Plankton populations

BloFIms. Microbiologists recognize two different populations of microorganisms. Free-floating (planktonic) populations are found in the bulk water. Attached (sessile) populations colonize surfaces. The same kinds of microorganisms can be found in either population, but the sessile population is responsible for biofouling. 

Particulate organic matter (POM) in the ocean originates largely from plankton in the euphotic zone and reflects living plankton populations. Between 40°N and 40°S... 

The major purpose of monitoring microbes is to identify the generation of biofilms and to find the locations of biofilms, if any. The purpose of sanitization is to kill and destroy the biofilm after detecting the location of the biofilms. The planktonic population, whose number of micro-organisms in water is monitored, should be understood and utilized to indicate biofilms in the system. The number of microbes in water is an indicator of system contamination levels and is the basis for the system alert levels. 

Holligan, P.M., Williams, P.J. le B., Purdine, D. and Harris, R.P., 1984 b. Photosynthesis, respiration and nitrogen supply of plankton populations in stratified frontal and tidally mixed shelf waters. Mar. Ecol. Prog. Ser., 17 201-213. 

Savidge, G, and Hutley, H.T. (1977) Rates of remineralization and assimilation of urea by fractionated plankton populations in coastal waters. J. Exp. Mar. Biol. Ecol. 28, 1-16. 

Figure 6.1 Average plankton population density as a function of the Damkohler number for logistic growth with non-uniform carrying capacity of the form K(x,y) = Kq + (5sin(27rx) sin(27ry) and chaotic mixing in the time-periodic sine-flow of Eq. (2.66). The continuous line represents results from the solution of the full partial differential equation with diffusion (Pe 104) and stars ( ) show the time-averaged plankton populations calculated from the non-diffusive Lagrangian representation.

The dependence of the average concentration on the Damkohler number can also be interpreted within the Lagrangian formulation. For example, the logistic growth function of the plankton population dynamics (Eq. (6.7)) is concave near the steady state P = K, i.e. the plankton population reacts more quickly when the carrying capacity is below the actual plankton density, than in the opposite case when higher carrying capacity allows for increase of the plankton concentration. Due to this asymmetric nonlinear response the... 

Truscott and Brindley (1994) have shown that some plankton population models can produce excitable dynamics, and they suggested this as a possible explanation for the observed plankton blooms. The phytoplankton population plays the role of the fast component while zooplankton responds on a slower timescale to increased phytoplankton concentration. This allows for a transient plankton bloom, that can be triggered by various changes in the environment. 

Neufeld et al. (2002a) have shown that this behavior can be explained by the interplay between excitable plankton population dynamics and chaotic flow, similarly to the excitable behavior described in the previous section. In a chaotic flow a steady bloom filament profile can be generated, that does not decay until it invades the whole computational domain as an advectively propagating bloom. The condition for the existence of the steady bloom filament solution in the corresponding one-dimensional filament model is that the rate of convergence, quantified by the Lyapunov exponent, should be slower than the phytoplankton growth rate, but faster than the zooplankton reproduction rate. In this case the phytoplankton does not became diluted by the flow and the zooplankton is thus kept at low concentration unable to graze down the bloom filament. 

Oscillations can also arise from the nonlinear interactions present in population dynamics (e.g. predator-prey systems). Mixing in this context is relevant for oceanic plankton populations. Phytoplankton-zooplankton (PZ) and other more complicated plankton population models often exhibit oscillatory solutions (see e.g. Edwards and Yool (2000)). Huisman and Weissing (1999) have shown that oscillations and chaotic fluctuations generated by the plankton population dynamics can provide a mechanism for the coexistence of the huge number of plankton species competing for only a few key resources (the plankton paradox ). In this chapter we review theoretical, numerical and experimental work on unsteady (mainly oscillatory) systems in the presence of mixing and stirring. 

D. M. Dubois. A model of patchiness for prey-predator plankton populations. Ecol. Mod., 1 67-80, 1975a. 

D.M. Dubois. Simulation of the spatial structuration of a patch of prey-predator plankton populations in the Southern Bight of the North Sea. Mem. Soc. Roy. Sci. Liege Ser. 6, 7 75-82, 1975b. 

