Control of primary productivity and the significance of photosynthetic bacteria in a meromictic kettle lake.

During 1986 planktonic primary production and controlling factors were investigated in a small (A0 = 11.8 · 103 m2, Zmax = 11.5 m) meromictic kettle lake (Mittlerer Buchensee). Annual phytoplankton productivity was estimated to ca 120 gC · m–2 · a–1 (1,42 tC · lake–1 · a–1). The marked thermal stratification of the lake led to irregular vertical distributions of chlorophylla concentrations (Chla) and, to a minor extent, of photosynthesis (Az). Between the depths of 0 to 6 m low Chla concentrations (< 7 mg · m–3) and comparatively high background light attenuation (kw = 0,525 m–1, 77% of total attenuation due to gelbstoff and abioseston) was found. As a consequence, light absorption by algae was low (mean value 17,4%) and self-shading was absent. Because of the small seasonal variation of Chla concentrations, no significant correlation between Chla and areal photosynthesis (A) was observed. Only in early summer (June–July) biomass appears to influence the vertical distribution of photosynthesis on a bigger scale. Around 8 m depth, low-light adapted algae and phototrophic bacteria formed dense layers. Due to low ambient irradiances, the contribution of these organisms to total primary productivity was small. Primary production and incident irradiance were significantly correlated with each other (r2 = 0.68). Although the maximum assimilation number (Popt) showed a clear dependence upon water temperature (Q10 = 2.31), the latter was of minor importance to areal photosynthesis

Copernicus Marine Service Ocean State Report

This is the final version. Available from Taylor & Francis via the DOI in this record

Nitrogen- and irradiance-dependent variations of the maximum quantum yield of carbon fixation in eutrophic, mesotrophic and oligotrophic marine systems

International audienceNatural variability of the maximum quantum yield of carbon fixation (phi C-max), as determined from the initial slope of the photosynthesis-irradiance curve and from light absorption measurements, was studied at three sites in the northeast tropical Atlantic representing typical eutrophic, mesotrophic and oligotrophic regimes. At the eutrophic and mesotrophic sites, where the mixed layer extended deeper than the euphotic layer, all photosynthetic parameters were nearly constant with depth, and phi C-max averaged between 0.05 and 0.03 mol C (mel quanta absorbed)(-1), respectively. At the oligotrophic site, a deep chlorophyll maximum (DCM) existed and phi C-max varied from ca 0.005 in the upper nutrient-depleted mixed layer to 0.063 below the DCM in stratified waters. Firstly, phi C-max was found roughly to covary with nitrate concentration between sites and with depth at the oligotrophic site, and secondly, it was found to decrease with increasing relative concentrations of non-photosynthetic pigments. The extent of phi C-max variations directly related to nitrate concentration was inferred from variations in the fraction of functional PS2 reaction centers (f), measured using fast repetition rate fluorometry. Covariations between f and nitrate concentration indicate that the latter factor may be responsible for a 2-fold variation in phi C-max. Moreover, partitioning light absorption between photosynthetic and non-photosynthetic pigments suggests that the variable contribution of the non-photosynthetic absorption may explain a 3-fold variation in phi C-max, as indicated by variations in the effective absorption cross-section of photosystem 2 (sigma(PS2)). Results confirm the role of nitrate in phi C-max variation, and emphasize those of light and vertical mixing. Copyright (C) 1996 Elsevier Science Lt

Estimation of phytoplankton concentration from downwelling irradiance measurements in water

The downwelling irradiance spectrum is so far not used directly for the determination of water constituents, mainly due to the large and unpredictable fluctuations of the underwater light field induced by the water surface. The potential of a new analytical model, which can cope with such environmental influences, was analyzed for the estimation of phytoplankton concentration using data from two German lakes. It turned out that the model is able to determine in these lakes phytoplankton concentration above a threshold between 0.4 and 0.9 µg/l, depending on the phytoplankton class, and total pigment concentration (sum of chlorophyll-a and phaeophytin-a) with an uncertainty of 0.7 µg/l. This new in situ spectroscopy method is particularily of interest for shallow waters, where it is difficult to apply the usual reflectance-based algorithms due to bottom influences

An Empirical Algorithm for Light Absorption by Ocean Water Based on Color

Empirical algorithms for the total absorption coefficient and absorption coefficient by pigments for surface waters at 440 nm were developed by applying a quadratic formula that combines two spectral ratios of remote-sensing reflectance. For total absorption coefficients ranging from 0.02 to 2.0 m(-1), a goodness of fit was achieved between the measured and modeled data with a root-mean-square difference between the measured and modeled values for log10 scale (RMSDlog10) of 0.062 (15.3% for linear scale, number of samples N = 63), while RMSDlog10 is 0.111 (29.1% for linear scale, N = 126) for pigment absorption (ranging from 0.01 to 1.0 m(-1)). As alternatives to pigment concentration algorithms, the absorption algorithms developed can be applied to the coastal zone color scanner and sea-viewing wide-field-of-view sensor data to derive inherent optical properties of the ocean, For the same data sets, we also directly related the chlorophyll a concentrations to the spectral ratios and obtained an RMSDlog10 value of 0.218 (65.2% for linear scale, N = 120) for concentrations ranging from 0.06 to 50.0 mg m(-3). These results indicate that it is more accurate to estimate the absorption coefficients than the pigment concentrations from remotely sensed data. This is likely due to the fact that for. the broad range of waters studied the pigment-specific absorption coefficient at 440 nm ranged from 0.03 to 0.2 m(2) (mg chl)(-1). As an indirect test of the algorithms developed, the chlorophyll a concentration algorithm is applied to an independent global data set and an RMSDlog10 of 0.191 (55.2% for linear scale, N = 919) is obtained. There is no independent global absorption data set available as yet to test the absorption algorithms

Semianalytic Moderate-Resolution Imaging Spectrometer Algorithms for Chlorophyll \u3cem\u3ea\u3c/em\u3e and Absorption with Bio-Optical Domains Based on Nitrate-Depletion Temperatures

This paper describes algorithms for retrieval of chlorophyll a concentration and phytoplankton and gelbstoff absorption coefficients for the Moderate-Resolution Imaging Spectrometer (MODIS) or sensors with similar spectral channels. The algorithms are based on a semianalytical, bio-optical model of remote sensing reflectance, Rrs([lambda]). The Rrs([lambda]) model has two free variables, the absorption coefficient due to phytoplankton at 675 nn, a[Phi](675), and the absorption coefficient due to gelbstoff at 400 nm, ag(400). The Rrs model has several parameters that are fixed or can be specified based on the region and season of the MODIS scene. These control the spectral shapes of the optical constituents of the model. Rrs([lambda]i) values from the MODIS data processing system are placed into the model, the model is inverted, and a[Phi](675), ag(400), and chlorophyll a are computed. The algorithm also derives the total absorption coefficients a([lambda]i) and the phytoplankton absorption coefficients a[Phi]([lambda]i) at the visible MODIS wavelengths. MODIS algorithms are parameterized for three different bio-optical domains: (1) high photoprotective pigment to chlorophyll ratio and low self-shading, which for brevity, we designate as unpackaged ; (2) low photoprotective pigment to chlorophyll ratio and high self shading, which we designate as packaged ; and (3) a transitional or global-average type. These domains can be identified from space by comparing sea-surface temperature to nitrogen-depletion temperatures for each domain. Algorithm errors of more than 45% are reduced to errors of less than 30% with this approach, with the greatest effect occurring at the eastern and polar boundaries of the basins