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  • 1
    Publication Date: 2008-10-07
    Print ISSN: 0944-1344
    Electronic ISSN: 1614-7499
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by Springer
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  • 2
    Publication Date: 2007-08-07
    Print ISSN: 0167-6369
    Electronic ISSN: 1573-2959
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Published by Springer
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  • 3
    Publication Date: 2020-05-04
    Description: The Southern Ocean may contribute a considerable amount to the proposed global network of marine protected areas (MPAs) that should cover about 10 % of the world's oceans in 2020. In the Antarctic, the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) is responsible for this task, and currently Germany leads a corresponding scientific evaluation of the wider Weddell Sea region. Compared to other marine regions within the Southern Ocean, the Weddell Sea is exceptionally well investigated. A tremendous amount of data and information has been produced over the last 4 decades. Here, we give a systematic overview of all data sources collected in the context of the Weddell Sea MPA planning process. The compilation of data sources is comprised of data produced by scientists and institutions from more than 20 countries that were either available within our institutes, downloaded via data portals or transcribed from the literature. It is the first compilation for this area that includes abiotic data, such as bathymetry and sea ice, and ecological data from zooplankton, zoobenthos, fish, birds and marine mammals. All data layer products based on this huge compilation of environmental and ecological data are available from the data publisher PANGAEA via the six persistent identifiers at https://doi.org/10.1594/PANGAEA.899595 (Pehlke and Teschke, 2019), https://doi.org/10.1594/PANGAEA.899667 (Teschke et al., 2019a), https://doi.org/10.1594/PANGAEA.899645 (Teschke et al., 2019b), https://doi.org/10.1594/PANGAEA.899591 (Teschke et al., 2019c), https://doi.org/10.1594/PANGAEA.899520 (Pehlke et al., 2019a) and https://doi.org/10.1594/PANGAEA.899619 (Pehlke et al., 2019b). This compilation of data sources including the final data layer products will serve future research and monitoring well beyond the current MPA development process.
    Print ISSN: 1866-3508
    Electronic ISSN: 1866-3516
    Topics: Geosciences
    Published by Copernicus
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  • 4
  • 5
    Publication Date: 2019-07-05
    Description: The Southern Ocean may contribute a considerable part to the proposed global network of Marine Protected Areas (MPAs) that should cover about 10 % of the world oceans in 2020. In the Antarctic, the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) is responsible for this task, and currently Germany leads a corresponding scientific evaluation of the wider Weddell Sea region. Compared to other marine regions within the Southern Ocean, the Weddell Sea is exceptionally well investigated. A tremendous amount of data and information has been produced over the last four decades. Here, we give a compilation of these data that were acquired in the context of the Weddell Sea MPA planning process. The data compilation comprises data produced by scientists/institutions from more than twenty countries and were either available within our institutes, provided by our collaborators, downloaded via data portals, or transcribed from the literature. It is the first data compilation for this area that includes abiotic data, such as bathymetry and sea ice, and ecological data from zooplankton, zoobenthos, fish, birds and marine mammals. The final data layer products based on this data compilation, including metadata description, are available from the data publisher PANGAE via the five persistent identifiers at https://doi.org/10.1594/PANGAEA.899520 (Pehlke et al., 2019a), https://doi.org/10.1594/PANGAEA.899591 (Teschke et al., 2019a), https://doi.org/10.1594/PANGAEA.899595 (Pehlke and Teschke, 2019), https://doi.org/10.1594/PANGAEA.899619 (Pehlke et al., 2019b), https://doi.org/10.1594/PANGAEA.899645 (Teschke et al., 2019b) and https://doi.org/10.1594/PANGAEA.899667 (Teschke et al., 2019c). This data compilation with the final data layer products will serve future research and monitoring well beyond the current MPA development process.