M. Edwards and A. Yool. The role of higher predation in plankton population models. J. Plank. Res., 22 1085-1112, 2000. 

J.E. Truscott and J. Brindley. Ocean plankton populations as excitable media. Bull. Math. Biol., 56 981-998, 1994. 

Iwamura, T., Nagai, H. and Ichimura, S., 1970. Improved methods for determining contents of chlorophyll, protein, ribonucleic acid and deoxyribonucleic acid in planktonic populations. Int. Revue Ges. Hydrobiol., 55 131—147. 

Derenbach, J.B. and Williams, P.J.LeB., 1974. Autotrophic and bacterial production fractionation of plankton population by differential filtration of samples from the English Channel. Mar. Biol., 25 263—269. 

Figure 4.22 The slow release of Mgp2 NPs inn the broth media and the high killing effect on the planktonic population.

Laser Fluorimeter As 2i source of biological information we propose the use of a multi-station (up to 12 sampling locations) towed sea water laser fluorimeter for water quality analysis specific to selected hydrocarbons which might be present in the area. The laser excites elements of the plankton population and that of calibrated hydrocarbons (e.g. breakdown products of munitions contents) present in the water. The fluorescent spectra are received through a fibre optic cable, split and counted through specific filters. From this data a direct correlation of the effects of pollution on the plankton population can be made. The system would be towed in conjunction with the multi-sensor towed array. 

Mayzaud, P., Eaton, C.A. and Ackman, R.G. (1976) The occurrence and distribution of octadecapentaenoic acid in a natural plankton population. A possible food chain index. Lipids 11, 858-862. 

The influence of abiotic factors on biocide efficacy has been largely studied on planktonic populations (Bessems, 1998), but can be expected to be also relevant to biofilms. For example, the enhanced efficacy of many biocides with increasing temperature has been described for the treatment of Pseudomonas aeruginosa bio-films thus, a formulation of peracetic acid and hydrogen peroxide caused an increase in killing when the temperature was increased within the temperature range of 10°C to 50°C (Blanchard et al., 1998). 

Relatively few studies have included the effect of chlorine dioxide on biofilms. Characklis (1990) mentions that chlorine dioxide has been successfully used to control biofouling in several industrial environments. Walker and Morales (1997) studied the effect of chlorine dioxide on a mixed population of drinking water bacteria in a continuous culture model which was developed to simulate an industrial water system. The addition of Img/L chlorine dioxide for approximately 18 h was sufficient to reduce the viable counts of the planktonic population by 99.9%, whereas 1.5 mg/L chlorine dioxide was required to achieve a similar reduction in the biofilms, suggesting an enhanced resistance of biofilm bacteria to the biocide. There are indications that continuous disinfection of drinking water using chlorine dioxide provides a certain control of biofilm formation. In a French drinking water distribution system, the presence of chlorine dioxide allowed a limited surface colonization, while in regions where chlorine dioxide was below the detection limit, an increase in biofilm formation occurred (Servais et al., 1995). 

Sampling procedures can also affect the type and frequency of microbial contaminants recovered from a contaminated fuel storage tank. The collection of samples, using a fuel sampler, provides data only on the planktonic population present in the tank water bottom and the fuel/water bottom interface where floating biofilm could be sampled. This sampling provides no information on the possible large sessile population attached to the walls of the tank. In many cases the actual level of contamination present is underestimated or misrepresented. 

Counts of the planktonic population may give the potential for fouling. 

Research has shown that while it may take 1 ppm of residual chlorine to kill planktonic population but it may take 1000 ppm to kill a sessile population. 

A sessile organism is protected from biocides by polysaccharide slime and changes in cell metabolism. Deposit control polymers or cationic biocides like quaternary ammonium may be more effective in preventing planktonic population from attaching than some biocides that may give better planktonic kill. 

However keep in mind that you need to control planktonic population to keep fibers and additives free from... 

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