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1

Total suspended particulate matter in the Porsanger fjord (Norway) in the summers of 2014 and 2015

Białogrodzka J., Stramska M., Ficek D., Wereszka M.

Oceanologia

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2018

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No. 60 (1)

1--15

EN

High-latitude fjords, very vulnerable to global change, are impacted by their land and ocean boundaries, and they may be influenced by terrestrial water discharges and oceanic water inputs into them. This may be reflected by temporal and spatial patterns in concentrations of biogeochemically important constituents. This paper analyses information relating to the total suspended matter (TSM) concentration in the Porsanger fjord (Porsangerfjorden), which is situated in the coastal waters of the Barents Sea. Water samples and a set of physical data (water temperature, salinity, inherent optical properties) were obtained during two field expeditions in the spring and summer of 2014 and 2015. Bio-optical relationships were derived from these measurements, enabling optical data to be interpreted in terms of TSM concentrations. The results revealed significant temporal variability of TSM concentration, which was strongly influenced by precipitation, terrestrial water discharge and tidal phase. Spatial distribution of TSM concentration was related to the bathymetry of the fjord, dividing this basin into three subregions. TSM concentrations ranged from 0.72 to 0.132 g m−3 at the surface (0–2 m) and from 0.5 to 0.67 g m−3 at 40 m depth. The average mineral fraction was estimated to be 44% at surface and 53% at 40 m.

2

Light absorption by phytoplankton in the southern Baltic and Pomeranian lakes: mathematical expressions for remote sensing applications

Meler J., Ostrowska M., Ficek D., Zdun A.

Oceanologia

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2017

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No. 59 (3)

195--212

EN

The absorption properties of phytoplankton in surface waters of the Baltic Sea and coastal lakes are examined in the context of their relationships with the concentration of the main photosynthetic pigment, chlorophyll a. The analysis covers 425 sets of spectra of light absorption coefficients aph (λ) and chlorophyll a concentrations Chla measured in 2006–2009 in various waters of the Baltic Sea (open and coastal waters, the Gulf of Gdańsk and the Pomeranian Bay, river mouths and the Szczecin Lagoon), as well as in three lakes in Pomerania, Poland (Obłęskie, Łebsko and Chotkowskie). In these waters the specific (i.e. normalized with respect to Chla) light absorption coefficient of phytoplankton aph*(λ) varies over wide ranges, which differ according to wavelength. For example, aph*(440) takes values from 0.014 to 0.124 mg−1 m2, but aph*(675) from 0.008 to 0.067 mg−1 m2, whereby Chla ranges from 0.8 to 120 mg m−3. From this analysis a mathematical description has been produced of the specific light absorption coefficient of phytoplankton aph*(λ), based on which the dynamics of its variability in these waters and the absorption spectra in the 400–700 nm interval can be reconstructed with a low level of uncertainty (arithmetic statistical error: 4.09–10.21%, systematic error: 29.63–51.37%). The relationships derived here are applicable in local remote sensing algorithms used for monitoring the Baltic Sea and coastal lakes and can substantially improve the accuracy of the remotely determined optical and biogeochemical characteristics of these waters.

3

Pine pollen grains in coastal waters of the Baltic Sea

Pawlik M., Ficek D.

Oceanological and Hydrobiological Studies

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2016

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Vol. 45, No. 1

35--41

EN

Measurements relating to a yellow deposit covering large areas of the Baltic Sea in spring are reported. Analysis of water samples showed it to be of terrestrial origin and to consist mainly of pine pollen grains. The equivalent spherical diameter (ESD) of these grains ranged from 29.1 to 78.4 μm, with a maximum between 47.7 and 56.3 μm. Surface water concentrations of pollen in the coastal zone near Ustka showed that its proportion in the total suspended particulate matter (SPM) might be as high as 30-40%. Such high surface water concentrations of hitherto neglected substances critical to water color formation can give rise to serious errors in remote measurements of water composition and properties.

4

Practical applicability and preliminary results of the Baltic environmental satellite remote sensing system (SATBAŁTYK)

Ostrowska M., Darecki M., Krężel A., Ficek D., Furmańczyk K.

