIGURE 3 Relationship between Hudson River planktonic bacterial production and ambient bulk DOC. Data are derived from biweekly sampling of a single station near Kingston, New York over a 10-year span. 

Aside from adding defined compounds, experimental additions of natural DOM mixtures suspected to vary in lability have helped test ideas about the contribution of various DOM sources to aquatic ecosystems. In a nice example using manipulation of natural DOM sources, Battin et al. (1999) used flowthrough microcosms to measure the relative uptake rates of allochthonous and autochthonous DOM by stream sediments. They documented greater than fivefold differences or more in uptake and respiration, depending on whether the DOM was extracted from soil or periphyton. Moreover, they were able to show, via transplant experiments, several cases where prior exposure to a particular source of DOM increased the ability of that community to metabolize the DOM supplied. There appears to be some preadaptation of microbial catabolic capacity when these stream biofilms were re-exposed to a familiar type of DOM. Similarly, the response of heterotrophic bacteria to carbon or nutrient addition was greatest when the source community was particularly active (Foreman et al., 1998). Kaplan et al. (1996) showed that fixed film bioreactors, colonized on one water source, were unable to rapidly metabolize DOC in water from another source. 

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III. Time Scale and Scope of Bacterial Response Variables 373... 

III. TIME SCALE AND SCOPE OF BACTERIAL RESPONSE VARIABLES... 

On the other hand, comparative analysis of Fi variables gave the relative reduction of SOS-response in preincubated with AR bacterial cells (Table 3). So, repression SOS-response was proportionally to the length of the AR alkyl radical and was Fi = 3.7 (for Ce-AR) and Fi = 7.0 (for C12-AR) that 76.43-40.40 fold lower than the SOS-system activation level in cells exposured only by UV radiation. With reduction of the AR concentration to lO- M is still observed statistically significant differences in the values of induction index (Fi) of the control and experimental samples, although the repression of SOS-response was less expressed. An increase of the AR concentration up to 1(>3 M in the case of Ci-AR and C3-AR led to some suppression, and for the C5-, Ca- and C12-AR to increase the values of R. 

Marine mammals share fundamental immunological features with their terrestrial counterparts. For example, as in veterinary medicine, hematological variables have long been used as diagnostic tools in marine mammal medicine, providing elementary clinical information on quantitative aspects on white blood cell subpopulations [6], Such work provided early evidence of inflammatory responses by a variety of marine mammal species to viral, bacterial and macroparasitic infection akin to those responses that were better understood in domestic animals. 

Understanding the factors controlling organic matter turnover is complicated by possible differences in population distributions of organisms responsible for enzyme production and product uptake. Although relationships between enzyme Vmax and bacterial productivity have been reported (Sinsabaugh et al., 1997), correlations between total bacterial numbers or bacterial production and enzyme activities are frequently found to be variable or weak (e.g., Mayer, 1989 Boetius et al., 1996, 2000). Vrba et al. (1992) observed that MUF-a-glucosidase activity correlated with bacterial biomass measured in a freshwater reservoir over the course of three seasons,... 

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