Downwelling spectral irradiance as measured in different depths, remote sensing reflectance and phytoplankton pigment concentration during POLARSTERN cruises ANT-XXIV/1, ANT-XXIV/4, ANT-XXVI/4 and Maria S. Merian cruise MSM18/3

The composition and abundance of algal pigments provide information on phytoplankton community characteristics such as photoacclimation, overall biomass and taxonomic composition. In particular, pigments play a major role in photoprotection and in the light-driven part of photosynthesis. Most phytoplankton pigments can be measured by high-performance liquid chromatography (HPLC) techniques applied to filtered water samples. This method, as well as other laboratory analyses, is time consuming and therefore limits the number of samples that can be processed in a given time. In order to receive information on phytoplankton pigment composition with a higher temporal and spatial resolution, we have developed a method to assess pigment concentrations from continuous optical measurements. The method applies an empirical orthogonal function (EOF) analysis to remote-sensing reflectance data derived from ship-based hyperspectral underwater radiometry and from multispectral satellite data (using the Medium Resolution Imaging Spectrometer - MERIS - Polymer product developed by Steinmetz et al., 2011, doi:10.1364/OE.19.009783) measured in the Atlantic Ocean. Subsequently we developed multiple linear regression models with measured (collocated) pigment concentrations as the response variable and EOF loadings as predictor variables. The model results show that surface concentrations of a suite of pigments and pigment groups can be well predicted from the ship-based reflectance measurements, even when only a multispectral resolution is chosen (i.e., eight bands, similar to those used by MERIS). Based on the MERIS reflectance data, concentrations of total and monovinyl chlorophyll a and the groups of photoprotective and photosynthetic carotenoids can be predicted with high quality. As a demonstration of the utility of the approach, the fitted model based on satellite reflectance data as input was applied to 1 month of MERIS Polymer data to predict the concentration of those pigment groups for the whole eastern tropical Atlantic area. Bootstrapping explorations of cross-validation error indicate that the method can produce reliable predictions with relatively small data sets (e.g., < 50 collocated values of reflectance and pigment concentration). The method allows for the derivation of time series from continuous reflectance data of various pigment groups at various regions, which can be used to study variability and change of phytoplankton composition and photophysiology.

Compilation of measurements from two interdisciplinary STAR-shaped surveys in the North Sea: The ZISCH - Dataset

The measurements were obtained during two North Sea wide STAR-shaped cruises during summer 1986 and winter 1987, which were performed to investigate the circulation induced transport and biologically induced pollutant transfer within the interdisciplinary research in the project "ZISCH - Zirkulation und Schadstoffumsatz in der Nordsee / Circulation and Contaminant Fluxes in the North Sea (1984-1989)". The inventory presents parameters measured on hydrodynamics, nutrient dynamics, ecosystem dynamics and pollutant dynamics in the pelagic and benthic realm. The research program had the objective of quantifying fluxes of major budgets, especially contaminants in the North Sea. In spring 1986, following the phytoplankton spring bloom, and in late winter 1987, at minimum primary production activity, the North Sea ecosystem was investigated on a station net covering the whole North Sea. The station net was shaped like a star. Sampling started in the centre, followed by the northwest section and moving counter clockwise around the North Sea following the residual currents. By this strategy, a time series was measured in the central North Sea and more synoptic data sets were obtained in the individual sections. Generally advection processes have to be considered when comparing the data from different stations. The entire sampling period lasted for more than six weeks in each cruise. Thus, a time-lag should be considered especially when comparing the data from the eastern and the western part of the central and northern North Sea, where samples were taken at the beginning and at the end of the campaign. The ZISCH investigations represented a qualitatively and quantitatively new approach to North Sea research in several respects. (1) The first simultaneous blanket coverage of all important biological, chemical and physical parameters in the entire North Sea ecosystem; (2) the first simultaneous measurements of major contaminants (metals and organohaline compounds) in the different ecosystem compartments; (3) simultaneous determinations of atmospheric inputs of momentum, energy and matter as important ecosystem boundary conditions; (4) performance of the complex measurement program during two seasons, namely the spring plankton bloom and the subsequent winter period of minimal biological activity; and (5) support of data analysis and interpretation by oceanographic and meteorological numerical models on the same scales.

Amino acid racemization of Neogloboquadrina pachyderma from the Arctic Ocean

The long-term rate of racemization for amino acids preserved in planktonic foraminifera was determined by using independently dated sediment cores from the Arctic Ocean. The racemization rates for aspartic acid (Asp) and glutamic acid (Glu) in the common taxon, Neogloboquadrina pachyderma, were calibrated for the last 150 ka using 14C ages and the emerging Quaternary chronostratigraphy of Arctic Ocean sediments. An analysis of errors indicates realistic age uncertainties of about ±12% for Asp and ±17% for Glu. Fifty individual tests are sufficient to analyze multiple subsamples, identify outliers, and derive robust sample mean values. The new age equation can be applied to verify and refine age models for sediment cores elsewhere in the Arctic Ocean, a critical region for understanding the dynamics of global climate change.