Water chemistry, and pigments and geochemistry of sediments from northern Victoria Land lakes

Total concentrations of algal pigments, organic C, C, N, P and S were determined in surface sediments from the littoral zone of 21 lakes in ice-free areas of northern Victoria Land (Antarctica) with different climatic and environmental conditions. Concentrations of major ions and nutrients were also determined in water samples from the same lakes. The latter samples had extremely variable chemical compositions; however, all the lakes resulted oligotrophic. Pigment concentrations in surface sediments were comparable to those reported for other Antarctic lakes and lower than those in oligotrophic lakes at lower latitudes. Cyanophyta, Chlorophyta and Bacillariophyta were the main taxa identified. These taxa correspond to those reported in previous microscopy-based studies on Antarctic phytoplankton and phytobenthos. Discriminant Function Analysis and Canonical Correspondence Analysis of data indicate that the distribution of pigments in these Victoria Land lakes depends mainly on their geographical location (particularly the distance from the sea) and nutrient status.

Site characteristics, sediment geochemistry and pigment concentration of northern Victoria Land lakes

Antarctic ice-free areas contain lakes and ponds that have interesting limnological features and are of wide global significance as early warning indicators of climatic and environmental change. However, most limnological and paleolimnological studies in continental Antarctica are limited to certain regions. There are several ice-free areas in Victoria Land that have not yet been studied well. There is therefore a need to extend limnological studies in space and time to understand how different geological and climatic features affect the composition and biological activity of freshwater communities. With the aim of contributing to a better limnological characterization of Victoria Land, this paper reports data on sedimentary pigments (used to identify the main algal taxa) obtained through a methodology that is more sensitive and selective than that of previous studies. Analyses were extended to 48 water bodies in ice-free areas with differing lithology, latitude, and altitude, and with different morphometry and physical, chemical, and biological characteristics in order to identify environmental factors affecting the distribution and composition of freshwater autotrophic communities. A wider knowledge of lakes in a limnologically important region of Antarctica was obtained. Cyanophyta was found to be the most important algal group, followed by Chlorophyta and Bacillariophyta, whereas latitude and altitude are the main factors affecting pigment distribution.

(Table 1) Characteristics of snow pits on De Geerfonna and Vestfonna during the IPY 2007-2010

Extensive glaciological field measurements were carried out on the ice cap Vestfonna as well as on the minor ice body De Geerfonna (Nordaustlandet, Svalbard) within the framework of IPY Kinnvika. Field campaigns were conducted during the period 2007-2010 in spring (April/May) and summer (August). In this study we compile and present snow cover information obtained from 22 snow pits that were dug on Vestfonna during this period. Locations are along two transects on the northwestern, land terminating slope of the ice cap, on its central summit, Ahlmann Summit, and at a set of several other locations in the eastern and northern part of the ice cap. Snow-cover information acquired from four snow pits on adjacent De Geerfonna is also incorporated in this study. Field data are analysed regarding snow stratigraphy, snow density, snow hardness and snow temperature. Results reveal mean snow densities of around 400 kg/m**3 for the snowpack of Vestfonna with no apparent spatial or interannual variability. A distinctly higher value of more than 450 kg/m**3 was obtained for De Geerfonna. A spatial comparison of snow water equivalents above the previous end-of-summer surface serves for obtaining insights into the spatial distribution of snow accumulation across Vestfonna. Altitude was found to be the only significant spatial parameter for controlling snow accumulation across the ice cap.

Benthic cover map of Heron Reef derived from a high-spatial-resolution multi-spectral satellite image using object based image analysis

Providing accurate maps of coral reefs where the spatial scale and labels of the mapped features correspond to map units appropriate for examining biological and geomorphic structures and processes is a major challenge for remote sensing. The objective of this work is to assess the accuracy and relevance of the process used to derive geomorphic zone and benthic community zone maps for three western Pacific coral reefs produced from multi-scale, object-based image analysis (OBIA) of high-spatial-resolution multi-spectral images, guided by field survey data. Three Quickbird-2 multi-spectral data sets from reefs in Australia, Palau and Fiji and georeferenced field photographs were used in a multi-scale segmentation and object-based image classification to map geomorphic zones and benthic community zones. A per-pixel approach was also tested for mapping benthic community zones. Validation of the maps and comparison to past approaches indicated the multi-scale OBIA process enabled field data, operator field experience and a conceptual hierarchical model of the coral reef environment to be linked to provide output maps at geomorphic zone and benthic community scales on coral reefs. The OBIA mapping accuracies were comparable with previously published work using other methods; however, the classes mapped were matched to a predetermined set of features on the reef.

Air photography Samoylov Island

For the qualitative description of surface properties like vegetation cover or land-water-ratio of Samoylov Island as well as for the evaluation of fetch homogeneity considerations of the eddy covariance measurements and for the up-scaling of chamber flux measurements, a detailed surface classification of the island at the sub-polygonal scale is necessary. However, up to know only grey-scale Corona satellite images from the 1960s with a resolution of 2 x 2 m and recent multi-spectral LandSat images with a resolution of 30 x 30 m were available for this region. Both are not useable for the desired classification because of missing spectral information and inadequate resolution, respectively. During the Lena 2003 expedition, a survey of the island by air photography was carried out in order to obtain images for surface classification. The photographs were taken from a helicopter on 10.07.2002, using a Canon EOS100 reflex camera, a Soligor 19-23 mm lens and colour slide film. The height from which the photographs were taken was approximately 600 meters. Due to limited flight time, not all the area of the island could be photographed and some regions could only be photographed with a slanted view. As a result, the images are of a varying quality and resolution. In Potsdam, after processing the films were scanned using a Nikon LS-2000 scanner at maximal resolution setting. This resulted in a ground resolution of the scanned images of approximately 0.3x0.3 m. The images were subsequently geo-referenced using the ENVI software and a referenced Corona image dating from 18.07.1964 (Spott, 2003). Geo-referencing was only possible for the Holocene river terrace areas; the floodplain regions in the western part of the island could not be referenced due to the lack of ground reference points. In Figure 3.7-1, the aerial view of Samoylov Island composed of the geo-referenced images is shown. Further work is necessary for the classification and interpretation of the images. If possible, air photography surveys will be carried out during future expeditions in order to determine changes in surface pattern and composition.

Application of Decision Theory methods for a Community of Madrid Soil classification case

A land classification method was designed for the Community of Madrid (CM), which has lands suitable for either agriculture use or natural spaces. The process started from an extensive previous CM study that contains sets of land attributes with data for 122 types and a minimum-requirements method providing a land quality classification (SQ) for each land. Borrowing some tools from Operations Research (OR) and from Decision Science, that SQ has been complemented by an additive valuation method that involves a more restricted set of 13 representative attributes analysed using Attribute Valuation Functions to obtain a quality index, QI, and by an original composite method that uses a fuzzy set procedure to obtain a combined quality index, CQI, that contains relevant information from both the SQ and the QI methods.

Proteome Analysis Database: online application of InterPro and CluSTr for the functional classification of proteins in whole genomes

The SWISS-PROT group at EBI has developed the Proteome Analysis Database utilising existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archaea and eukaryotes (http://www.ebi.ac.uk/proteome/). The two main projects used, InterPro and CluSTr, give a new perspective on families, domains and sites and cover 31–67% (InterPro statistics) of the proteins from each of the complete genomes. CluSTr covers the three complete eukaryotic genomes and the incomplete human genome data. The Proteome Analysis Database is accompanied by a program that has been designed to carry out InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.