Animation of micro-computed tomography of bioerosion trace Entobia megastoma made by East Australian bioeroding sponge Cliona celata

Endolithic bioerosion is difficult to analyse and to describe, and it usually requires damaging of the sample material. Sponge erosion (Entobia) may be one of the most difficult to evaluate as it is simultaneously macroscopically inhomogeneous and microstructurally intricate. We studied the bioerosion traces of the two Australian sponges Cliona celata Grant, 1826 (sensu Schönberg 2000) and Cliona orientalis Thiele, 1900 with a newly available radiographic technology: high resolution X-ray micro-computed tomography (MCT). MCT allows non-destructive visualisation of live and dead structures in three dimensions and was compared to traditional microscopic methods. MCT and microscopy showed that C. celata bioerosion was more intense in the centre and branched out in the periphery. In contrast, C. orientalis produced a dense, even trace meshwork and caused an overall more intense erosion pattern than C. celata. Extended pioneering filaments were not usually found at the margins of the studied sponge erosion, but branches ended abruptly or tapered to points. Results obtained with MCT were similar in quality to observations from transparent optical spar under the dissecting microscope. Microstructures could not be resolved as well as with e.g. scanning electron microscopy (SEM). Even though sponge scars and sponge chips were easily recognisable on maximum magnification MCT images, they lacked the detail that is available from SEM. Other drawbacks of MCT involve high costs and presently limited access. Even though MCT cannot presently replace traditional techniques such as corrosion casts viewed by SEM, we obtained valuable information. Especially for the possibility to measure endolithic pore volumes, we regard MCT as a very promising tool that will continue to be optimised. A combination of different methods will produce the best results in the study of Entobia.

Geological map of SIRINUTEN, Heimefrontfjella, Antarctica (Scale 1:25,000)

Topographic data of this geological map were obtained through stereoscopic aerial photo interpretation. The photogrammetric photo flights were undertaken in 1986 by the Institut für Angewandte Geodäsie, Frankfurt. Horizontal ground control points required for aerial photo interpretation were determined by means of Doppler satellite observation during the 2nd German Neuschwabenland Expedition 1985/86. Vertical ground control points were taken from unpublished map drafts at 1:100 000 scale by Norsk Polarinstitutt, Oslo. The elevation above mean sea level was transferred to Heimefrontfjella barometrically. For this reason assertions concerning the absolute elevation (referred to sea level) are uncertain. Contours and spot heights presented on the map were obtained from the photogrammetric evaluation of the photography taken in 1986; relative elevation data (hight differences) are accurate to approximately ±10 m.

Geological map of NORUMNUTEN, Heimefrontfjella, Antarctica (Scale 1:25,000)

Topographic data of this geological map were obtained through stereoscopic aerial photo interpretation. The photogrammetric photo flights were undertaken in 1986 by the Institut für Angewandte Geodäsie, Frankfurt. Horizontal ground control points required for aerial photo interpretation were determined by means of Doppler satellite observation during the 2nd German Neuschwabenland Expedition 1985/86. Vertical ground control points were taken from unpublished map drafts at 1:100 000 scale by Norsk Polarinstitutt, Oslo. The elevation above mean sea level was transferred to Heimefrontfjella barometrically. For this reason assertions concerning the absolute elevation (referred to sea level) are uncertain. Contours and spot heights presented on the map were obtained from the photogrammetric evaluation of the photography taken in 1986; relative elevation data (hight differences) are accurate to approximately ±10 m.

Simulated temperature changes as a result of Antarctic ice sheet growth and CO2 reduction

During the Middle Miocene climate transition about 14 million years ago, the Antarctic ice sheet expanded to near-modern volume. Surprisingly, this ice sheet growth was accompanied by a warming in the surface waters of the Southern Ocean, whereas a slight deep-water temperature increase was delayed by more than 200 thousand years. Here we use a coupled atmosphere-ocean model to assess the relative effects of changes in atmospheric CO2 concentration and ice sheet growth on regional and global temperatures. In the simulations, changes in the wind field associated with the growth of the ice sheet induce changes in ocean circulation, deep-water formation and sea-ice cover that result in sea surface warming and deep-water cooling in large swaths of the Atlantic and Indian ocean sectors of the Southern Ocean. We interpret these changes as the dominant ocean surface response to a 100-thousand-year phase of massive ice growth in Antarctica. A rise in global annual mean temperatures is also seen in response to increased Antarctic ice surface elevation. In contrast, the longer-term surface and deep-water temperature trends are dominated by changes in atmospheric CO2 concentration. We therefore conclude that the climatic and oceanographic impacts of the Miocene expansion of the Antarctic ice sheet are governed by a complex interplay between wind field, ocean circulation and the sea-ice system.

Secchi depth maps for the Baltic Sea, 2003-2012, with links to GeoTIFs

Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.