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

Meler, Justyna; Ostrowska, Mirosława; Ficek, Dariusz; Zdun, Agnieszka

doi:10.1016/j.oceano.2017.03.010

Cited by 12 publications

(11 citation statements)

References 36 publications

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“…4-13, data were acquired from previous studies and field measurements) (Shi et al, 2011); and (3) Class 3 contains 19 lakes and coastal waters around the world (Nos. 14-32, data were acquired from published articles) (Brunelle et al, 2012;Li et al, 2015;Meler et al, 2017;Meler et al, 2016;Nima et al, 2016;Perez et al, 2011;Perkins et al, 2013;Riddick et al, 2015;Shi et al, 2011;Trochta et al, 2015;Wang et al, 2014;Wang et al, 2005;Ylöstalo et al, 2014). In addition, the NOMAD dataset were also used to make the comparison of optical properties in different oceanic and coastal waters (Werdell and Bailey, 2005).…”

Section: Optical Characteristics Of the Three Large Lakesmentioning

confidence: 99%

Inversion of inherent optical properties in optically complex waters using sentinel-3A/OLCI images: A case study using China's three largest freshwater lakes

Xue

Duan

et al. 2019

Remote Sensing of Environment

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Inherent optical properties (IOPs) play an important role in underwater light field, and are difficult to estimate accurately using satellite data in optically complex waters. To study water quality in appropriate temporal and spatial scales, it is necessary to develop methods to obtain IOPs form space-based observation with quantified uncertainties. Field-measured IOP data (N = 405) were collected from 17 surveys between 2011 and 2017 in the three major largest freshwater lakes of China (Lake Chaohu, Lake Taihu, and Lake Hongze) in the lower reaches of the Yangtze River and Huai River (LYHR). Here we provide a case-study on how to use in-situ observation of IOPs to devise an improved algorithm for retrieval of IOPs. We then apply this algorithm to observation with Sentinel-3A OLCI (Ocean and Land Colour Instrument, corrected with our improved AC scheme), and use in-situ data to show that the algorithm performs better than the standard OLCI IOP product. We use the satellite derived products to study the spatial and seasonal distributions of IOPs and concentrations of optically active constituents in these three lakes, including chlorophyll-a (Chla) and suspended particulate matter (SPM), using all cloud-free OLCI images (115 scenes) over the lakes in the LYHR basin in 2017. Our study provides a strategy for using local and remote observations to obtain important water quality parameters necessary to manage resources such as reservoirs, lakes and coastal waters. water bodies that exhibit large variations in properties (Li et al., 2013). Several solution methods of SAAs have been developed to derive the

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Section: Optical Characteristics Of the Three Large Lakesmentioning

confidence: 99%

Inversion of inherent optical properties in optically complex waters using sentinel-3A/OLCI images: A case study using China's three largest freshwater lakes

Xue

Duan

et al. 2019

Remote Sensing of Environment

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“…On the other hand, another recent paper of ours identified significant differences in the absorption properties of Baltic phytoplankton at different times of the year (Meler et al, 2016b). In a further preliminary study, limited to just the single light wavelength of 440 nm, we demonstrated differences between the coefficients of the relevant simplified parameterizations when they were tailored to data gathered at specific times of the year (Meler et al, 2017b). It is in this context, therefore, that we have decided in the present paper to readdress the problem of determining practical forms of a simplified parameterization of the phytoplankton absorption coefficient appropriate to Baltic Sea conditions.…”

Section: Introductionmentioning

confidence: 49%

“…High performance liquid chromatography (HPLC) was used to determine phytoplankton pigment concentrations; the methodology is described in detail in Meler et al (2017b), Stoń and Kosakowska (2002), and Stoń-Egiert and Kosakowska (2005). In this work we refer mainly to the total chlorophyll a concentration (Tchl a) (defined as the sum of chlorophyll a, allomer and epimer, chlorophyllide a, and phaeophytin a) and to the sum of the concentrations of all accessory pigments C i , i.e.…”

Section: Time Of Open Baltic Coastal Areasmentioning

confidence: 99%

Parameterization of phytoplankton spectral absorption coefficients in the Baltic Sea: general, monthly and two-component variants of approximation formulas

Meler

Woźniak²,

Stoń-Egiert

et al. 2018

Ocean Sci.