Polish Maritime Research

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2015

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nr 3

43--49

EN

The SatBałtyk (Satellite Monitoring of the Baltic Sea Environment) project is being realized in Poland by the SatBałtyk Scientific Consortium, specifically appointed for this purpose, which associates four scientific institutions: the Institute of Oceanology PAN in Sopot – coordinator of the project, the University of Gdańsk (Institute of Oceanography), the Pomeranian Academy in Słupsk (Institute of Physics) and the University of Szczecin (Institute of Marine Sciences). The project is aiming to prepare a technical infrastructure and set in motion operational procedures for the satellite monitoring of the Baltic Sea ecosystem. The main sources of input data for this system will be the results of systematic observations by metrological and environmental satellites such as TIROS N/NOAA, MSG (currently Meteosat 10), EOS/AQUA and Sentinel -1, 2, 3 (in the future). The system will deliver on a routine basis the variety of structural and functional properties of this sea, based on data provided by relevant satellites and supported by hydro-biological models. Among them: the solar radiation influx to the sea’s waters in various spectral intervals, energy balances of the short- and long-wave radiation at the Baltic Sea surface and in the upper layers of the atmosphere over the Baltic, sea surface temperature distribution, dynamic states of the water surface, concentrations of chlorophyll a and other phytoplankton pigments in the Baltic waters, spatial distributions of algal blooms, the occurrence of coastal upwelling events, and the characteristics of primary production of organic matter and photosynthetically released oxygen in the water and many others. The structure of the system and preliminary results will be presented.

5

UV absorption reveals mycosporine-like amino acids (MAAs) in Tatra mountain lake phytoplankton

Ficek D., Dera J., Woźniak B.

Oceanologia

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2013

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No. 55 (3)

599--609

EN

Enhanced absorption of UV radiation, an effect characteristic of mycosporine-like amino acids (MAAs), is reported in samples of phytoplankton from six lakes in the Tatra Mountains National Park (Poland). It was demonstrated that the mass-specific UV absorption coefficients for the phytoplankton in these lakes increased with altitude above sea level. Based on a comparison with the phytoplankton of Alpine lakes, investigated earlier by other authors (cited in this paper), it may be inferred that the phytoplankton of Tatra mountain lakes produce MAAs, which protect plant cells from UV light, the intensity of which increases with altitude.

6

Inherent optical properties and remote sensing reflectance of Pomeranian lakes (Poland)

Ficek D., Meler J., Zapadka T., Woźniak B., Dera J.

Oceanologia

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2012

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No. 54 (4)

611-630

EN

This paper describes the results of comprehensive empirical studies of the inherent optical properties (IOPs), the remote sensing reflectance Rrs(λ) and the contents of the principal optically active components (OAC) i.e. coloured dissolved organic matter (CDOM), suspended particulate matter (SPM) and chlorophyll a, in the waters of 15 lakes in Polish Pomerania in 2007-2010. It presents numerous spectra of the total absorption a(λ) and scattering b(λ = bp(λ) of light in the visible band (400-700 nm) for surface waters, and separately, spectra of absorption by CDOM aCDOM(λ) and spectra of the mass-specific coefficients of absorption ap*(SPM)(λ) and scattering bp*(SPM)(λ) by SPM. The properties of these lake waters are highly diverse, but all of them can be classified as Case 2 waters (according to the optical classification by Morel & Prieur 1977) and they all have a relatively high OAC content. The lakes were conventionally divided into three types: Type I lakes have the lowest OAC concentrations (chlorophyll concentration Ca = (8.76 š 7.4) mg m-3 and CDOM absorption coefficients aCDOM(440) = (0.57 š 0.22) m-1 (i.e. mean and standard deviation), and optical properties (including spectra of Rrs(?) resembling those of Baltic waters. Type II waters have exceptionally high contents of CDOM (aCDOM(440) = (15.37 š 1.54) m-1), and hence appear brown in daylight and have very low reflectances Rrs(?) (of the order of 0.001 sr-1). Type III waters are highly eutrophic and contain large amounts of suspended matter, including phytoplankton ((CSPM = (47.0 š 39.4) g m-3, Ca = (86.6 š 61.5) mg m-3; aCDOM(440) = (2.77 š 0.86) m-1). Hence the reflectances Rrs(?) of these type of waters are on average one order of magnitude higher than those of the other natural waters, reaching maximum values of 0.03 sr-1 in ? bands 560-580 nm and 690-720 nm (see Ficek et al. 2011). The article provides a number of empirical formulas approximating the relationships between the properties of these lake waters.

