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  • Pensoft  (16)
  • PANGAEA  (10)
  • 2020-2024  (26)
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  • 1
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    Unknown
    More than 50 years of Th-234 data: a comprehensive global oceanic compilation (2021)
    PANGAEA
    Details
    Publication Date: 2024-06-09
    Description: The ²³⁴Th-²³⁸U radioactive pair has been extensively used to evaluate the efficiency with which photosyntetically fixed carbon is exported from the surface ocean by means of the biological pump since the 90's. The seminal work of Buesseler et al. (1992) proposed that particulate organic carbon (POC) flux can be indirectly calculated from ²³⁴Th distributions if the ratio of POC to ²³⁴Th measured on sinking particles (POC:²³⁴Th) at the desired export depth is known. Since then, a huge amount of ²³⁴Th depth profiles have been collected using a variety of sampling instruments and strategies that have changed along years. This is a global oceanic compilation of ²³⁴Th measurements, that collects results from innumerable researchers and laboratories over a period exceeding 50 years. The present compilation is made of a total 223 datasets: 214 from studies published either in articles in referred journals, PhD thesis or repositories, and 9 unpublished datasets. Including measurements from JGOFS, VERTIGO and GEOTRACES programs, with sampling from approximately 5000 locations spanning all the oceans. The compilation includes total ²³⁴Th profiles, dissolved and particulate ²³⁴Th concentrations, and POC:²³⁴Th ratios (both from pumps and sediment traps) for two sizes classes (1-53 μm and 〈 53 μm) when available. Appropriate metadata have been included, including geographic location, date, and sample depth, among others. When available, we also include water temperature, salinity, ²³⁸U data and particulate organic nitrogen data. Data sources and methods information (including ²³⁸U and ²³⁴Th) are also detailed along with valuable information for future data analysis such as bloom stage and steady/non-steady state conditions at the sampling moment. This undertaking is a treasure of data to understand and quantify how oceanic carbon cycle functions and how it will change in future. The compilation can be downloaded in three different ways: 1) A single merged file including all the individual excel files. This option can be accessed under "Other version: More than 50 years of Th-234 data: a comprehensive global oceanic compilation (single xlsx file)". 2) A summary table that includes details from cruise, sampling dates, techniques applied, authors and DOI of the compiled ²³⁴Th data, among others, each line corresponds to a specific dataset. The table can be accessed by clicking ""View dataset as HTML" and downloaded in "Download dataset as tab-delimited text". 3) Individual Excel files for each dataset can be manually chosen from the summary table, corresponding to the complete ²³⁴Th dataset and metadata from a specific publication or program. This option is available by clicking "View dataset as HTML". Furthermore, all files referred to can be downloaded in one go as ZIP or TAR.
    Keywords: 234Th; Author(s); Binary Object; biological carbon pump; Carbon, organic, particulate/Thorium-234 ratio; carbon export; Chief scientist(s); Cruise/expedition; DATE/TIME; ELEVATION; Gear; GEOTRACES; Global marine biogeochemical cycles of trace elements and their isotopes; JGOFS; Joint Global Ocean Flux Study; Journal/report title; LATITUDE; LONGITUDE; Multiple cruises/expeditions; Ocean; Ocean and sea region; Period; POC flux; Project; Reference of data; Thorium-234, dissolved; Thorium-234, particulate; Thorium-234, total; Uniform resource locator/link to reference; Uranium-238; Vessel; Year of publication
    Type: Dataset
    Format: text/tab-separated-values, 4056 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 2
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    Global Early Instrumental Monthly Meteorological Multivariable Database (HCLIM) (2022)
    PANGAEA
    Details
    Publication Date: 2024-04-27
    Description: There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and the construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data has been merged from 18250 original data files. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate data set for the preindustrial period.
