Near-bottom zooplankton aggregations in Kongsfjorden with link to images from the optical zooplankton sensor MOKI

Near-bottom zooplankton communities have rarely been studied despite numerous reports of high zooplankton concentrations, probably due to methodological constraints. In Kongsfjorden, Svalbard, the near-bottom layer was studied for the first time by combining daytime deployments of a remotely operated vehicle (ROV), the optical zooplankton sensor moored on-sight key species investigation (MOKI), and Tucker trawl sampling. ROV data from the fjord entrance and the inner fjord showed high near-bottom abundances of euphausiids with a mean concentration of 17.3 ± 3.5 n/100 m**3. With the MOKI system, we observed varying numbers of euphausiids, amphipods, chaetognaths, and copepods on the seafloor at six stations. Light-induced zooplankton swarms reached densities in the order of 90,000 (euphausiids), 120,000 (amphipods), and 470,000 ind/m**3 (chaetognaths), whereas older copepodids of Calanus hyperboreus and C. glacialis did not respond to light. They were abundant at the seafloor and 5 m above and showed maximum abundance of 65,000 ind/m**3. Tucker trawl data provided an overview of the seasonal vertical distribution of euphausiids. The most abundant species Thysanoessa inermis reached near-bottom concentrations of 270 ind/m**3. Regional distribution was neither related to depth nor to location in the fjord. The taxa observed were all part of the pelagic community. Our observations suggest the presence of near-bottom macrozooplankton also in other regions and challenge the current view of bentho-pelagic coupling. Neglecting this community may cause severe underestimates of the stock of elagic zooplankton, especially predatory species, which link secondary production with higher trophic levels.

Potential of RapidEye image data for sediment monitoring of the German tidal flats

The Wadden Sea is located in the southeastern part of the North Sea forming an extended intertidal area along the Dutch, German and Danish coast. It is a highly dynamic and largely natural ecosystem influenced by climatic changes and anthropogenic use of the North Sea. Changes in the environment of the Wadden Sea, natural or anthropogenic origin, cannot be monitored by the standard measurement methods alone, because large-area surveys of the intertidal flats are often difficult due to tides, tidal channels and unstable underground. For this reason, remote sensing offers effective monitoring tools. In this study a multi-sensor concept for classification of intertidal areas in the Wadden Sea has been developed. Basis for this method is a combined analysis of RapidEye (RE) and TerraSAR-X (TSX) satellite data coupled with ancillary vector data about the distribution of vegetation, mussel beds and sediments. The classification of the vegetation and mussel beds is based on a decision tree and a set of hierarchically structured algorithms which use object and texture features. The sediments are classified by an algorithm which uses thresholds and a majority filter. Further improvements focus on radiometric enhancement and atmospheric correction. First results show that we are able to identify vegetation and mussel beds with the use of multi-sensor remote sensing. The classification of the sediments in the tidal flats is a challenge compared to vegetation and mussel beds. The results demonstrate that the sediments cannot be classified with high accuracy by their spectral properties alone due to their similarity which is predominately caused by their water content.

Airborne hyperspectral image data of Heron Reef, Australia

This airborne hyperspectral (19 bands) image data of Heron Reef, Great Barrier Reef, Australia is derived from Compact Airborne Spectrographic Imager (CASI) data acquired on 1st and 3rd of July 2002, latitude -23.45, longitude 151.92. Processing and correction to at-surface data was completed by Karen Joyce (Joyce, 2004). Raw imagery consisted several images corresponding to the number of flight paths taken to cover the entire Heron Reef. Spatial resolution is one meter. Radiometric corrections converted the at-sensor digital number values to at surface spectral radiance values using sensor specific calibration coefficients and CSIRO's c-WomBat-c atmospheric correction software. Geometric corrections were done using field collected coordinates of features identified in the image. Projection used was Universal Transverse Mercator Zone 56 South and Datum used was WGS 84. Image data is in TIFF format.

Core scan image analysis corrected for cracks, ODP Hole 154-926C

Drill cores are essential for the study of deep-sea sediments and on-land sites because often no suitable outcrop is available or accessible. These cores form the backbone of stratigraphical studies using and combining various dating techniques. Cyclostratigraphy is usually based on fast and inexpensive measurements of physical sediment properties. One indirect but highly valuable proxy for reconstructing the sediment composition and variability is sediment color. However, cracks and other disturbances in sediment cores may dramatically influence the quality of color data retrieved either directly from photospectrometry or derived from core image analysis. Here we present simple but powerful algorithms to extract color data from core images, and focus on routines to exclude cracks from these images. Results are discussed using the example of an ODP core from the Ceara Rise in the Central Atlantic. The crack correction approach presented highly improves the quality of color data and allows the easy incorporation of cracked cores into studies based on core images. This facilitates the quick and inexpensive generation of large color datasets directly from quantified core images, for cyclostratigraphy and other purposes.