The pigment phycocyanin (PC) is a marker for cyanobacterial presence in eutrophic inland water. We present a reflectance band-ratio algorithm for retrieval of cyanobacterial PC. The model conforms to the band settings of the Medium Resolution Imaging Spectrometer. The parameters of the algorithm were optimized using reflectance and absorption data from two highly eutrophic lakes. Using measured specific absorption coefficients for PC [a (620)] * pc for every sample, the error in the predicted PC concentrations was 19.7% (r 2 ϭ 0.94, n ϭ 34) for measured PC concentrations up to 80 mg m Ϫ3 . Applying a fixed value of a (620) caused an overestimation of the PC content * pc that increased toward lower PC concentrations. The PC prediction best matched observed values during periods of high relative abundance of cyanobacteria in the plankton community. The results suggest strong seasonal variation in a (620). The presence of pigments other than PC and chlorophyll a (Chl a) and a variable influence of Chl a * pc on retrieved absorption at 620 nm are potential causes of errors in PC retrieval. The algorithm in its current form is considered to be suitable for detection of the PC concentration in turbid, cyanobacteria-dominated waters.Eutrophic inland waters often exhibit blooms of cyanobacteria. Notorious for their negative impact on water quality, cyanobacterial blooms have been increasingly subject of water management and scientific studies. The hazards of toxic cyanobacterial blooms call for frequent and rapid monitoring of water bodies. Remote sensing provides insights into the distribution of blooms for a large number of lakes or reservoirs simultaneously. The concentration of chlorophyll a (Chl a) as a general indicator for plankton biomass can be assessed using imagery from a wide range of air-and spaceborn sensors (Vos et al. 2003). Recent advances in spaceborn remote sensing technology broaden the perspectives of monitoring toward the identification and quantification of plankton groups. Algorithms for the retrieval of Chl a from turbid water reflectance were already being developed (Gons et al. 2002). Now, the retrieval of the pigment phycocyanin (PC), which is characteristic of the presence of cyanobacterial, is being attempted. It is known that the presence of PC can be detected from spectral reflectance (Dekker et al.

Marine phytoplankton account for about 50% of all global net primary productivity (NPP). Active fluorometry, mainly Fast Repetition Rate fluorometry (FRRf), has been advocated as means of providing high resolution estimates of NPP. However, not measuring CO2-fixation directly, FRRf instead provides photosynthetic quantum efficiency estimates from which electron transfer rates (ETR) and ultimately CO2-fixation rates can be derived. Consequently, conversions of ETRs to CO2-fixation requires knowledge of the electron requirement for carbon fixation (Φe,C, ETR/CO2 uptake rate) and its dependence on environmental gradients. Such knowledge is critical for large scale implementation of active fluorescence to better characterise CO2-uptake. Here we examine the variability of experimentally determined Φe,C values in relation to key environmental variables with the aim of developing new working algorithms for the calculation of Φe,C from environmental variables. Coincident FRRf and 14C-uptake and environmental data from 14 studies covering 12 marine regions were analysed via a meta-analytical, non-parametric, multivariate approach. Combining all studies, Φe,C varied between 1.15 and 54.2 mol e− (mol C)−1 with a mean of 10.9±6.91 mol e− mol C)−1. Although variability of Φe,C was related to environmental gradients at global scales, region-specific analyses provided far improved predictive capability. However, use of regional Φ e,C algorithms requires objective means of defining regions of interest, which remains challenging. Considering individual studies and specific small-scale regions, temperature, nutrient and light availability were correlated with Φ e,C albeit to varying degrees and depending on the study/region and the composition of the extant phytoplankton community. At the level of large biogeographic regions and distinct water masses, Φ e,C was related to nutrient availability, chlorophyll, as well as temperature and/or salinity in most regions, while light availability was also important in Baltic Sea and shelf waters. The novel Φ e,C algorithms provide a major step forward for widespread fluorometry-based NPP estimates and highlight the need for further studying the natural variability of Φe,C to verify and develop algorithms with improved accuracy.

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Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in-water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n 5 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions.

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