7

SatBałtyk - A Baltic environmental satellite remote sensing system - an ongoing project in Poland. Part 2: Practical applicability and preliminary results

Woźniak B., Bradtke K., Darecki M., Dera J., Dudzińska-Nowak J., Dzierzbicka-Głowacka L., Ficek D., Furmańczyk K., Kowalewski M., Krężel A., Majchrowski R., Ostrowska M., Paszkuta M., Stoń-Egiert J., Stramska M., Zapadka T.

Oceanologia

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2011

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No. 53 (4)

925-956

8

SatBałtyk - A Baltic environmental satellite remote sensing system - an ongoing project in Poland. Part 1: Assumptions, scope and operating range

Woźniak B., Bradtke K., Darecki M., Dera J., Dudzińska-Nowak J., Dzierzbicka-Głowacka L., Ficek D., Furmańczyk K., Kowalewski M., Krężel A., Majchrowski R., Ostrowska M., Paszkuta M., Stoń-Egiert J., Stramska M., Zapadka T.

Oceanologia

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2011

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No. 53 (4)

897-924

EN

This article is the first of two papers on the remote sensing methods of monitoring the Baltic ecosystem, developed by a Polish team. The main aim of the five-year SatBałtyk (2010-2014) research project (Satellite Monitoring of the Baltic Sea Environment) is to prepare the technical infrastructure and set in motion operational procedures for the satellite monitoring of the Baltic environment. This system is to characterize on a routine basis the structural and functional properties of this sea on the basis of data supplied by the relevant satellites. The characterization and large-scale dissemination of the following properties of the Baltic is anticipated: the solar radiation influx to the sea's waters in various spectral intervals, energy balances of the short- and long-wave radiation at the Baltic Sea surface and in the upper layers of the atmosphere over the Baltic, sea surface temperature distribution, dynamic states of the water surface, concentrations of chlorophyll a and other phytoplankton pigments in the Baltic water, distributions of algal blooms, the occurrence of upwelling events, and the characteristics of primary organic matter production and photosynthetically released oxygen in the water. It is also intended to develop and, where feasible, to implement satellite techniques for detecting slicks of petroleum derivatives and other compounds, evaluating the state of the sea's ice cover, and forecasting the hazards from current and future storms and providing evidence of their effects in the Baltic coastal zone. The ultimate objective of the project is to implement an operational system for the routine determination and dissemination on the Internet of the above-mentioned features of the Baltic in the form of distribution maps as well as plots, tables and descriptions characterizing the state of the various elements of the Baltic environment. The main sources of input data for this system will be the results of systematic recording by environmental satellites and also special-purpose ones such as TIROS N/NOAA, MSG (currently Meteosat 9), EOS/AQUA and ENVISAT. The final effects of the SatBałtyk project are to be achieved by the end of 2014, i.e. during a period of 60 months. These two papers present the results obtained during the first 15 months of the project. Part 1 of this series of articles contains the assumptions, objectives and a description of the most important stages in the history of our research, which constitute the foundation of the current project. It also discusses the way in which SatBałtyk functions and the scheme of its overall operations system. The second article (Part 2), will discuss some aspects of its practical applicability in the satellite monitoring of the Baltic ecosystem (see Woźniak et al. (2011) in this issue).

9

Remote sensing reflectance of Pomeranian lakes and the Baltic

Ficek D., Zapadka T., Dera J.

Oceanologia

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2011

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No. 53 (4)