    Keywords: A Palaeoreanalysis To Understand Decadal Climate Variability; de-duplication; early instrumental; GlobCover; PALAEO-RA; paleoclimatology; Paleometeorology; quality control; Time series
    Type: Dataset
    Format: application/zip, 24 datasets
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 3
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    The rise of the Functional Response in invasion science: a systematic review (2023)
    Pensoft
    Details
    Publication Date: 2024-02-07
    Description: Predicting which non-native species will negatively impact biodiversity is a longstanding research priority. The Functional Response (FR; resource use in relation to availability) is a classical ecological concept that has been increasingly applied to quantify, assess and compare ecological impacts of non-native species. Despite this recent growth, an overview of applications and knowledge gaps across relevant contexts is currently lacking. We conducted a systematic review using a combination of terms regarding FR and invasion science to synthesise scientific studies that apply the FR approach in the field and to suggest new areas where it could have valuable applications. Trends of publications using FR in invasion science and publications about FR in general were compared through the Activity Index. Data were extracted from papers to reveal temporal, bibliographic, and geographic trends, patterns in study attributes such as type of interaction and habitat investigated, taxonomic groups used, and context-dependencies assessed. In total, 120 papers were included in the review. We identified substantial unevenness in the reporting of FRs in invasion science, despite a rapidly growing number of studies. To date, research has been geographically skewed towards North America and Europe, as well as towards predator-prey interactions in freshwater habitats. Most studies have focused on a few species of invertebrates and fishes. Species origin, life stage, environmental temperature and habitat complexity were the most frequently considered context-dependencies. We conclude that while the FR approach has thus far been narrowly applied, it has broad potential application in invasion science and can be used to test major hypotheses in this research field. © Larissa Faria et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 4
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    Count and biomass records of infauna and sediment characteristics from grab samples at the alpha ventus offshore wind farm (North Sea), 2008 - 2011 (2022)
    PANGAEA
    Details
    Publication Date: 2024-01-16
    Description: Data on infauna and sediment characteristics were collected as part of an extensive research program on the effects of offshore wind turbines on the marine environment funded by the German Federal Maritime and Hydrographic Agency. The investigations were performed in the first German offshore wind farm alpha ventus in the German Bight (North Sea). The overall aim of the program was to evaluate the German national standard concept for environmental impact assessments for offshore wind farms. Specifically, our study addressed the potential changes of the infauna communities in different distances from single turbines in an early stage of the operational phase of the wind farm. The data were collected during the cruises HE296 (2008), HE313 (2009), HE340 (2010) and HE369 (2000) of the German research vessel RV Heincke. Infauna samples were taken with van Veen grab samples (sampling area: 0.1 m2, weight: 95 kg) inside the wind farm and in two reference sites outside the wind farm. Three replicate samples were taken at each station. The samples were sieved through a 1 mm mesh and species of the macro-infauna were determined to the lowest taxonomic level possible. Sub-samples of the sediments were fractionated in a cascade of sieves of different mesh sizes to determine the grain size distributions. The organic contents of the sediments were determined as weight loss on ignition. The dataset comprises 11,400 count and biomass records for 103 infaunal taxa (89 % on species level, 11 % others) from 528 samples. Sediments were characterised for 176 van Veen grabs.
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 5
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    Physical oceanography and current velocity data from mooring M3 on the upper continental slope, east of Filchner Trough, February 2017 – February 2021 (2023)
    PANGAEA
    Details
    Publication Date: 2024-02-23
    Description: Time series data of physical oceanography (seawater conductivity, temperature, pressure, salinity) and ocean current velocities were obtained from mooring M3 on the upper part (750 m isobath) of the continental slope, just east of the Filchner Trough in the southern Weddell Sea in February 2017 - February 2021. The mooring was deployed during the WAPITI expedition on James Clark Ross (JR16004), and recovered during the COSMUS expedition with Polarstern (PS124). The attached archive contains data from 1 RCM7 (21 meters above bottom (mab herafter) and sampling interval (sint hereafter) 2h), 13 SBE56 (22,56,81,106,159,184,6508,260,285,310,335,360,385 mab, sint: 120 s), 4 SBE37 (31, 134, 209, 410 mab, sint: 600 s), 1 RDI ADCP 75 kHz (235 mab, upwardlooking, sint: 2h), 1 SBE39 (435 mab, sint: 900s). Mooring diagrams and information about data processing are provided.
