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  • 1
    facet.materialart.
    Unbekannt
    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
    Publikationsdatum: 2023-03-02
    Beschreibung: 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.
    Schlagwort(e): 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
    Materialart: Dataset
    Format: text/tab-separated-values, 398 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Publikationsdatum: 2023-09-05
    Beschreibung: 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.
    Schlagwort(e): File content; File format; File name; File size; Uniform resource locator/link to file; Weddell_Sea
    Materialart: Dataset
    Format: text/tab-separated-values, 10 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 3
    facet.materialart.
    Unbekannt
    PANGAEA
    In:  Supplement to: Jerosch, Kerstin; Scharf, Frauke Katharina; Pehlke, Hendrik; Weber, Lukas; Abele, Doris (in prep.): Explanation of the spatial distribution of physiochemical properties of Potter Cove, Antarctica, by classification of Potter Cove, Antarctica, via k means clustering, canonical-correlation analysis and multidimensional scaling.
    Publikationsdatum: 2024-02-16
    Beschreibung: This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.
    Schlagwort(e): Carlini/Jubany Station; IMCOAST/IMCONet; Impact of climate induced glacier melt on marine coastal systems, Antarctica; Jubany_Dallmann; MULT; Multiple investigations; PotterCove; Potter Cove, King George Island, Antarctic Peninsula
    Materialart: Dataset
    Format: application/zip, 101.5 MBytes
    Standort Signatur Erwartet Verfügbarkeit
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  • 4
    facet.materialart.
    Unbekannt
    PANGAEA
    In:  Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven | Supplement to: Jerosch, Kerstin; Pehlke, Hendrik; Weber, Lukas; Teschke, Katharina; Heidemann, Teresa; Scharf, Frauke Katharina (in prep.): Comparing the surface and the bottom of the Southern Ocean using multivariate cluster analysis: regional effects of environmental parameters.
    Publikationsdatum: 2024-02-16
    Beschreibung: This study subdivides the Weddell Sea, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis uses 28 environmental variables for the sea surface, 25 variables for the seabed and 9 variables for the analysis between surface and bottom variables. The data were taken during the years 1983-2013. Some data were interpolated. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared for the identification of the most reasonable method. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested. For the seabed 8 and 12 clusters were identified as reasonable numbers for clustering the Weddell Sea. For the sea surface the numbers 8 and 13 and for the top/bottom analysis 8 and 3 were identified, respectively. Additionally, the results of 20 clusters are presented for the three alternatives offering the first small scale environmental regionalization of the Weddell Sea. Especially the results of 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.
    Schlagwort(e): File format; File name; File size; Priority Programme 1158 Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas; SPP1158; Uniform resource locator/link to file; Weddell_Sea
    Materialart: Dataset
    Format: text/tab-separated-values, 16 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 5
    Publikationsdatum: 2024-04-20
    Beschreibung: 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.
    Schlagwort(e): Binary Object; Binary Object (File Size); Brandal_ROV; Event label; Hansneset_north_ROV; Hansneset_south_ROV; Kongsfjorden, Spitsbergen, Arctic; Kongsfjordneset_ROV; Prince_Heinrich_Island_ROV; Remote operated vehicle; ROV; Tyskahytta_ROV
    Materialart: Dataset
    Format: text/tab-separated-values, 7 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 6
    Publikationsdatum: 2024-06-12
    Beschreibung: Here we provide an ArcGIS map package on the pelagic regionalisation in the wider Weddell Sea (Antarctica), which were created in the context of the development of a marine protected area (MPA) in the Weddell Sea. For the pelagic regionalisation following parameters were incorporated: (i) ice coverage from AMSR-E sea ice maps, (ii) bathymetric data from the International Bathymetric Chart of the Southern Ocean (IBCSO), and (iii) seawater temperature and salinity data from the Finite Element Sea Ice - Ocean Model (FESOM) provided by R. Timmermann (AWI). To classify different pelagic areas we have applied K-means clustering algorithm and 'clusGap' function from R package 'cluster'. Coastal polynyas mainly occurred east and west of the Prime Meridian (between 20°W to 30°E) as well as around the tip of Antarctic Peninsula, whereas the inner Weddell Sea was characterised by perennial ice-coverage. The largest area proportion of the wider Weddell Sea were classified by above average large water depths and relative high probabilities of ice-free days. More information on the spatial analysis is given in working paper WG-EMM-16/03 submitted to the CCAMLR Working Group on Ecosystem Monitoring and Management (available at https://www.ccamlr.org/en/wg-emm-16).