959-970

EN

The remote sensing reflectance R_rs, concentrations of chlorophyll a and other pigments C_i, suspended particulate matter concentrations C_SPM and coloured dissolved organic matter absorption coefficient αCDOM(λ) were measured in the euphotic zones of 15 Pomeranian lakes in 2007-2010. On the basis of 235 sets of data points obtained from simultaneous estimates of these quantities, we classified the lake waters into three types. The first one, with the lowest αCDOM(440 nm) (usually between 0.1 and 1.3 m-1 and chlorophyll α concentrations 1.3 < Ca < 33 mg m-3), displays a broad peak on the reflectance spectrum at 560-580 nm and resembles the shape of the remote sensing reflectance spectra usually observed in the Baltic Proper. A set of Rrs spectra from the Baltic Proper is given for comparison. The second lake water type has a very high CDOM absorption coefficient (usually αCDOM(440 nm) > 10 m-1, up to 17.4 m-1 in Lake Pyszne; it has a relatively low reflectance (Rrs < 0.001 sr-1) over the entire spectral range, and two visible reflectance spectra peaks at ca 650 and 690-710 nm. The third type of lake water represents waters with a lower CDOM absorption coefficient (usually αCDOM(440 nm) < 5 m-1) and a high chlorophyll a concentration (usually Ca > 4 mg m-3, up to 336 mg m-3 in Lake Gardno). The remote sensing reflectance spectra in these waters always exhibit three peaks (Rrs > 0.005 sr-1): a broad one at 560-580 nm, a smaller one at ca 650 nm and a well-pronounced one at 690-720 nm. These Rrs(λ) peaks correspond to the relatively low absorption of light by the various optically active components of the lake water and the considerable scattering (over the entire spectral range investigated) due to the high SPM concentrations there. The remote sensing maximum at λ 690-720 nm is higher still as a result of the natural fluorescence of chlorophyll a. Empirical relationships between the spectral reflectance band ratios at selected wavelengths and the various optically active components for these lake waters are also established: for example, the chlorophyll a concentration in surface water layer Ca = 6.432 e4.556X, where X = [max Rrs (695 ≤λ≤720) - Rrs(? = 670)] / max Rrs (695 ? ? ? 720), and the coefficient of determination R^2 = 0.95.

10

Factors controlling pelagic production and respiration in a shallow polymictic lake

Wielgat-Rychter M., Rychter K., Ficek D.

Polish Journal of Ecology

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2010

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Vol. 58, nr 2

379-385

EN

Shallow lakes, defined as 'nonstratifying', polymictic water bodies are usually eutrophic and highly productive, and more turbid than deeper lakes due to bottom sediment resuspension. Gross primary production (GPP) and total planktonic community respiration (TCR) were measured in a very shallow (on average 1.2 m deep) and large (area 25 km2), polymictic, eutrophic Lake Gardno (Baltic coastal lake, Northern Poland) with the light-and-dark bottle method. The aim was to compare GPP to TCR ratio in the pelagic zone in a course of a year and identify factors governing these processes. Identified factors governing GPP were light conditions and temperature, with Q[10] = 2.23 in the 2-24.5[degrees]C temperature range, whereas TCR was driven by water temperature (Q[10] = 2.15 in the same temperature range) and by organic matter content in water. TCR was correlated with total suspended matter (effect of bottom sediment resuspension due to wind action in a very shallow lake), however not with chlorophyll content. During two-year measurement period (years 2006 and 2007), annual GPP amounted to 402 and 471 g C m[^-2], and TCR amounted to 192 and 223 g C m[^-2] respectively. Lake Gardno pelagic system seemed to be net autotrophic on annual basis; GPP to TCR ratio = 2.1. Part of the organic matter produced in pelagial is probably deposited in bottom sediments decomposed there. Wind induced resuspension increases matter content in water (measured here as TSM content) and thus contributes to pelagic respiration processes (TCR).

11

Spatial distribution and seasonal variability in chlorophyll concentration in the coastal Lake Gardno (Poland)

Ficek D., Wielgat-Rychert M.

Oceanological and Hydrobiological Studies

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2009

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Vol. 38, No.1

3-15

EN

In 2006 the spatial distribution and seasonal variations in chlorophyll concentration were measured, at about two-week frequency, in Lake Gardno. In general, chlorophyll concentrations in the central part of the lake were high throughout the growth season. The minimum chlorophyll concentration was recorded in March (7.5 mg m-3), and the maximum value in September (303 mg m-3). Higher chlorophyll concentrations and lower temporal variability were measured in the central part of the lake, compared to lower concentrations and higher variability in the vicinity of the Łupawa River input to the lake. Chlorophyll concentrations were measured fluorometrically along several vertical and horizontal profiles, enabling direct observations of the dynamics of changing chlorophyll concentrations in Lake Gardno throughout the year.