    Keywords: ADCP; Antarctica; AWI_PhyOce; Continental Slope; Filchner Region; Filchner Trough; GPF 19-2_039, COSMUS; James Clark Ross; JR16004; JR16004_162; JR16004_162, PS124_14-1; M3_MOOR_WeddellSea; M3, M3_MOOR_WeddellSea; MOOR; Mooring; oceanographic moorings; oceanographic time series; Physical Oceanography @ AWI; Polarstern; PS124; PS124_14-1; Temperature and Salinity; WAPITI; Weddell Sea
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 6
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    Physical oceanography and current velocity data from mooring M6 on the upper continental slope, east of Filchner Trough, February 2017 – February 2021 (2024)
    PANGAEA
    Details
    Publication Date: 2024-02-23
    Description: Time series data of physical oceanography (seawater conductivity, temperature, pressure, salinity) and ocean current velocities were obtained from mooring M6 on the upper part (500 m isobath) of the continental slope, just east of the Filchner Trough in the southern Weddell Sea in February 2017 - February 2021. The mooring was deployed during the WAPITI expedition on James Clark Ross (JR16004), and recovered during the COSMUS expedition with Polarstern (PS124). The attached archive contains data from 1 RCM7 (24 meters above bottom (mab herafter) and sampling interval (sint hereafter) 2h), 5 SBE56 (25, 59, 74, 126, 202 mab, sint: 120 s), 3 SBE37 (34, 99, 176 mab, sint: 600 s), 1 RDI ADCP 150 kHz (235 mab, upwardlooking, sint: 1h), 1 SBE39 (15 mab, sint: 900s). Mooring diagrams and information about data processing are provided
    Keywords: ADCP; Antarctica; AWI_PhyOce; Continental Slope; Filchner Region; Filchner Trough; GPF 19-2_039, COSMUS; James Clark Ross; JR16004; JR16004_160; JR16004_160, PS124_99-1; M6_MOOR_WeddellSea; M6, M6_MOOR_WeddellSea; MOOR; Mooring; oceanographic moorings; oceanographic time series; Physical Oceanography @ AWI; Polarstern; PS124; PS124_99-1; Temperature and Salinity; WAPITI; Weddell Sea
    Type: Dataset
    Format: application/zip, 2 datasets
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 7
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    Continuous optical chlorophyll-a and turbidity data along RV SONNE cruise SO289 (2024)
    PANGAEA
    Details
    Publication Date: 2024-06-02
    Description: Underway optical chlorophyll-a and turbidity data were collected along the cruise track with Sea-Bird Scientific ECO FLNTU sensors installed within two autonomous measurement systems, called self-cleaning monitoring boxes (SMBs). The SMBs measure alternatingly. While one box is measuring, the other one is being cleaned. At the beginning of the transect, the boxes switched to operation every three hours, later, while the ship is transecting the Pacific Gyre, the cleaning interval was changed to only every 24 hours. The water inlet for the SMBs is at about 4 m depth. The data were quality controlled and the chlorophyll-a data were additionally calibrated using discrete water samples. In situ chlorophyll-a samples were collected by the scientific party from Niskin bottles during CTD stations and underway using a tow fish. Chlorophyll-a of these samples was determined in the lab on board using a bench top fluorometer. Details on all quality control steps, the calibration, as well as a comparison to satellite data can be found in the data processing report. The resulting data set contains the original data and corresponding quality flags and, in case of chlorophyll-a, additionally the calibrated data plus quality flag. The data source is given through the name of the active SMB. The data set contains data during transect and station. We recommend to use ship's speed to filter for only transect data.
    Keywords: Chlorophyll a; chlorophyll-a; DAM; DAM_Underway; DAM Underway Research Data; Data quality control procedures according to Copernicus Marine in situ TAC BGC quality control group (2021); DATE/TIME; DEPTH, water; EPA 445; Fluorescence; Fluorometer, Sea-Bird Scientific, ECO FLNTU; Fluorometer, Sea-Bird Scientific, ECO FLNTU; Calibration with samples measured according to Arar and Collins (1997); GEOTRACES GP21; ICBM; LATITUDE; LONGITUDE; Measurement container; Quality flag, chlorophyll a; Quality flag, turbidity; Ship speed; SO289; SO289_0_Underway-7; Sonne_2; turbidity; Turbidity (Nephelometric turbidity unit); Underway Measurement
    Type: Dataset
    Format: text/tab-separated-values, 470752 data points
    Location Call Number Limitation Availability
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    DATA PANGAEA
  • 8
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    Biological invasions in Singapore and Southeast Asia: data gaps fail to mask potentially massive economic costs (2021)
    Pensoft
    Details
    Publication Date: 2024-02-07