    Schlagwort(e): AWI_FuncEco; Development of a CCAMLR Marine Protected Area in the Antarctic Weddell Sea; File content; File format; File name; File size; Functional Ecology @ AWI; Model; Uniform resource locator/link to file; Wider_Weddell_Sea_Antarctica_pelagic_regionalisati; WSMPA
    Materialart: Dataset
    Format: text/tab-separated-values, 15 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 7
    Publikationsdatum: 2024-06-12
    Beschreibung: Here we provide four ArcGIS map packages with georeferenced files on the spatial distribution of Antarctic petrels, Adélie penguins (breeders and non-breeders) and Emperor penguins in the wider Weddell Sea (Antarctica), which were created in the context of the development of a marine protected area in the Weddell Sea. Antarctic petrel (Thalassoica antarctica): We approximated potential foraging habitats of T. antarctica according to existing literature by ice coverage from AMSR-E sea ice maps, bathymetric data from the International Bathymetric Chart of the Southern Ocean (IBCSO), and seawater temperature data from the Finite Element Sea Ice - Ocean Model (FESOM) provided by R. Timmermann (AWI). Subsequently, we combined our Antarctic petrel model with the kernel utilization distribution model from Descamps et al. (2016). The authors kindly provided us with shape files showing the kernel utilization summer and winter distribution of Antarctic petrel breeding at Svarthamaren. Breeding locations and estimated number of breeding pairs were taken from van Franeker et al. (1999). Favourable habitat conditions for Antarctic petrels were predicted for the Lazarev Sea and along the eastern coast of the Weddell Sea, particularly for the area off the Fimbul Ice Shelf and along the coast between approx. 15°E to 10°W within a water depth range from approx. 500 m to 2500 m. Breeding Adélie penguins (Pygoscelis adeliae): The map of potential foraging habitats of breeding P. adeliae is based on British Antarctic Survey (BAS) Inventory data from Phil Trathan (ID 754) and Mike Dunn and P. Trathan (ID 764, 773, 779), a dataset from BAS (P. Trathan) and Instituto Antártico Argentino (Mercedes Santos) (ID 753) and a dataset from the US AMLR Program from Jefferson Hinke and Wayne Trivelpiece (NOAA) (ID 910), which are stored in the Birdlife International's Seabird Tracking Database (data request: 20-10-2015). Suitable foraging habitats for breeding Adélies from colonies from which no tracking data were not available were approximated by a 50 km buffer and a 50-100 km ring buffer around each colony according to the recommendations of a CCAMLR MPA planning workshop. Breeding locations and estimated abundance of breeding pairs were taken from Lynch and LaRue (2014). The tracking data were processed with a state-space model described by Johnson et al. (2008) and were implemented in the R package crawl (Johnson 2011). Jefferson Hinke (NOAA) kindly provided us with support running the R script. Highly suitable foraging habitats occurred about 50 km away from the colonies on King Georg Island, the colony in Hope Bay (Graham Land) and the colonies on the South Orkney Islands. Non-breeding Adélie penguins (Pygoscelis adeliae): The map of potential foraging habitats of non-breeding P. adeliae is based on British Antarctic Survey (BAS) Inventory data from Phil Trathan (ID 754) and Mike Dunn and P. Trathan (ID 773, 779), a dataset from BAS (P. Trathan) and Instituto Antártico Argentino (Mercedes Santos) (ID 753) and a dataset from the US AMLR Program from Jefferson Hinke and Wayne Trivelpiece (NOAA) (ID 910), which are stored in the Birdlife International's Seabird Tracking Database (data request: 20-10-2015). The tracking data were processed with a state-space model described by Johnson et al. (2008) and were implemented in the R package crawl (Johnson 2011). Jefferson Hinke (NOAA) kindly provided us with support running the R script. Highest habitat utilisation was concentrated in relative small areas (e.g., close to King Georg Island). However, the