12

Algorithms for the remote sensing of the Baltic ecosystem (DESAMBEM). Part 2: Empirical validation

Darecki M., Ficek D., Krężel A., Ostrowska M., Majchrowski R., Woźniak S.B., Bradtke K., Dera J., Woźniak B.

Oceanologia

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2008

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No. 50 (4)

509-538

EN

This paper is the second of two articles on the methodology of the remote sensing of the Baltic ecosystem. In Part 1 the authors presented the set of DESAMBEM algorithms for determining the major parameters of this ecosystem on the basis of satellite data (see Woźniak et al. 2008 - this issue). That article discussed in detail the mathematical apparatus of the algorithms. Part 2 presents the effects of the practical application of the algorithms and their validation, the latter based on satellite maps of selected Baltic ecosystem parameters: the distributions of the sea surface temperature (SST), the Photosynthetically Available Radiation (PAR) at the sea surface, the surface concentrations of chlorophyll a and the total primary production of organic matter. Particular emphasis was laid on analysing the precision of estimates of these and other parameters of the Baltic ecosystem, determined by remote sensing methods. The errors in these estimates turned out to be relatively small; hence, the set of DESAMBEM algorithms should in the future be utilised as the foundation for the effective satellite monitoring of the state and functioning of the Baltic ecosystem.

13

Algorithm for the remote sensing of the Baltic ecosystem (DESAMBEM). Part 1: Mathematical apparatus

Woźniak B., Krężel A., Darecki M., Woźniak S.B., Majchrowski R., Ostrowska M., Kozłowski Ł., Ficek D., Olszewski J., Dera J.

Oceanologia

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2008

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No. 50 (4)

451-508

EN

This article is the first of two papers on the remote sensing methods of monitoring the Baltic ecosystem, developed by our team. Earlier, we had produced a series of detailed mathematical models and statistical regularities describing the transport of solar radiation in the atmosphere-sea system, the absorption of this radiation in the water and its utilisation in a variety of processes, most importantly in the photosynthesis occurring in phytoplankton cells, as a source of energy for the functioning of marine ecosystems. The comprehensive DESAMBEM algorithm, presented in this paper, is a synthesis of these models and regularities. This algorithm enables the abiotic properties of the environment as well as the state and the functioning of the Baltic ecosystem to be assessed on the basis of available satellite data. It can be used to determine a good number of these properties: the sea surface temperature, the natural irradiance of the sea surface, the spectral and spatial distributions of solar radiation energy in the water, the surface concentrations and vertical distributions of chlorophyll a and other phytoplankton pigments in this sea, the radiation energy absorbed by phytoplankton, the quantum efficiency of photosynthesis and the primary production of organic matter. On the basis of these directly determined properties, other characteristics of processes taking place in the Baltic ecosystem can be estimated indirectly. Part 1 of this series of articles deals with the detailed mathematical apparatus of the DESAMBEM algorithm. Part 2 will discuss its practical applicability in the satellite monitoring of the sea and will provide an assessment of the accuracy of such remote sensing methods in the monitoring of the Baltic ecosystem (see Darecki et al. 2008 - this issue).

14

Remote sensing of vertical phytoplankton pigment distributions in the Baltic: new mathematical expressions. Part 3: Nonphotosynthetic pigment absorption factor

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

Oceanologia

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2007

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No. 49 (4)

513-526

EN

This paper, part 3 of the description of vertical pigment distributions in the Baltic Sea, discusses the mathematical expression enabling the vertical distributions of the non-photosynthetic pigment absorption factor fa to be estimated. The factor fa is directly related to concentrations of the several groups of phytoplankton pigments and describes quantitatively the ratio of the light energy absorbed at given depths by photosynthetic pigments to the light energy absorbed by all the phytoplankton pigments together (photosynthetic and photoprotecting). Knowledge of this factor is highly desirable in the construction of state-of-the-art "light-photosynthesis" models for remote-sensing purposes. The expression enables fa to be estimated with considerable precision on the basis of two surface parameters (available from satellite observations): the total chlorophyll a concentration at the surface Ca(0) and the spectral downward irradiance Ed(?, 0) just below the sea surface. The expression is applicable to Baltic waters from the surface down to an optical depth of ? ? 5. The verification of the model description of fa was based on 400 quasi-empirical values of this factor which were calculated on the basis of empirical values of the following parameters measured at the same depths: Ed(?, z) (or also PAR(z)), apl(?, z), and the concentrations of all the groups of phytoplankton pigments Ca(z) and Cj(z) (where j denotes in turn chl b, chl c, PSC, phyc, PPC). The verification shows that the errors in the values of the non-photosynthetic pigment absorption factor fa estimated using the model developed in this work are small: in practice they do not exceed 4%. Besides the mathematical description of the vertical distribution of fa, this paper also discusses the range of variation of its values measured in the Baltic and its dependence on the trophic index of a basin and depth in the sea. In addition, the similarities and differences in the behaviour of fa in Baltic and oceanic basins are compared.