    Description: The impacts of invasive alien species are well-known and are categorised as a leading contributor to biodiversity loss globally. However, relatively little is known about the monetary costs incurred from invasions on national economies, hampering management responses. In this study, we used published data to describe the economic cost of invasions in Southeast Asia, with a focus on Singapore – a biodiversity-rich, tropical island city state with small size, high human density and high trade volume, three factors likely to increase invasions. In this country, as well as in others in Southeast Asia, cost data were scarce, with recorded costs available for only a small fraction of the species known to be invasive. Yet, the overall available economic costs to Singapore were estimated to be ~ US$ 1.72 billion in total since 1975 (after accounting for inflation), which is approximately one tenth of the total cost recorded in all of Southeast Asia (US$ 16.9 billion). These costs, in Singapore and Southeast Asia, were mostly linked to insects in the family Culicidae (principally Aedes spp.) and associated with damage, resource loss, healthcare and control-related spending. Projections for 11 additional species known to be invasive in Singapore, but with recorded costs only from abroad, amounted to an additional US$ 893.13 million, showing the potential huge gap between recorded and actual costs (cost records remain missing for over 90% of invasive species). No costs within the database for Singapore – or for other Southeast Asian countries – were exclusively associated with proactive management, highlighting that a shortage of reporting on the costs of invasions is mirrored by a lack of investment in management. Moreover, invasion cost entries in Singapore were under-reported relative to import levels, but total costs exceeded expectations, based on land area and population size, and to a greater extent than in other Southeast Asian countries. Therefore, the evaluation and reporting of economic costs of invasions need to be improved in this region to provide efficient data-based support for mitigation and management of their impacts.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 9
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    Economic costs of invasive species in Germany (2021)
    Pensoft
    Details
    Publication Date: 2024-02-07
    Description: Invasive alien species are a well-known and pervasive threat to global biodiversity and human well-being. Despite substantial impacts of invasive alien species, quantitative syntheses of monetary costs incurred from invasions in national economies are often missing. As a consequence, adequate resource allocation for management responses to invasions has been inhibited, because cost-benefit analysis of management actions cannot be derived. To determine the economic cost of invasions in Germany, a Central European country with the 4th largest GDP in the world, we analysed published data collected from the first global assessment of economic costs of invasive alien species. Overall, economic costs were estimated at US$ 9.8 billion between 1960 and 2020, including US$ 8.9 billion in potential costs. The potential costs were mostly linked to extrapolated costs of the American bullfrog Lithobates catesbeianus, the black cherry Prunus serotina and two mammals: the muskrat Ondatra zibethicus and the American mink Neovison vison. Observed costs were driven by a broad range of taxa and mostly associated with control-related spending and resource damages or losses. We identified a considerable increase in costs relative to previous estimates and through time. Importantly, of the 2,249 alien and 181 invasive species reported in Germany, only 28 species had recorded economic costs. Therefore, total quantifications of invasive species costs here should be seen as very conservative. Our findings highlight a distinct lack of information in the openly-accessible literature and governmental sources on invasion costs at the national level, masking the highly-probable existence of much greater costs of invasions in Germany. In addition, given that invasion rates are increasing, economic costs are expected to further increase. The evaluation and reporting of economic costs need to be improved in order to deliver a basis for effective mitigation and management of invasions on national and international economies.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 10
    facet.materialart.
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    Biomass records of infauna from grab samples at the alpha ventus offshore wind farm (North Sea), 2008 - 2011 (2022)
    PANGAEA
    Details
    Publication Date: 2024-01-16
    Description: Data on infauna and sediment characteristics were collected as part of an extensive research program on the effects of offshore wind turbines on the marine environment funded by the German Federal Maritime and Hydrographic Agency. The investigations were performed in the first German offshore wind farm alpha ventus in the German Bight (North Sea). The overall aim of the program was to evaluate the German national standard concept for environmental impact assessments for offshore wind farms. Specifically, our study addressed the potential changes of the infauna communities in different distances from single turbines in an early stage of the operational phase of the wind farm. The data were collected during the cruises HE296 (2008), HE313 (2009), HE340 (2010) and HE369 (2011) of the German research vessel RV HEINCKE. Infauna samples were taken with van Veen grab samples (sampling area: 0.1 m2, weight: 95 kg) inside the wind farm and in two reference sites outside the wind farm. Three replicate samples were taken at each station. The samples were sieved through a 1 mm mesh and species of the macro-infauna were determined to the lowest taxonomic level possible. Sub-samples of the sediments were fractionated in a cascade of sieves of different mesh sizes to determine the grain size distributions. The organic contents of the sediments were determined as weight loss on ignition. The dataset comprises 11,400 count and biomass records for 103 infaunal taxa (89 % on species level, 11 % others) from 528 samples. Sediments were characterised for 176 van Veen grabs.
