Complex monitoring of the state of sea water basins by optical methods: part 4. Fiber optic system for measurements of the phytoplankton concentration
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Phytoplankton cell or colony sizes range from <1 µm to several cm, i.e. 4–5 orders of magnitude in linear dimensions, which is roughly equivalent to the log-size span within terrestrial vegetation. It is commonplace to assume that smaller phytoplankton have an advantage in growth related traits while larger ones are more resistant to losses. However, the current state of literature calls for a more differentiated view. It is still controversial, whether smaller phytoplankton have higher maximal growth rates (µmax) or if there is a peak of µmax at intermediate size (102 µm3 cell volume). Smaller phytoplankton have an advantage in nutrient acquisition at low concentrations while larger phytoplankton have an advantage in utilizing nutrient pulses and exploiting vertical gradients. At equal density, larger phytoplankton experience bigger sinking losses. Small phytoplankton (<5–10 µm) are more affected mostly from grazing by protists and tunicates, while larger phytoplankton are more affected by copepod and krill grazing. Size spectra within the most important higher taxa show some conspicuous differences between marine and lake phytoplankton, e.g. the absence of very large diatoms (>105 µm3) in lake phytoplankton and the absence of large (>103 µm3) green algae in marine plankton. Overall, size is one of the most important traits for the performance of phytoplankton, but it is overly simplistic to equate small size with metabolic advantages.
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Phytoplanktons are primary producer, which determine the waters productivity. The assemblages of phytoplankton in the lake varied spatially and temporally as a result of nutrient concentration, some physical and chemical factors. However, the assemblage of phytoplankton in the lake was not well documented. The overall aim of the study was to count and identify phytoplankton taxa and to examine assemblages at location with and without ooze, and to relate the presence/absence of ooze to phytoplankton abundance and assemblages. The samples were collected from Myall Lakes, NSW Australia. The data were analysed using multivariate analysis to determine assemblages of phytoplankton amongst location. Furthermore, univariate analysis was used to examine how the water quality was in particular presence/absence of ooze affected to phytoplankton abundance. The hypothesis being tested was: (1) phytoplankton assemblages vary spatially in Myall Lake due to varying water quality characteristics, including presence of ooze, (2) there was a significant difference of phytoplankton abundances between locations due to presence/absence of ooze. In both instance the hypothesis on this study was accepted. There was a significant different not only phytoplankton assemblages but also phytoplankton abundance within locations. It concluded that the phytoplankton varied spatially in those locations. Presence/absence of ooze affects abundance of phytoplankton. However, further study was needed to conduct in particular to determine certain aspects which affect the assemblages and abundances of phytoplankton.
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The northern Bering and Chukchi seas are biologically productive regions but, recently, unprecedented environmental changes have been reported. For investigating the dominant phytoplankton communities and relative contribution of small phytoplankton (<2 µm) to the total primary production in the regions, field measurements mainly for high-performance liquid chromatography (HPLC) and size-specific primary productivity were conducted in the northern Bering and Chukchi seas during summer 2016 (ARA07B) and 2017 (OS040). Diatoms and phaeocystis were dominant phytoplankton communities in 2016 whereas diatoms and Prasinophytes (Type 2) were dominant in 2017 and diatoms were found as major contributors for the small phytoplankton groups. For size-specific primary production, small phytoplankton contributed 38.0% (SD = ±19.9%) in 2016 whereas 25.0% (SD = ±12.8%) in 2017 to the total primary productivity. The small phytoplankton contribution observed in 2016 is comparable to those reported previously in the Chukchi Sea whereas the contribution in 2017 mainly in the northern Bering Sea is considerably lower than those in other arctic regions. Different biochemical compositions were distinct between small and large phytoplankton in this study, which is consistent with previous results. Significantly higher carbon (C) and nitrogen (N) contents per unit of chlorophyll-a, whereas lower C:N ratios were characteristics in small phytoplankton in comparison to large phytoplankton. Given these results, we could conclude that small phytoplankton synthesize nitrogen-rich particulate organic carbon which could be easily regenerated.
Primary productivity
Primary producers
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The paper presents results of investigating phytoplankton of the Barje Reservoir during 1998/99 and in 2001. Changes in the qualitative and quantitative structure of phytoplankton are followed by comparing the obtained results with results of investigations conducted in 1996 (one year after formation of the reservoir). Initially (in 1996) an oligotrophic water body in which Bacillariophyta were dominant, this reservoir during 1998/99 exhibited traits of a mesoeutrophic lake and was characterized by the presence of a large biomass of phytoplankton (Bacillariophyta and Pyrrophyta), Investigations of the phytoplankton community repeated in 2001 showed decline in the abundance of phytoplankton, but further processes of eutrophication too, as reflected in the appearance of Cyanophyta.