non-breeding Adélies seemed to roam through large parts of the Weddell Sea. Emperor penguins (Aptenodytes forsteri): The probability map of A. forsteri occurrence was developed as a function of distance to colony and colony size from Fretwell et al. (2012, 2014) as well as from sea ice concentration from AMSR-E sea ice maps. Our model of emperor penguin foraging distribution during breeding season showed that the probability of occurrence is highest at the Halley and Dawson colony near Brunt Ice Shelf and at the Atka colony near Ekstrøm Ice Shelf. More information on the spatial analysis is given in working paper WG-EMM-16/03 and WG-SAM-17/30 (for T. antarctica) submitted to the CCAMLR Working Group on Ecosystem Monitoring and Management (EMM) and the CCAMLR Working Group on Statistics, Assessments and Modelling (SAM), respectively (available at https://www.ccamlr.org/en/wg-emm-16 and https://www.ccamlr.org/en/wg-sam-17).
    Schlagwort(e): Antarctica; Aptenodytes forsteri; AWI_FuncEco; Development of a CCAMLR Marine Protected Area in the Antarctic Weddell Sea; File content; File format; File name; File size; Functional Ecology @ AWI; Marine Protected Area (MPA); Model; Pygoscelis adeliae; Uniform resource locator/link to file; Weddell Sea; Wider_Weddell_Sea_Antarctica_Penguins; WSMPA
    Materialart: Dataset
    Format: text/tab-separated-values, 30 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 8
    Publikationsdatum: 2024-06-12
    Beschreibung: Here we provide two ArcGIS map packages with georeferenced files on the spatial distribution of seals in the wider Weddell Sea (Antarctica), which were created in the context of the development of a marine protected area in the Weddell Sea. Spatial distribution of seals based on aerial surveys: The map of the spatial distribution of crabeater seals is based on modelled seal abundances from Flores et al. (2008) and Forcada et al. (2012). These modelled abundances were supplemented by abundance data derived from Bester et al. (1995, 2002) and by point data from Plötz et al. (2011a-e), which were translated into abundance values by the count method for line transect data. The calculated data on seal abundances from Plötz et al. (2011a-e) and Bester et al. (1995, 2002) were interpolated using the inverse distance weighted method. The combined data set of modelled and interpolated abundances showed highest absolute seal abundances offshore the Riiser-Larsen Ice Shelf and Quarisen Ice Shelf. Spatial distribution of seals based on tracking data: The map of probability of seal occurrence is based on all tracking data publicly available for the wider Weddell Sea from the MEOP data portal "Marine Mammals Exploring the Oceans Pole to Pole" (data request: 14-11-2016). In addition, we have used MEOP data (UK data: ct27, ct70; German data: ct113, wd06, wd07) for which unconditional sharing is not yet accepted. These data were provided by Lars Boehme (University of St. Andrews) and Horst Bornemann (AWI), respectively. Furthermore, the data from the MEOP data portal were complemented by tracking data sets on southern elephant seals (Tosh et al. 2009, James et al. 2012), Weddell seals (McIntyre et al. 2013) and crabeater seals (Nachtsheim et al. 2016). All tracking data united were processed with a state-space model described by Johnson et al. (2008) and were implemented in the R package crawl (Johnson 2011). The tracking data analysis indicated frequent occurrence of seals in a larger area off the Brunt and Filchner Ice Shelf (approx. 25°W-40°W), and in smaller patches along the eastern Weddell Sea ice shelfs as well as in the region around the tip of the Antarctic Peninsula. More information on the spatial analysis is given in working paper WG-EMM-16/03 and WG-SAM-17/30 submitted to the CCAMLR Working Group on Ecosystem Monitoring and Management (EMM) and the CCAMLR Working Group on Statistics, Assessments and Modelling (SAM), respectively (available at https://www.ccamlr.org/en/wg-emm-16 and https://www.ccamlr.org/en/wg-sam-17).
