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Influence of underwater light fields on pigment characteristics in the Baltic Sea - results of statistical analysis

Stoń-Egiert J., Majchrowski R., Darecki M., Kosakowska A., Ostrowska M.

Oceanologia

2012

No. 54 (1)

7-27

Changes in phytoplankton pigment concentrations in Case 2 waters (such as those of the Baltic Sea) were analysed in relation to the light intensity and its spectral distribution in the water. The analyses were based on sets of empirical measurements containing two types of data: chlorophyll and carotenoid concentrations obtained by HPLC, and the distribution of underwater light fields measured with a MER 2049 spectrophotometer - collected during 27 research cruises on r/v "Oceania" in 1999-2004. Statistical analysis yielded relationships between the total relative (to chlorophyll a concentrations) concentrations of major groups of phytoplankton pigments and optical depth τ, between the total relative concentrations of major groups of photosynthetic pigments (chlorophylls b (C_chl b tot / Cchl a tot), chlorophylls c (C_chl c tot / C_chl a tot) and photosynthetic carotenoids (CPSC tot / C_chl a tot)) and the spectral fitting function (the "chromatic acclimation factor"), and between the total relative concentrations of photoprotective carotenoids (CPPC tot / C_chl a tot) in Baltic waters and the potentially destructive radiation (PDR), defined as the absolute amount of energy in the blue part of the spectrum (400-480 nm) absorbed by unit mass of chlorophyll a. The best approximations were obtained for the total chlorophyll c content, while the relative estimation errors were the smallest (σ_ = 34.6%) for the approximation to optical depth and spectral fitting function. The largest errors related to the approximation of chlorophyll b concentrations: σ_ = 56.7% with respect to optical depth and 57.3% to the spectral fitting function. A comparative analysis of the relative (to chlorophyll a content) concentrations of the main groups of pigments and the corresponding irradiance characteristics in ocean (Case 1) waters and Baltic waters (Case 2 waters) was also carried out. The distribution of C_chl b tot / C_chl a tot ratios with respect to optical depth reveals a decreasing trend with increasing τ for Baltic data, which is characteristic of photoprotective pigments and the reverse of the trend in oceans. In the case of the C_chl c tot approximations, the logarithmic statistical error is lower for Baltic waters than for Case 1 waters: σ_ = 34.6% for Baltic data and σ_ = 39.4% for ocean data. In relation to photoprotective carotenoids (CPPC), ?_ takes a value of 38.4% for Baltic waters and 36.1% for ocean waters. The relative errors of the approximated concentrations of different pigment groups are larger than those obtained for ocean waters. The only exception is chlorophyll c, for which the logarithmic statistical error is about 8.8% lower (σ_ = 34.6% for Baltic waters and 38.2% for ocean waters). Analysis of the errors resulting from the approximations of the photoprotective carotenoid content, depending on the energy characteristics of the underwater irradiance in the short-range part of PAR, showed that the relative errors are 1.3 times higher for Baltic waters than for ocean waters: σ_ = 38.4% for Baltic waters and 32.0% for ocean waters.

Modelling light and photosynthesis in the marine environment

Woźniak B., Dera J., Ficek D., Majchrowski R., Ostrowska M., Kaczmarek S.

Oceanologia

2003

No. 45 (2)

171-245

The overriding and far-reaching aim of our work has been to achieve a good understanding of the processes of light interaction with phytoplankton in the sea and to develop an innovative physical model of photosynthesis in the marine environment, suitable for the remote sensing of marine primary production. Unlike previous models, the present one takes greater account of the complexity of the physiological processes in phytoplankton. We have focused in particular on photophysiological processes, which are governed directly or indirectly by light energy, or in which light, besides the nutrient content in and the temperature of seawater, is one of the principal limiting factors. To achieve this aim we have carried out comprehensive statistical analyses of the natural variability of the main photophysiological properties of phytoplankton and their links with the principal abiotic factors in the sea. These analyses have made use of extensive empirical data gathered in a wide diversity of seas and oceans by Polish and Russian teams as well as by joint Polish-Russian expeditions. Data sets available on the Internet have also been applied. As a result, a set of more or less complex, semi-empirical models of light-stimulated processes occurring in marine phytoplankton cells has been developed. The trophic type of sea, photo-acclimation and the production of photoprotecting carotenoids, chromatic acclimation and the production of various forms of chlorophyll-antennas and photosynthetic carotenoids, cell adaptation by the package effect, light absorption, photosynthesis, photoinhibition, the fluorescence effect, and the activation of PS2 centres are all considered in the models. These take into account not only the influence of light, but also, indirectly, that of the vertical mixing of water; in the case of photosynthesis, the quantum yield has been also formulated as being dependent on the nutrient concentrations and the temperature of seawater. The bio-optical spectral models of irradiance transmittance in case 1 oceanic waters and case 2 Baltic waters, developed earlier, also are described in this paper. The development of the models presented here is not yet complete and they all need continual improvement. Nevertheless, we have used them on a preliminary basis for calculating various photosynthetic characteristics at different depths in the sea, such as the concentration of chlorophyll and other pigments, and primary production. The practical algorithm we have constructed allows the vertical distribution of these characteristics to be determined from three input data: chlorophyll a concentration, irradiance, and temperature at the sea surface. Since all three data can be measured remotely, our algorithm can be applied as the "marine part" of the remote sensing algorithms used for detecting marine photosynthesis.