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Abstract. This paper presents approximate formulas (empirical equations) for parameterizing the coefficient of light absorption by phytoplankton aph(λ) in Baltic Sea surface waters. Over a thousand absorption spectra (in the 350–750 nm range), recorded during 9 years of research carried out in different months of the year and in various regions of the southern and central Baltic, were used to derive these parameterizations. The empirical material was characterized by a wide range of variability: the total chlorophyll a concentration (Tchl a) varied between 0.31 and 142 mg m−3, the ratio of the sum of all accessory pigment concentrations to chlorophyll a (∑Ci/Tchla) ranged between 0.21 and 1.5, and the absorption coefficients aph(λ) at individual light wavelengths varied over almost 3 orders of magnitude. Different versions of the parameterization formulas were derived on the basis of these data: a one-component parameterization in the “classic” form of a power function with Tchl a as the only variable and a two-component formula – the product of the power and exponential functions – with Tchl a and ∑Ci/Tchla as variables. We found distinct differences between the general version of the one-component parameterization and its variants derived for individual months of the year. In contrast to the general variant of parameterization, the new two-component variant takes account of the variability of pigment composition occurring throughout the year in Baltic phytoplankton populations.

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“…The greater depth heterogeneity of the eastern segment of the lake favored a higher abundance of macroinvertebrates ( Table 2 ). Simultaneously, the depth gradient is an abiotic factor that determines habitat heterogeneity with respect to substrate type, thickness of sediments, access to light and nutrients, or water quality, as those factors directly affect the biotic components of the ecosystem [ 2 , 7 ]. This creates a situation of the structure of benthic fauna inhabiting one reservoir by two, hierarchical systems of environmental predictors.…”

Section: Discussionmentioning

confidence: 99%

“…Shallow polymictic lakes reach an advanced stage of development because almost their entire water volume takes part in most of the energy processes and phenomena, along with a relatively large surface area of active bottom sediments. Such processes are typical of coastal lakes connected with, or isolated from, the sea [ 2 , 3 ]. They are large and shallow, so changes in their morphometric parameters are some of the most important abiotic indicators of evolution of those ecosystems [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Response of Benthic Fauna to Habitat Heterogeneity in a Shallow Temperate Lake

Obolewski

Glińska-Lewczuk

Sidoruk

et al. 2021

Animals

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We investigated the response of benthic macroinvertebrates in the eulittoral, infralittoral, and sublittoral zones, in two segments of the freshwater Lake Wicko on the coast of the Baltic Sea. Our results showed that the morphometry of lakes plays a major role as a factor structuring the macroinvertebrates communities. Two parts of the lake, different in size and depth, show decreasing differences in the trophic state, abundance, diversity and number of indicator species of benthic fauna with the depth gradient. The most significant differences were observed between the littoral zones of both segments. Similar environmental conditions in the sublittoral zones corresponded to the simplified structure of the benthic macroinvertebrates communities. In the infralittoral zone, the most significant differences between the two segments, were recorded for mollusks and large crustaceans as well as the Oligochaeta/Chironomidae abundance ratio. In the sublittoral zone, the diversity of chironomids differed most strongly. Lower species diversity was found in the part of the lake with a slight depth decrease. Shredders reached significantly higher values in eulittoral and infralittoral of the deeper lake segment. Average Score Per Taxon increased with a depth gradient. We recommend testing benthic macroinvertebrates in lakes with different morphometrics individually for each depth zone.

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

Cited by 12 publications

References 36 publications

Inversion of inherent optical properties in optically complex waters using sentinel-3A/OLCI images: A case study using China's three largest freshwater lakes

Inversion of inherent optical properties in optically complex waters using sentinel-3A/OLCI images: A case study using China's three largest freshwater lakes

Parameterization of phytoplankton spectral absorption coefficients in the Baltic Sea: general, monthly and two-component variants of approximation formulas

Response of Benthic Fauna to Habitat Heterogeneity in a Shallow Temperate Lake

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