    Schlagwort(e): Antarctica; AWI_FuncEco; Development of a CCAMLR Marine Protected Area in the Antarctic Weddell Sea; File content; File format; File name; File size; Functional Ecology @ AWI; Marine Protected Area (MPA); Model; pinnipeds; Uniform resource locator/link to file; Weddell Sea; Wider_Weddell_Sea_Antarctica_Seals; WSMPA
    Materialart: Dataset
    Format: text/tab-separated-values, 20 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 9
    Publikationsdatum: 2024-06-12
    Beschreibung: Here we provide four ArcGIS map packages with georeferenced files on the spatial distribution of demersal and pelagic fishes in the wider Weddell Sea (Antarctica), which were created in the context of the development of a marine protected area (MPA) in the Weddell Sea. Antarctic toothfish: The map of Dissostichus mawsoni occurrence probability is based on catch per unit effort (CPUE) data from the database of the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) (data request: 03-08-2016) and on bathymetric data from the International Bathymetric Chart of the Southern Ocean (IBCSO). We fitted a four-parameter Weibull model to the simulated CPUE data per depth interval by means of the R package 'fitdistrplus'. The highest D. mawsoni occurrence probability was shown at depths between 1500 and 2000 m and only approximately 20 % of the Antarctic toothfish population occurred deeper than 2000 m. Antarctic silverfish: The map of interpolated abundances of Pleuragramma antarctica was based on pelagic trawl survey data, which were collected during "Polarstern" cruises ANT-I/2, ANT-III/3 and in the context of the Lazarev Sea Krill Survey (LAKRIS) ("Polarstern" cruises ANT-XXI/4, ANT-XXIII/6, ANT-XXIV/2). The first mentioned data were provided by V. Siegel (retired; formerly Thünen Institute), the LAKRIS data by H. Flores (AWI). Those data were complemented by benthic trawl survey data, which were collected during seven "Polarstern" cruises between 1996 and 2011 (ANT-XIII/3, ANT-XV/3, ANT-XVII/3, ANT-XIX/5, ANT-XXI/2, ANT-XXIII/8, ANT-XXVII/3) and were provided by R. Knust (AWI) as well as by data on counts of fish species from trawl and dredge samples by Drescher et. (2012), Ekau et al. (2012a, b), Hureau et al. (2012), Kock et al. (2012) and Wöhrmann et al. (2012). An inverse distance weighted interpolation was performed for a 10 nautical mile radius around each record. Areas with highest numbers of P. antarctica (〉 36 individuals/1000 m²) occurred offshore Riiser -Larsen Ice Shelf and on the southern Weddell Sea continental shelf offshore Filchner Ice Shelf. Demersal fish: The map of predicted habitat suitability for demersal fish is based on data, which were collected during seven "Polarstern" cruises between 1996 and 2011 (ANT-XIII/3, ANT-XV/3, ANT-XVII/3, ANT-XIX/5, ANT-XXI/2, ANT-XXIII/8, ANT-XXVII/3) and were provided by R. Knust (AWI). The habitat suitability model was developed by the use of the modelling package "biomod2". Most suitable habitat conditions for demersal fish in the wider Weddell Sea occurred on the continental shelf between approx. 