    Electronic ISSN: 1866-3591
    Topics: Geosciences
    Published by Copernicus
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  • 6
    Publication Date: 2021-02-01
    Print ISSN: 0308-597X
    Electronic ISSN: 1872-9460
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Political Science , Law
    Published by Elsevier
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  • 7
    Publication Date: 2018-05-14
    Description: The coasts of the West Antarctic Peninsula are strongly influenced by glacier meltwater discharge. The spatial structure and biogeochemical composition of inshore habitats are shaped by large quantities of terrigenous particulate material deposited in the vicinity of the coast, which impacts the pelagic and benthic ecosystems. We used a multitude of geochemical and environmental variables to identify the radius extension of the meltwater impact from the Fourcade Glacier into the fjord system of Potter Cove, King George Island. The k -means cluster algorithm, canonical correspondence analysis, variance analysis and Tukey's post hoc multiple comparison tests were applied to define and cluster coastal meltwater habitats. A minimum of 10 clusters were needed to classify the 8 km 2 study area into meltwater fjord habitats (MFHs), fjord habitats and marine habitats. Strontium content in surface sediments is the main geochemical indicator for lithogenic creek discharge in Potter Cove. Furthermore, bathymetry, glacier distance and geomorphic positioning are the essential habitats explaining variables. The mean and maximum MFH extent amounted to 1 km and 2 km, respectively. Extrapolation of the identified meltwater impact ranges to King George Island coastlines, which are presently ice-covered bays and fjord areas, indicated an overall coverage of 200–400 km 2 MFH, underpinning the importance of better understanding the biology and biogeochemistry in terrestrial marine transition zones. This article is part of the theme issue ‘The marine system of the West Antarctic Peninsula: status and strategy for progress in a region of rapid change’.
    Print ISSN: 1364-503X
    Electronic ISSN: 1471-2962
    Topics: Mathematics , Physics , Technology
    Published by The Royal Society
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  • 8
    facet.materialart.
    Unknown
    PANGAEA
    In:  Supplement to: Degen, Renate; Jørgensen, Lis Lindal; Ljubin, Pavel; Ellingsen, Ingrid H; Pehlke, Hendrik; Brey, Thomas (2016): Patterns and drivers of megabenthic secondary production on the Barents Sea shelf. Marine Ecology Progress Series, 546, 1-16, https://doi.org/10.3354/meps11662
    Publication Date: 2023-03-02
    Description: Megabenthos plays a major role in the overall energy flow on Arctic shelves, but information on megabenthic secondary production on large spatial scales is scarce. Here, we estimated for the first time megabenthic secondary production for the entire Barents Sea shelf by applying a species-based empirical model to an extensive dataset from the joint Norwegian- Russian ecosystem survey. Spatial patterns and relationships were analyzed within a GIS. The environmental drivers behind the observed production pattern were identified by applying an ordinary least squares regression model. Geographically weighted regression (GWR) was used to examine the varying relationship of secondary production and the environment on a shelfwide scale. Significantly higher megabenthic secondary production was found in the northeastern, seasonally ice-covered regions of the Barents Sea than in the permanently ice-free southwest. The environmental parameters that significantly relate to the observed pattern are bottom temperature and salinity, sea ice cover, new primary production, trawling pressure, and bottom current speed. The GWR proved to be a versatile tool for analyzing the regionally varying relationships of benthic secondary production and its environmental drivers (R² = 0.73). The observed pattern indicates tight pelagic- benthic coupling in the realm of the productive marginal ice zone. Ongoing decrease of winter sea ice extent and the associated poleward movement of the seasonal ice edge point towards a distinct decline of benthic secondary production in the northeastern Barents Sea in the future.