15

Remote sensing of vertical phytoplankton pigment distributions in the Baltic: new mathematical expressions. Part 1: Total chlorophyll a distribution

Ostrowska M., Majchrowski R., Stoń-Egiert J., Woźniak B., Ficek D., Dera J.

Oceanologia

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2007

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No. 49 (4)

471-489

EN

This article is the first in a series of three describing the modelling of the vertical different photosynthetic and photoprotecting phytoplankton pigments concentration distributions in the Baltic and their interrelations described by the so-called non-photosynthetic pigment factor. The model formulas yielded by this research are an integral part of the algorithms used in the remote sensing of the Baltic ecosystem. Algorithms of this kind have already been developed by our team from data relating mainly to oceanic Case 1 waters (WC1) and have produced good results for these waters. But their application to Baltic waters, i.e., Case 2 waters, was not so successful. On the basis of empirical data for the Baltic Sea, we therefore derived new mathematical expressions for the spatial distribution of Baltic phytoplankton pigments. They are discussed in this series of articles. This first article presents a statistical model for determining the total concentration of chlorophyll, a (i.e., the sum of chlorophylls a+pheo derived spectrophotometrically) at different depths in the Baltic Sea Ca(z) on the basis of its surface concentration Ca(0), which can be determined by remote sensing. This model accounts for the principal features of the vertical distributions of chlorophyll concentrations characteristic of the Baltic Sea. The model's precision was verified empirically: it was found suitable for application in the efficient monitoring of the Baltic Sea. The modified mathematical descriptions of the concentrations of accessory pigments (photosynthetic and photoprotecting) in Baltic phytoplankton and selected relationships between them are given in the other two articles in this series (Majchrowski et al. 2007, Woźniak et al. 2007b, both in this volume).

16

Remote sensing of vertical phytoplankton pigment distributions in the Baltic: new mathematical expressions. Part 2: Accessory pigment distribution

Majchrowski R., Stoń-Egiert J., Ostrowska M., Woźniak B., Ficek D., Lednicka B., Dera J.

Oceanologia

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2007

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No. 49 (4)

491-511

EN

This is the second in a series of articles, the aim of which is to derive mathematical expressions describing the vertical distributions of the concentrations of different groups of phytoplankton pigments; these expressions are necessary in the algorithms for the remote sensing of the marine ecosystem. It presents formulas for the vertical profiles of the following groups of accessory phytoplankton pigments: chlorophylls b, chlorophylls c, phycobilins, photosynthetic carotenoids and photoprotecting carotenoids, all for the uppermost layer of water in the Baltic Sea with an optical depth of ? ? 5. The mathematical expressions for the first four of these five groups of pigments, classified as photosynthetic pigments, enable their concentrations to be estimated at different optical depths in the sea from known surface concentrations of chlorophyll a. The precision of these estimates is characterised by the following relative statistical errors according to logarithmic statistics ?_: approximately 44% for chlorophyll b, approx. 39% for chlorophyll c, approx. 43% for phycobilins and approx. 45% for photosynthetic carotenoids. On the other hand, the mathematical expressions describing the vertical distributions of photoprotecting carotenoid concentrations enable these to be estimated at different depths in the sea also from known surface concentrations of chlorophyll a, but additionally from known values of the irradiance in the PAR spectral range at the sea surface, with a statistical error ?_ of approximately 42%.