5° and 30°W, on the shelf west and east of the tip of the Antarctic Peninsula as well as around the South Shetland and South Orkney Islands. Nesting sites of demersal fish: The map on observation of nesting sites of demersal fish is based on data, which were collected during "Polarstern" cruises ANT-XXVII/3, ANT-XXIX/9 and ANT-XXXI/2 and were obtained by T. Lundälv (retired; formerly University of Gothenburg), D. Gerdes (retired; formerly AWI) and E. Riginella (University of Padova), respectively. Those data were complemented by a literature research. Most nesting sites were observed west of 25°W, north of the tip of the Antarctic Peninsula and along the west coast of the Antarctic Peninsula. More information is given in the working paper WG-EMM-16/03 submitted to the CCAMLR Working Group on Ecosystem Monitoring and Management CCAMLR (available at https://www.ccamlr.org/en/wg-emm-16). Revised versions of the spatial analysis are described in working paper WG-SAM-17/30 and WS-SM-18/13 submitted to the CCAMLR Working Group on Statistics, Assessments and Modelling and the CCAMLR Workshop on Spatial Management, respectively (available at https://www.ccamlr.org/en/wg-sam-17; https://www.ccamlr.org/en/ws-sm-18).
    Schlagwort(e): Antarctica; Antarctic silverfish (Pleuragramma antarctica); Antarctic toothfish (Dissostichus mawsoni); AWI_FuncEco; Development of a CCAMLR Marine Protected Area in the Antarctic Weddell Sea; File content; File format; File name; File size; Functional Ecology @ AWI; Marine Protected Area (MPA); Model; nesting sites; Uniform resource locator/link to file; Weddell Sea; Wider_Weddell_Sea_Antarctica_Fish; WSMPA
    Materialart: Dataset
    Format: text/tab-separated-values, 30 data points
    Standort Signatur Erwartet Verfügbarkeit
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  • 10
    Publikationsdatum: 2024-06-12
    Beschreibung: Here we provide two ArcGIS map packages with georeferenced files on the spatial distribution of sponges and echinoderms in the wider Weddell Sea (Antarctica), which were created in the context of the development of a marine protected area (MPA) in the Weddell Sea. Sponges: The map of interpolated occurrence of sponges is based on quantitative abundance data (Gerdes 2014 a - o) and on semi-quantitative data obtained by W. Arntz (retired; formerly AWI) (see Teschke & Brey 2019a for presence / absence records of the latter dataset). The abundance data were classified to be merged with the semi-quantitative data and an inverse distance weighted method was performed on the united dataset. Areas with very common occurrence of sponges occurred on the shelf near Brunt Ice Shelf along Riiser - Larsen Ice Shelf to Ekstrøm Ice Shelf. Echinoderms: A cluster analysis with species x station datasets of asteroids (Teschke & Brey 2019b), ophiuroids (Teschke & Brey 2019c) and holothurians (Gutt et al. 2014) from the Antarctic Weddell Sea indicated a particular cold-water echinoderm fauna on the Filchner shelf. We approximated this potential habitat by bottom temperature ≤ -1°, based on seawater temperature data from the Finite Element Sea Ice - Ocean Model provided by R. Timmermann (AWI). More information on the spatial analysis is given in working paper WG-EMM-16/03 submitted to the CCAMLR Working Group on Ecosystem Monitoring and Management (available at https://www.ccamlr.org/en/wg-emm-16).
    Schlagwort(e): Antarctica; AWI_FuncEco; Development of a CCAMLR Marine Protected Area in the Antarctic Weddell Sea; Echinodermata; File content; File format; File name; File size; Functional Ecology @ AWI; Marine Protected Area (MPA); Model; Porifera; Uniform resource locator/link to file; Weddell Sea; Wider_Weddell_Sea_Antarctica_Zoobenthos; WSMPA
    Materialart: Dataset
    Format: text/tab-separated-values, 20 data points
    Standort Signatur Erwartet Verfügbarkeit
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