    Keywords: Area/locality; Biomass, wet mass; Counts; DATE/TIME; DEPTH, water; Event label; Gear; HE296; HE296/865-1; HE296/865-2; HE296/865-3; HE296/866-2; HE296/866-3; HE296/866-4; HE296/867-2; HE296/867-3; HE296/867-4; HE296/868-1; HE296/868-2; HE296/868-3; HE296/903-1; HE296/903-2; HE296/904-1; HE296/905-1; HE296/905-2; HE296/905-4; HE296/906-2; HE296/906-3; HE296/906-4; HE296/907-2; HE296/907-3; HE296/907-4; HE296/908-2; HE296/908-3; HE296/908-4; HE296/912-1; HE296/912-3; HE296/912-4; HE296/913-1; HE296/913-3; HE296/913-4; HE296/914-1; HE296/914-3; HE296/914-4; HE296/915-2; HE296/915-3; HE296/915-4; HE296/916-2; HE296/916-3; HE296/916-4; HE296/917-1; HE296/917-2; HE296/917-3; HE296/918-1; HE296/918-2; HE296/918-4; HE296/919-1; HE296/919-3; HE296/919-4; HE296/920-1; HE296/920-2; HE296/920-3; HE296/921-1; HE296/921-3; HE296/921-4; HE296/923-1; HE296/923-2; HE296/923-3; HE296/924-1; HE296/924-2; HE296/924-3; HE296/925-1; HE296/925-2; HE296/925-3; HE296/926-1; HE296/926-3; HE296/926-4; HE296/927-2; HE296/927-3; HE296/927-4; HE296/928-1; HE296/928-3; HE296/928-4; HE296/929-1; HE296/929-2; HE296/929-3; HE296/930-1; HE296/930-2; HE296/930-3; HE296/931-1; HE296/931-2; HE296/931-3; HE296/932-1; HE296/932-3; HE296/932-4; HE296/933-1; HE296/933-2; HE296/933-4; HE296/934-1; HE296/934-2; HE296/934-3; HE296/935-1; HE296/935-2; HE296/935-4; HE296/936-1; HE296/936-2; HE296/936-3; HE296/949-1; HE296/949-2; HE296/949-3; HE296/950-1; HE296/950-2; HE296/950-4; HE296/951-1; HE296/951-3; HE296/951-4; HE296/952-1; HE296/952-3; HE296/952-4; HE296/953-1; HE296/953-2; HE296/953-3; HE296/954-1; HE296/954-2; HE296/954-3; HE296/955-1; HE296/955-2; HE296/955-4; HE296/956-1; HE296/956-2; HE296/956-3; HE296/965-1; HE296/965-2; HE296/965-3; HE296/992-1; HE296/992-3; HE296/992-4; HE296/993-2; HE296/993-3; HE296/993-4; HE313; HE313/916-2; HE313/916-3; HE313/916-4; HE313/917-2; HE313/917-3; HE313/917-4; HE313/918-2; HE313/918-3; HE313/918-4; HE313/919-2; HE313/919-3; HE313/919-4; HE313/920-2; HE313/920-3; HE313/920-4; HE313/921-1; HE313/921-4; HE313/922-2; HE313/922-3; HE313/922-4; HE313/923-2; HE313/923-3; HE313/923-4; HE313/924-2; HE313/924-3; HE313/924-4; HE313/925-2; HE313/925-3; HE313/925-4; HE313/926-2; HE313/926-3; HE313/926-4; HE313/927-2; HE313/927-3; HE313/927-4; HE313/928-2; HE313/928-3; HE313/928-4; HE313/929-2; HE313/929-3; HE313/929-4; HE313/930-2; HE313/930-3; HE313/930-4; HE313/931-2; HE313/931-3; HE313/931-4; HE313/932-2; HE313/932-3; HE313/932-4; HE313/933-2; HE313/933-3; HE313/933-4; HE313/934-2; HE313/934-3; HE313/934-4; HE313/935-2; HE313/935-3; HE313/935-4; HE313/936-2; HE313/936-3; HE313/936-4; HE313/941-2; HE313/941-3; HE313/941-4; HE313/942-2; HE313/942-3; HE313/942-4; HE313/943-2; HE313/943-3; HE313/943-4; HE313/944-2; HE313/944-3; HE313/944-4; HE313/945-2; HE313/945-3; HE313/945-4; HE313/946-2; HE313/946-3; HE313/946-4; HE313/947-2; HE313/947-3; HE313/947-4; HE313/948-2; HE313/948-3; HE313/948-4; HE313/955-2; HE313/955-3; HE313/955-4; HE313/956-2; HE313/956-3; HE313/956-4; HE313/957-2; HE313/957-3; HE313/957-4; HE313/958-2; HE313/958-3; HE313/958-4; HE313/959-2; HE313/959-3; HE313/959-4; HE313/960-2; HE313/960-3; HE313/960-4; HE313/961-2; HE313/961-3; HE313/961-4; HE313/962-2; HE313/962-3; HE313/962-4; HE313/963-2; HE313/963-3; HE313/963-4; HE313/964-2; HE313/964-3; HE313/964-4; HE313/965-2; HE313/965-3; HE313/965-4; HE313/966-2; HE313/966-3; HE313/966-4; HE313/967-2; HE313/967-3; HE313/967-4; HE313/968-2; HE313/968-3; HE313/968-4; HE313/969-2; HE313/969-3; HE313/969-4; HE340; HE340/03-2; HE340/03-3; HE340/03-4; HE340/04-2; HE340/04-3; HE340/04-4; HE340/05-2; HE340/05-3; HE340/05-4; HE340/06-2; HE340/06-3; HE340/06-4; HE340/07-2; HE340/07-3; HE340/07-4; HE340/08-2; HE340/08-3; HE340/08-4; HE340/09-2; HE340/09-3; HE340/09-4; HE340/10-2; HE340/10-3; HE340/10-4; HE340/11-2; HE340/11-3; HE340/11-4; HE340/12-2; HE340/12-3; HE340/12-4; HE340/13-2; HE340/13-3; HE340/13-4; HE340/14-2; HE340/14-3; HE340/14-4; HE340/15-2; HE340/15-3; HE340/15-4; HE340/16-2; HE340/16-3; HE340/16-4; HE340/17-2; HE340/17-3; HE340/17-4; HE340/18-2; HE340/18-3; HE340/18-4; HE340/19-2; HE340/19-3; HE340/19-4; HE340/20-2; HE340/20-3; HE340/20-4; HE340/21-2; HE340/21-3; HE340/21-4; HE340/22-2; HE340/22-3; HE340/22-4; HE340/23-2; HE340/23-3; HE340/23-4; HE340/24-2; HE340/24-3; HE340/24-4; HE340/25-2; HE340/25-3; HE340/25-4; HE340/26-2; HE340/26-3; HE340/26-4; HE340/27-2; HE340/27-3; HE340/27-4; HE340/47-2; HE340/47-3; HE340/47-4; HE340/48-2; HE340/48-3; HE340/48-4; HE340/49-2; HE340/49-3; HE340/49-4; HE340/50-2; HE340/50-3; HE340/50-4; HE340/51-2; HE340/51-3; HE340/51-4; HE340/56-2; HE340/56-3; HE340/56-4; HE340/57-2; HE340/57-3; HE340/57-4; HE340/58-2; HE340/58-3; HE340/58-4; HE340/59-2; HE340/59-3; HE340/59-4; HE340/60-2; HE340/60-3; HE340/60-4; HE340/61-2; HE340/61-3; HE340/61-4; HE340/62-2; HE340/62-3; HE340/62-4; HE340/63-2; HE340/63-3; HE340/63-4; HE340/64-2; HE340/64-3; HE340/64-4; HE340/65-2; HE340/65-3; HE340/65-4; HE340/66-2; HE340/66-3; HE340/66-4; HE340/67-2; HE340/67-3; HE340/67-4; HE340/73-2; HE340/73-3; HE340/73-4; HE340/74-2; HE340/74-3; HE340/74-4; HE369; HE369/001-2; HE369/001-3; HE369/001-4; HE369/002-1; HE369/003-1; HE369/004-1; HE369/005-1; HE369/006-1; HE369/007-1; HE369/008-1; HE369/009-1; HE369/010-1; HE369/011-1; HE369/012-1; HE369/015-1; HE369/016-1; HE369/017-1; HE369/018-1; HE369/023-2; HE369/023-3; HE369/023-4; HE369/024-1; HE369/025-1; HE369/026-1; HE369/027-1; HE369/028-1; HE369/029-1; HE369/030-1; HE369/031-1; HE369/032-1; HE369/033-1; HE369/034-1; HE369/035-1; HE369/036-1; HE369/058-1; HE369/059-1; HE369/060-1; HE369/061-1; HE369/062-1; HE369/063-1; HE369/064-1; HE369/065-1; HE369/066-1; HE369/067-1; HE369/068-1; HE369/069-1; HE369/070-1; HE369/071-1; Heincke; LATITUDE; LONGITUDE; North Sea; Penetration depth; Project; Replicate; Scientific name; van Veen Grab; VGRAB
    Type: Dataset
    Format: text/tab-separated-values, 90465 data points
    Location Call Number Limitation Availability
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