17

Quantum yield of photosynthesis in the Baltic : a new mathematical expression for remote sensing applications

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

Oceanologia

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2007

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No. 49 (4)

527-542

EN

Statistical relationships between the quantum yield of photosynthesis ? and selected environmental factors in the Baltic have been established on the basis of a large quantity of empirical data. The model formula is the product of the theoretical maximum quantum yield [formula]. To a sufficiently good approximation, each of these factors fi appears to be dependent on one or at most two environmental factors, such as temperature, underwater irradiance, surface concentration of chlorophyll a, absorption properties of phytoplankton and optical depth. These dependences have been determined for Baltic Case 2 waters. The quantum yield ?, calculated from known values of these environmental factors, is then applicable in the model algorithm for the remote sensing of Baltic primary production. The statistical error of the approximate quantum yields [Fi} is 62%.

18

Modelling the light absorption properties of particulate matter forming organic particles suspended in sea water. Part 3. Practical applications

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

Oceanologia

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2006

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No. 48 (4)

479-507

EN

This paper brings to a close our cycle of articles on modelling the light absorption properties of particulate organic matter (POM) in the sea. In the first two parts of this cycle (Woźniak et al. 2005a,b) we discussed these properties with reference to various model chemical classes and physical types of POM. We have put these results into practice in the present third part. As a result of the appropriate theoretical speculations, logically underpinned by empirical knowledge, we selected 25 morphological variants of marine organic detritus, to which we ascribed definite chemical compositions and physical types. On this basis and using known spectra of the mass-specific coefficients of light absorption by various naturally occurring organic substances (systematised in Parts 1 and 2), we determined the absorption properties of these 25 morphological groups of particles, that is, the spectra of the imaginary part of the refractive index n'p(?) (in the 200-700 nm range) of the particulate matter. They can be applied, with the aid of Mie's or some other similar theory, to calculate the bulk optical properties (absorbing and scattering) of such sets of particles in the sea.

19

Modelling the light absorption properties of particulate matter forming organic particles suspended in seawater. Part 2. Modelling results

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

Oceanologia

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2005

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No. 47 (4)

621-662

EN

Model spectra of mass-specific absorption coefficients a*OM(?) were established for 26 naturally occurring organic substances or their possible mixtures, capable of forming particulate organic matter (POM) in the sea. An algorithm was constructed, and the set of spectra of a*OM(?) was used to determine the spectra of the imaginary part of the complex refractive index n'p(?) characteristic of different physical types and chemical classes of POM commonly occurring in sea water. The variability in the spectra and absolute values of n'p for the various model classes and types of POM was shown to range over many orders of magnitude. This implies that modelling the optical properties of sea water requires a multi-component approach that takes account of the numerous living and non-living fractions of POM, each of which has a different value of n'p.

20

Spectra of light absorption by phytoplankton pigments in the Baltic; conclusions to be drawn from a Gaussian analysis of empirical data

Ficek D., Kaczmarek S., Stoń-Egiert J., Woźniak B., Majchrowski R., Dera J.

Oceanologia

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2004

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No. 46 (4)

533-555

EN

Analysed by differential spectroscopy, 1208 empirical spectra of light absorption apl(?) by Baltic phytoplankton were spectrally decomposed into 26 elementary Gaussian component bands. At the same time the composition and concentrations of each of the 5 main groups of pigments (chlorophylls a, chlorophylls b, chlorophylls c, photosynthetic carotenoids and photoprotecting carotenoids) were analysed in 782 samples by HPLC. Inspection of the correlations between the intensities of the 26 elementary absorption bands and the concentrations of the pigment groups resulted in given elementary bands being attributed to particular pigment groups and the spectra of the mass-specific absorption coefficients established for these pigment groups. Moreover, balancing the absorption effects due to these 5 pigment groups against the overall absorption spectra of phytoplankton suggested the presence of a sixth group of pigments, as yet unidentified (UP), undetected by HPLC. A preliminary mathematical description of the spectral absorption properties of these UP was established. Like some forms of phycobilins, these pigments are strong absorbers in the 450-650 nm spectral region. The packaging effect of pigments in Baltic phytoplankton was analysed statistically, then correlated with the concentration of chlorophyll a in Baltic water. As a result, a Baltic version of the algorithm of light absorption by phytoplankton could be developed. This algorithm can be applied to estimate overall phytoplankton absorption spectra and their components due to the various groups of pigments from a knowledge of their concentrations in Baltic water.