    Keywords: 2008-GS-140; 2008-GS-144; 2008-GS-147; 2008-GS-151; 2008-GS-152; 2008-GS-175; 2008-GS-178; 2008-GS-183; 2008-GS-186; 2008-GS-190; 2008-GS-193; 2008-GS-194; 2008-GS-196; 2008-GS-199; 2008-GS-200; 2008-GS-260; 2008-GS-285; 2008-GS-286; 2008-GS-311; 2008-GS-312; 2008-GS-313; 2008-GS-314; 2008-GS-315; 2008-GS-318; 2008-GS-319; 2008-GS-320; 2008-GS-321; 2008-GS-322; 2008-GS-323; 2008-GS-324; 2008-GS-325; 2008-GS-326; 2008-GS-327; 2008-GS-328; 2008-GS-329; 2008-GS-330; 2008-GS-331; 2008-GS-332; 2008-GS-333; 2008-GS-334; 2008-GS-335; 2008-GS-336; 2008-JH-322; 2008-JH-323; 2008-JH-324; 2008-JH-325; 2008-JH-326; 2008-JH-327; 2008-JH-328; 2008-JH-383; 2008-JH-386; 2008-JH-391; 2008-JH-393; 2008-JH-394; 2008-JH-398; 2008-JH-401; 2008-JH-402; 2008-JH-403; 2008-JH-410; 2008-JH-411; 2008-JH-414; 2008-JH-418; 2008-VY-003; 2008-VY-006; 2008-VY-008; 2008-VY-010; 2008-VY-012; 2008-VY-014; 2008-VY-016; 2008-VY-018; 2008-VY-020; 2008-VY-022; 2008-VY-024; 2008-VY-026; 2008-VY-028; 2008-VY-033; 2008-VY-035; 2008-VY-037; 2008-VY-039; 2008-VY-041; 2008-VY-043; 2008-VY-045; 2008-VY-047; 2008-VY-049; 2008-VY-051; 2008-VY-053; 2008-VY-055; 2008-VY-057; 2008-VY-059; 2008-VY-061; 2008-VY-063; 2008-VY-065; 2008-VY-067; 2008-VY-069; 2008-VY-071; 2008-VY-073; 2008-VY-075; 2008-VY-076; 2008-VY-077; 2008-VY-078; 2008-VY-079; 2008-VY-081; 2008-VY-082; 2008-VY-083; 2008-VY-085; 2008-VY-087; 2008-VY-089; 2008-VY-091; 2008-VY-093; 2008-VY-095; 2008-VY-097; 2008-VY-099; 2008-VY-101; 2008-VY-103; 2008-VY-105; 2008-VY-107; 2008-VY-109; 2008-VY-111; 2008-VY-113; 2008-VY-114; 2008-VY-116; 2008-VY-118; 2008-VY-120; 2008-VY-123; 2008-VY-126; 2008-VY-128; 2008-VY-130; 2008-VY-132; 2008-VY-134; 2008-VY-136; 2008-VY-138; 2008-VY-140; 2008-VY-142; 2008-VY-144; 2008-VY-146; 2008-VY-148; 2008-VY-153; 2008-VY-155; 2008-VY-157; 2008-VY-158; 2008-VY-160; 2008-VY-162; 2008-VY-164; 2008-VY-166; 2008-VY-168; 2008-VY-170; 2008-VY-172; 2008-VY-174; 2008-VY-176; 2008-VY-178; 2008-VY-180; 2008-VY-182; 2008-VY-184; 2008-VY-186; 2008-VY-188; 2008-VY-190; 2008-VY-192; 2008-VY-194; 2008-VY-196; 2008-VY-198; 2008-VY-200; 2008-VY-202; 2008-VY-204; 2008-VY-206; 2008-VY-208; 2008-VY-210; 2008-VY-212; 2008-VY-214; 2008-VY-216; 2008-VY-218; 2008-VY-220; 2008-VY-222; 2008-VY-224; 2008-VY-226; 2008-VY-228; 2008-VY-229; 2008-VY-232; 2008-VY-234; 2008-VY-236; 2008-VY-238; 2008-VY-240; 2008-VY-243; 2008-VY-244; 2008-VY-245; 2008-VY-246; 2008-VY-248; 2008-VY-251; 2008-VY-253; 2008-VY-254; 2008-VY-255; 2008-VY-256; 2008-VY-257; 2008-VY-258; 2008-VY-259; 2008-VY-260; 2008-VY-261; 2008-VY-262; 2008-VY-264; 2008-VY-265; 2008-VY-267; 2008-VY-268; 2008-VY-269; 2008-VY-271; 2008-VY-272; 2008-VY-273; 2008-VY-275; 2008-VY-277; 2008-VY-278; 2008-VY-279; 2008-VY-280; 2008-VY-281; 2008-VY-282; 2008-VY-283; 2008-VY-284; 2008-VY-285; 2008-VY-288; 2008-VY-290; 2008-VY-291; 2008-VY-292; 2008-VY-293; 2008-VY-294; 2008-VY-296; 2009-GS-142; 2009-GS-143; 2009-GS-146; 2009-GS-154; 2009-GS-155; 2009-GS-158; 2009-GS-159; 2009-GS-162; 2009-GS-163; 2009-GS-166; 2009-GS-167; 2009-GS-170; 