ALBERT

Description: The crabeater seal (Lobodon carcinophaga) is the most abundant Antarctic seal and inhabits the circumpolar pack ice zone of the Southern Ocean. Until now, information on important environmental factors affecting its distribution as well as on foraging behaviour is limited. In austral summer 1998, 12 crabeater seals of both sexes and different age classes were equipped with satellitelinked dive recorders at Drescher Inlet (72.85°S, 19.26°E), eastern Weddell Sea. To identify suitable habitat conditions within the Weddell Sea, a maximum entropy (Maxent) modelling approach was implemented. The model revealed that the eastern and southern Weddell Sea is especially suitable for crabeater seals. Distance to the continental shelf break and sea ice concentration were the two most important parameters in modelling species distribution throughout the study period. Model predictions demonstrated that crabeater seals showed a dynamic response to their seasonally changing environment emphasized by the favoured sea ice conditions. Crabeater seals utilized ice-free waters substantially, which is potentially explained by the comparatively low sea ice cover of the Weddell Sea during summer 1998. Diving behaviour was characterized by short (〉90 % = 0-4 min) and shallow (〉90 % = 0-51 m) dives. This pattern reflects the typical summer and autumn foraging behaviour of crabeater seals. Both the distribution and foraging behaviour corresponded well with the life history of the Antarctic krill (Euphausia superba), the preferred prey of crabeater seals. In general, predicted suitable habitat conditions were congruent with probable habitats of krill, which emphasizes the strong dependence on their primary prey.

Description: A meta data compilation available in Pangaea, papers or row data of main investigations during the IMCOAST\IMCONET Project (1991-2016) in Potter Cove, Carlini Station, King George Island (Isla 25 de Mayo). This includes environmental (metereology, geochemistry, chemistry, biogeochemistry, light (PAR,kd), webcam, suspended matter, CTD) and biological variables. Map picture available and Shapefile for ArcGis (Projection WGS 1984 UTM21S).

Description: Macroalgae is a central part of marine shelf ecosystems in the Arctic, both as primary producers and as habitat builders and may contribute substantially to the carbon export into the deep sea. In Kongsfjorden we quantified the zonation of visually dominant macroalgal taxa and of detached macroalgae from underwater videos taken in summer 2009 at six transects between 2 to 138 m water depth. Four transects were located at the south shore along the length axis of the fjord (Kongsfjordneset, Brandal, Prince Heinrich Island, Tyskahytta). Two further transects investigated the steep bedrock of Hansneset with a west-east orientation 50 m apart from each other: Hansneset 1 (north) and Hansneset 2 (south). The georeferenced data (date, depth, coordinates) of all transects were linked to the timecode of the video and imported into a geographic coordinate system (GIS). Presence/absence and cover data of macroalgae along the transects was collated into the GIS. The resulting shape files provide useful information for further investigations of macroalgae in the fjord and the geographical information may enhance the repeatability of the investigation in the future.

Description: Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS 〉 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values.