GLORIA

GEOMAR Library Ocean Research Information Access

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • PANGAEA  (26)
  • SPRINGER  (3)
  • Elsevier  (1)
  • Paleontological Institute, University of Kansas, Lindley Hall
  • 2015-2019  (27)
  • 2005-2009  (3)
  • 1985-1989  (1)
Document type
Keywords
Years
Year
  • 1
    facet.materialart.
    Unknown
    Elsevier
    In:  Journal of Experimental Marine Biology and Ecology, 117 (3). pp. 271-278.
    Publication Date: 2018-03-21
    Description: In ecological studies, especially in those dealing with energy circulation in nature, determinations of the energy content of organisms are inevitable. Energy determinations are, however, laborious and time-consuming. Average conversion factors based on different species form various areas and seasons may often be a shortcut for overcoming this problem. To establish general energy conversion factors for aquatic invertebrate groups, we used 376 values of J · mg−1 DW and 255 values of J · mg−1 AFDW, representing 308 and 229 species, respectively. The dry-weight-to-energy factors were highly variable both within and between taxonomic groups, e.g.: Porifera, 6.1 J · mg−1 DW; insect larvae, 22.4 J · mg−1 DW (median values). The energy-conversion factors related to AFDW showed a much smaller dispersion with a minimum median value of 19.7 J · mg−1 AFDW (Ascidiacea) and a maximum of 23.8 J · mg−1 AFDW (insect larvae). Within taxonomic groups, the 95% confidence intervals (AFDW) were only a few percent of the median values. The use of energy-conversion factors based on AFDW is preferable due to their lower dispersion. For aquatic macrobenthic invertebrates, a general conversion factor of 23 J · mg−1 AFDW can be used.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 2
    facet.materialart.
    Unknown
    PANGAEA
    In:  Supplement to: Brey, Thomas (2012): A multi-parameter artificial neural network model to estimate macrobenthic invertebrate productivity and production. Limnology and Oceanography-Methods, 10, 581-589, https://doi.org/10.4319/lom.2012.10.581
    Publication Date: 2023-01-13
    Description: I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.
    Type: Dataset
    Format: application/zip, 187.7 kBytes
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2023-02-24
    Keywords: 13200-001; 13200-009; 13200-027; 13200-035; 13200-039; 13200-041; 13200-059; 13200-060; 13200-070; 13200-074; 13200-084; 13200-091; 13200-093; 13200-094; 13200-099; ALBEX lander; BENGAL; Benthic Biology and Geochemistry of a North-eastern Atlantic Abyssal Locality; BN; Bottom net; Chalut à perche (6 m beam trawl); Comment; CP; D229; Date/Time of event; DEPTH, sediment/rock; Discovery (1962); Elevation of event; Event label; Individuals; Latitude of event; Longitude of event; MCB57; MultiCorer Barnett pattern (12-57); NIOZL; OTSB14; Semi-balloon trawl; Spade box corer; Species; Taxonomic hierarchy; VEGBOXC; δ13C; δ15N
    Type: Dataset
    Format: text/tab-separated-values, 898 data points
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 4
    Publication Date: 2023-02-24
    Keywords: 12930-010; 12930-015; 12930-025; 12930-026; 12930-032; 12930-034; 12930-037; 12930-046; 12930-064; 12930-071; 12930-078; 12930-081; Baited free-fall benthic amphipod trap; BC; BENGAL; Benthic Biology and Geochemistry of a North-eastern Atlantic Abyssal Locality; Box corer; Comment; D222/2; Date/Time of event; DEMAR; DEPTH, sediment/rock; Discovery (1962); Elevation of event; Event label; Individuals; Latitude of event; Longitude of event; MCB57; MEGAC; MegaCorer; MultiCorer Barnett pattern (12-57); OTSB14; SAPS; Semi-balloon trawl; Species; Stand-alone pumps; Taxonomic hierarchy; δ13C; δ15N
    Type: Dataset
    Format: text/tab-separated-values, 437 data points
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 5
    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
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 6
    Publication Date: 2024-03-01
    Keywords: AWI_BPP; Bentho-Pelagic Processes @ AWI; Brandal; Comment; Kongsfjorden, Spitsbergen, Arctic; Mass spectrometer, Finnigan, MAT 253; MULT; Multiple investigations; ORDINAL NUMBER; Serripes groenlandicus, δ13C; Serripes groenlandicus, δ18O; δ13C, standard deviation; δ18O, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 530 data points
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 7
    Publication Date: 2024-03-01
    Keywords: AWI_BPP; Bentho-Pelagic Processes @ AWI; Brandal; Comment; Kongsfjorden, Spitsbergen, Arctic; Mass spectrometer, Finnigan, MAT 253; MULT; Multiple investigations; ORDINAL NUMBER; Serripes groenlandicus, δ13C; Serripes groenlandicus, δ18O; δ13C, standard deviation; δ18O, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 890 data points
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 8
    facet.materialart.
    Unknown
    PANGAEA
    In:  Supplement to: Epplé, Valerie M; Brey, Thomas; Witbaard, Rob; Kuhnert, Henning; Pätzold, Jürgen (2006): Sclerochronological records of Arctica Islandica from the inner German Bight. The Holocene, 16(5), 763-769, https://doi.org/10.1191/0959683606hl970rr
    Publication Date: 2024-01-25
    Description: Sclerochronological records of interannual shell growth variability were established for eight modern shells (26 to 163 years of age) of the bivalve Arctica islandica, which were sampled at one site in the inner German Bight. The records indicate generally low synchrony between individuals. Spectral analysis of the whole 163-yr masterchronology indicated a cyclic pattern with a period of 5 and 7 years. The masterchronology correlated poorly to time series of environmental parameters over the last 90 years. High environmental variability in time and space of the dynamic and complex German Bight hydrographic system results in an extraordinarily high noise' level in the shell growth pattern of Arctica islandica.
    Keywords: Age; AGE; arctica-2002_01; BEAM; Beam trawl; Digital imaging; LTER_Benthos; Macrobenthic long-term series in the German Bight; ORDINAL NUMBER; Replicates; Spiekeroog, German Bight, North Sea; Standardized shell increment; Standardized shell increment, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 599 data points
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 9
    Publication Date: 2024-03-01
    Keywords: AWI_BPP; Bentho-Pelagic Processes @ AWI; Brandal; Comment; Kongsfjorden, Spitsbergen, Arctic; Mass spectrometer, Finnigan, MAT 253; MULT; Multiple investigations; ORDINAL NUMBER; Serripes groenlandicus, δ13C; Serripes groenlandicus, δ18O; δ13C, standard deviation; δ18O, standard deviation
    Type: Dataset
    Format: text/tab-separated-values, 540 data points
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
  • 10
    Publication Date: 2024-06-12
    Description: 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).
    Keywords: 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
    Type: Dataset
    Format: text/tab-separated-values, 30 data points
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...