2009-GS-171; 2009-GS-174; 2009-GS-175; 2009-GS-178; 2009-GS-179; 2009-GS-182; 2009-GS-184; 2009-GS-187; 2009-GS-188; 2009-GS-191; 2009-GS-192; 2009-GS-195; 2009-GS-196; 2009-GS-203; 2009-GS-204; 2009-GS-207; 2009-GS-208; 2009-GS-211; 2009-JH-282; 2009-JH-284; 2009-JH-286; 2009-JH-288; 2009-JH-290; 2009-JH-292; 2009-JH-294; 2009-JH-296; 2009-JH-298; 2009-JH-305; 2009-JH-307; 2009-JH-311; 2009-JH-313; 2009-JH-318; 2009-JH-325; 2009-JH-327; 2009-JH-333; 2009-JH-335; 2009-JH-337; 2009-JH-339; 2009-JH-341; 2009-JH-345; 2009-JH-347; 2009-JH-350; 2009-JH-353; 2009-JH-356; 2009-JH-362; 2009-JH-365; 2009-JH-368; 2009-JH-371; 2009-JH-373; 2009-JH-375; 2009-JH-377; 2009-JH-379; 2009-JH-383; 2009-JH-385; 2009-JH-390; 2009-JH-392; 2009-JH-395; 2009-JH-398; 2009-JH-400; 2009-JH-403; 2009-JH-405; 2009-JH-407; 2009-JH-410; 2009-JH-412; 2009-JH-417; 2009-JH-422; 2009-JH-424; 2009-JH-427; 2009-JH-429; 2009-JH-431; 2009-JH-433; 2009-JH-436; 2009-JH-438; 2009-JH-442; 2009-JH-445; 2009-JH-447; 2009-JH-449; 2009-JH-452; 2009-JH-454; 2009-JH-456; 2009-JH-461; 2009-JH-463; 2009-JH-465; 2009-JH-468; 2009-JH-470; 2009-JH-472; 2009-JH-475; 2009-JH-478; 2009-JH-480; 2009-JH-482; 2009-JH-484; 2009-JH-486; 2009-JH-488; 2009-JH-490; 2009-JH-492; 2009-JH-494; 2009-JH-496; 2009-JH-497; 2009-JH-500; 2009-JH-502; 2009-JH-504; 2009-JH-506; 2009-JM-491; 2009-JM-495; 2009-JM-497; 2009-JM-499; 2009-JM-506; 2009-JM-509; 2009-JM-519; 2009-JM-522; 2009-JM-527; 2009-JM-528; 2009-JM-532; 2009-JM-541; 2009-JM-543; 2009-JM-544; 2009-JM-549; 2009-JM-550; 2009-JM-555; 2009-JM-557; 2009-JM-559; 2009-JM-560; 2009-JM-561; 2009-JM-563; 2009-JM-565; 2009-JM-566; 2009-JM-568; 2009-JM-572; 2009-JM-574; 2009-JM-578; 2009-JM-582; 2009-JM-586; 2009-JM-587; 2009-JM-590; 2009-JM-592; 2009-JM-595; 2009-JM-599; 2009-JM-602; 2009-JM-604; 2009-JM-607; 2009-JM-609; 2009-JM-611; 2009-JM-613; 2009-JM-615; 2009-JM-617; 2009-VY-01; 2009-VY-02; 2009-VY-03; 2009-VY-04; 2009-VY-05; 2009-VY-06; 2009-VY-07; 2009-VY-08; 2009-VY-09; 2009-VY-10; 2009-VY-11; 2009-VY-12; 2009-VY-13; 2009-VY-14; 2009-VY-15; 2009-VY-16; 2009-VY-18; 2009-VY-19; 2009-VY-20; 58GS2008; 58GS2009; 58JH2008; 58JH2009; 58JM2009; 90VY2008; 90VY2009; Arctic Ocean; Barents Sea; Basis of event; Campaign of event; Date/Time of event; Event label; G. O. Sars (2003); Jan Mayen; Johan Hjort (1990); Kara Sea; Latitude of event; Location of event; Longitude of event; North Greenland Sea; Norwegian Sea; Secondary production as carbon; Vilnyus
    Type: Dataset
    Format: text/tab-separated-values, 398 data points
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  • 9
    Publication Date: 2023-09-05
