Zoobenthos and oceanographical parameters in the Kemskaya Guba (Bay) - estuary of the Kem' River entering the Onega Bay, White Sea

Data on distribution of zoobenthos in the Kemskaya Guba (or Kemskaya Bay - the estuary of the Kem' River entering the Onega Bay of the White Sea), which is strongly influenced by river runoff, are presented. The number of species at sampling stations varied from 4 to 65. Density of communities and zoobenthos biomass varied from 342±68 to 4293±96 #/m**2 and from 0.418±0.081 to 1975.22±494.36 g/m**2, respectively. Shannon index values varied between 1.19 to 4.7 bit/ind. At the upper part of the estuary, detritivores dominated, while in the central part and at outlets sestonophages prevailed. Changes in quantitative parameters of the zoobenthos along gradient of water salinity were traced, and relations of these parameters with seven other environmental factors were revealed. It was found that species composition, biodiversity, and trophic structure of the zoobenthos significantly correlated with some of parameters mentioned above. Multiple regression analysis was used to assess combined effect of factors, and it revealed which of them played a determining role in Kemskaya Guba: for species composition - depth, water color, and total concentration of suspended matter; for number of species - contents of <0.01 mm grain size (pelite) fraction and organic carbon in bottom sediments. Biomass depended on water salinity, water chromaticity, and organic carbon contents in bottom sediments and suspended matter. Values of the Shannon index of diversity are determined by water color, and contents of organic carbon and pelite fraction in bottom sediments. Calculations of ecological stress values revealed two zones with unstable state of the zoobenthos.

High resolution color reflectance and hematite and goethite record of ODP Hole 184-1143A in the South China Sea

Precipitation has a larger variability than temperature in tropical monsoon regions, thus it is an important climate variable. However, reconstructions of long-term rainfall histories are scarce because of the lack of reliable proxies. Here we document that iron oxide minerals, specifically the ratio of hematite to goethite (Hm/Gt), is a reasonable precipitation proxy. Using diffuse reflectance spectrophotometry, we measured samples from Ocean Drilling Program (ODP) 1143 drilling site (9°21.72'N, 113°17.11'E, 2777 m water depth) for hematite and goethite, whose formation processes are favored by opposing climate conditions. In order to determine the content of hematite and goethite we produced a set of calibration samples by removing the iron oxides to generate the natural matrix to which hematite and goethite in known percentages were added. From these calibration samples we developed a transfer function for determining hematite and goethite concentration from a sample's spectral reflectance. Applying this method to ODP 1143 sediments (top 34 m of a 510 m core with sampling interval of 10 cm) we were able to reconstruct a continuous precipitation history for SE Asia of the past 600 kyr using the Hm/Gt ratio as a proxy of the precipitation variability of Asian monsoon. The reliability of this Hm/Gt proxy is corroborated by its consistency with the stalagmite delta18O data from South China. Comparing long-term Hm/Gt records with the surface temperature gradient of equatorial Pacific Ocean, we found that monsoon precipitation and El Niño are correlated for the last 600 kyr. The development of El Niño-like conditions decreased SE Asia precipitation, whereas precipitation increases in response to La Niña intensification

Shipborne ocean color remote sensing

In this paper, modernized shipborne procedures are presented to collect and process above-water radiometry for remote sensing applications. A setup of five radiometers and a bidirectional camera system, which provides panoramic sea surface and sky images, is proposed for the collection of high-resolution radiometric quantities. Images from the camera system can be used to determine sky state and potential glint, whitecaps, or foam contamination. A peak in the observed remote sensing reflectance RRS spectra between 750-780 nm was typically found in spectra with relatively high surface reflected glint (SRG), which suggests this waveband could be a useful SRG indicator. Simplified steps for computing uncertainties in SRG corrected RRS are proposed and discussed. The potential of utilizing "unweighted multimodel averaging," which is the average of four or more common SRG correction models, is examined to determine the best approximation RRS. This best approximation RRS provides an estimate of RRS based on various SRG correction models established using radiative transfer simulations and field investigations. Applying the average RRS provides a measure of the inherent uncertainties or biases that result from a user subjectively choosing any one SRG correction model. Comparisons between inherent and apparent optical property derived observations were used to assess the robustness of the SRG multimodel averaging ap- proach. Correlations among the standard SRG models were completed to determine the degree of association or similarities between the SRG models. Results suggest that the choice of glint models strongly affects derived RRS values and can also influence the blue to green band ratios used for modeling biogeochemical parameters such as for chlorophyll a. The objective here is to present a uniform and traceable methodology for determining ship- borne RRS measurements and its associated errors due to glint correction and to ensure the direct comparability of these measurements in future investigations. We encourage the ocean color community to publish radiometric field measurements with matching and complete metadata in open access repositories.