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Storing carbon dioxide in the oceans is expected to provide a useful means of tackling climate change. Especially, the availability of iron to marine phytoplankton has received considerable attention. There is a hypothesis that fertilizing the oceans with iron may help to reduce carbon dioxide in the atmosphere, because they increase the amount of carbon dioxide absorbed by phytoplankton in the oceans. In this study, we present data on the effect of the chemical form of iron on the growth of phytoplankton in artificial seawater media, in which we have varied the composition of dissolved iron species using synthetic chelators. It was found that chemical forms of iron in the culture media influenced the cell growth of phytoplankton. Under low-iron conditions, the phytoplankton growth was affected by the concentrations of synthetic chelators in the culture media. Under high-iron conditions, there was little difference in growth rates of phytoplankton between chelators in the media. On the basis of the data obtained, we discuss equilibrium conditions controlling the phytoplankton growth in the cultures.
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On the basis of the monthly observation of concentrations of size-fractionated Chl.a during 2003—2010,the phytoplankton size structure and its seasonal,annual,and long term changes in Jiaozhou Bay were studied.Results indicated that the micro-and nano-phytoplankton were the main components in the phytoplankton community in Jiaozhou Bay.The concentration of Chl.a decreased from the north and northeast to the middle and the south of the bay.The seasonal and annual changes of the size-fractionated Chl.a concentrations were similar in different areas of the bay.The micro-and nano-phytoplankton showed a seasonal change of double-peak,with the micro-phytoplankton peak in winter and nano-phytoplankton peak in summer.The percentage of the micro-,nano-and pico-phytoplankton in different areas were similar.The results of the long term changes indicated that the percentage of the micro-phytoplankton was increasing since 1990s in the winter,and the nano-phytoplankton percentage increases in the summer.The percentage of pico-phytoplankton significantly decreased after 2000.The temperature,the concentration and structure of nutrients were important factors affecting the change of the size fractionated Chl.a in Jiaozhou Bay.
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Data from three cruises conducted in the northern South China Sea (SCS),the Daya Bay and the Pearl River Estuary,respectively,were examined to access the variations of phytoplankton size structure. A spectral mixing model was established to retrieve phytoplankton size parameter from phytoplankton absorption spectra,with Sf as a proxy of the size parameter. There were significant similarities in phytoplankton size structure in the estuarine and coastal waters; however,it is very dif-ferent in the open ocean. In the estuarine and coastal waters,the micro-phytoplankton plays a dominant role,while in the open ocean the pico-phytoplankton was the dominant species. Phytoplankton size parameter tended to decrease with increasing micro-phytoplankton,and to increase with increasing pico-phytoplankton. There was an increasing trend for chlorophyll a concentration from the open ocean to the coastal sea. Phytoplankton size parameter showed a power function relation with chlorophyll a concentration and decreased with increasing chlorophyll a concentration. The results showed that there was a relationship between phytoplankton size parameter retrieved from the spectral mixing model and the bio-optical characteristics in different circumstances of the SCS. This spectral mixing model provided a simple tool for extracting ecological information of phytoplankton species from optical measurements,and can be used to analyze the influence of dominant phytoplankton size structure on optical characteristics.
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Time-series observations and a phytoplankton manipulation experiment were combined to test the hypothesis that phytoplankton succession effects changes in bacterial community composition. Three humic lakes were sampled weekly May-August and correlations between relative abundances of specific phytoplankton and bacterial operational taxonomic units (OTUs) in each time series were determined. To experimentally characterize the influence of phytoplankton, bacteria from each lake were incubated with phytoplankton from one of the three lakes or no phytoplankton. Following incubation, variation in bacterial community composition explained by phytoplankton treatment increased 65%, while the variation explained by bacterial source decreased 64%. Free-living bacteria explained, on average, over 60% of the difference between phytoplankton and corresponding no-phytoplankton control treatments. Fourteen out of the 101 bacterial OTUs that exhibited positively correlated patterns of abundance with specific algal populations in time-series observations were enriched in mesocosms following incubation with phytoplankton, and one out of 59 negatively correlated bacterial OTUs was depleted in phytoplankton treatments. Bacterial genera enriched in mesocosms containing specific phytoplankton assemblages included Limnohabitans (clade betI-A), Bdellovibrio and Mitsuaria. These results suggest that effects of phytoplankton on certain bacterial populations, including bacteria tracking seasonal changes in algal-derived organic matter, result in correlations between algal and bacterial community dynamics.
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