    Description: Interests in exploring Cold Water Corals (CWC) ecosystems witnessed a dramatic increase in the last decades, after the realisation that their habitats are threatened by ocean warming and acidification. However, they are still largely overlooked by the scientific community in deep and harsh environments like the Southern Ocean. Recent advances in species distribution models (SDM) have allowed forecasting species distribution patterns and assessing climate change impacts at different spatial scales. Several limitations related to the accuracy of species presences, the lack of reliable absence data and the limited spatial resolution of environmental factors, have restricted the widespread utilisation of these approaches in polar areas. In this work, real presence-absence records of 13 species were gathered from research expeditions and literature and combined with model-generated pseudo-absences, to cover the study area. Moreover, a final set of 14 high-resolution environmental variables was pre-selected and nine species distribution modelling algorithms were merged with means of the ensemble forecasting platform 'biomod2' to model the habitat suitability for azooxanthallate scleractinian corals, in the Weddell Sea. 'Biomod2' is implemented in 'R' and is a freeware, open source package. Response of scleractinian distribution to the future climate change was also investigated, based on two future scenarios of the bottom sea temperature. Present ensemble prediction maps accurately captured the potential ecological niches of the modelled species (good to excellent true skill statistic (TSS) and area under the receiver operating characteristic curve (AUC) evaluation measures). In the Weddell Sea, scleractinian distribution is limited to the continental shelf and slope areas with preference to small scale features (i.e., seamounts), which have been identified as having a high probability of supporting cold-water coral habitat. The most important factors in determining CWC habitat suitability were distance to coast and ice shelves, bathymetry, calcium carbonate and temperature. The response of scleractinian to future climate revealed some changes in small-scale spatial distribution patterns. Under warmer conditions, the CWC will probably expand their distribution range by a total of 6 to 10%, by 2037 and 2150 respectively, compared to the present. This expansion would concern the Filchner Trough and the adjacent continental shelves as well as the eastern side of the Antarctic Peninsula.
    Keywords: File content; File format; File name; File size; Uniform resource locator/link to file; Weddell_Sea
    Type: Dataset
    Format: text/tab-separated-values, 10 data points
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  • 10
    facet.materialart.
    Unknown
    PANGAEA
    In:  Supplement to: Jerosch, Kerstin; Scharf, Frauke Katharina; Deregibus, Dolores; Campana, Gabriela L; Zacher-Aued, Katharina; Pehlke, Hendrik; Abele, Doris; Quartino, Maria Liliana (in prep.): The potential macroalgae habitat shifts in an Antarctic Peninsula fjord due to climate change.
    Publication Date: 2024-02-16
    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.
    Keywords: IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; Priority Programme 1158 Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas; SPP1158
    Type: Dataset
    Format: application/zip, 2 datasets
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