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  • 2020-2024  (15,703)
  • 1960-1964  (7)
  • 2020  (15,703)
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Year
  • 1
    Publication Date: 2024-07-11
    Description: The annual glacier mass balance of Hallstätter Gletscher in Austria is measured since 1.10.2006 with the direct glaciological method in the fixed date system (1.10. to 30. 09. of the following year). The accumulation of snow is measured by determination of the water equivalent in 6 snow pits, the ice ablation is measured with 15 stakes drilled into the ice. Results are the annual net mass balance in kg, the total accumulation and ablation, the glacier area and the portions of the area which are subject to ablation and accumulation, the elevation of the equilibrium line and the specific mass balance in kg/m² (= mm w.e.). The accumulation during the winter is determined by the 1 May. The project is funded by the Federal Government of Upper Austria. The measurements are carried out the Institute for Interdisciplinary Mountain Research of the Austrian Academy of Sciences and the company Blue Sky in Gmunden, Austria.
    Keywords: Ablation area; Accumulation area; Accumulation area ratio; DATE/TIME; Equilibrium line altitude; Glaciers Austria; Hallstätter Gletscher, Dachstein, Austria; HSG; Mass balance, total; Mass balance in ablation area; Mass balance in accumulation area; Specific mass balance; Specific mass balance, summer; Specific mass balance, winter; Specific mass balance in the ablation area; Specific mass balance in the accumulation area; Total area
    Type: Dataset
    Format: text/tab-separated-values, 13 data points
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  • 2
    Publication Date: 2024-07-11
    Description: The annual glacier mass balance of Hallstätter Gletscher in Austria is measured since 1.10.2006 with the direct glaciological method in the fixed date system (1.10. to 30. 09. of the following year). The accumulation of snow is measured by determination of the water equivalent in 6 snow pits, the ice ablation is measured with 15 stakes drilled into the ice. Results are the annual net mass balance in kg, the total accumulation and ablation, the glacier area and the portions of the area which are subject to ablation and accumulation, the elevation of the equilibrium line and the specific mass balance in kg/m² (= mm w.e.). The accumulation during the winter is determined by the 1 May. The project is funded by the Federal Government of Upper Austria. The measurements are carried out the Institute for Interdisciplinary Mountain Research of the Austrian Academy of Sciences and the company Blue Sky in Gmunden, Austria.
    Keywords: DATE/TIME; Elevation, maximum; Elevation, minimum; Glaciers Austria; Hallstätter Gletscher, Dachstein, Austria; HSG; Mass balance, total of the altitude zone; Specific mass balance of the altitude zone; Specific mass balance of the altitude zone, summer; Specific mass balance of the altitude zone, winter; Total area of the altitude zone
    Type: Dataset
    Format: text/tab-separated-values, 98 data points
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  • 3
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    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-07-09
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; Germany; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; LIN; Lindenberg; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CM22, SN 020073, WRMC No. 12014; Pyranometer, Kipp & Zonen, CM22, SN 020074, WRMC No. 12013; Pyrgeometer, Eppley, PIR, SN 32802F3, WRMC No. 12011; Pyrheliometer, Kipp & Zonen, CH1, SN 030340, WRMC No. 12016; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 764122 data points
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  • 4
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    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-07-09
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; Germany; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; LIN; Lindenberg; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CM22, SN 020073, WRMC No. 12014; Pyranometer, Kipp & Zonen, CM22, SN 020074, WRMC No. 12013; Pyrgeometer, Eppley, PIR, SN 32802F3, WRMC No. 12011; Pyrheliometer, Kipp & Zonen, CH1, SN 030340, WRMC No. 12016; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 846480 data points
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  • 5
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    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-07-09
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; Germany; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; LIN; Lindenberg; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CM22, SN 020073, WRMC No. 12014; Pyranometer, Kipp & Zonen, CM22, SN 020074, WRMC No. 12013; Pyrgeometer, Eppley, PIR, SN 32802F3, WRMC No. 12011; Pyrheliometer, Kipp & Zonen, CH1, SN 030340, WRMC No. 12016; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 825050 data points
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  • 6
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    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-07-09
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; Germany; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; LIN; Lindenberg; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CM22, SN 020073, WRMC No. 12014; Pyranometer, Kipp & Zonen, CM22, SN 020074, WRMC No. 12013; Pyrgeometer, Eppley, PIR, SN 32802F3, WRMC No. 12011; Pyrheliometer, Kipp & Zonen, CH1, SN 030340, WRMC No. 12016; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 818962 data points
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  • 7
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    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-07-09
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; Germany; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; LIN; Lindenberg; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CM22, SN 020073, WRMC No. 12014; Pyranometer, Kipp & Zonen, CM22, SN 020074, WRMC No. 12013; Pyrgeometer, Eppley, PIR, SN 32802F3, WRMC No. 12011; Pyrheliometer, Kipp & Zonen, CH1, SN 030340, WRMC No. 12016; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 845640 data points
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  • 8
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    PANGAEA
    In:  Meteorologisches Observatorium Potsdam
    Publication Date: 2024-07-09
    Keywords: Air temperature at 2 m height; BARO; Barometer; Baseline Surface Radiation Network; BSRN; DATE/TIME; Diffuse radiation; Diffuse radiation, maximum; Diffuse radiation, minimum; Diffuse radiation, standard deviation; Direct radiation; Direct radiation, maximum; Direct radiation, minimum; Direct radiation, standard deviation; Germany; HEIGHT above ground; Humidity, relative; HYGRO; Hygrometer; LIN; Lindenberg; Long-wave downward radiation; Long-wave downward radiation, maximum; Long-wave downward radiation, minimum; Long-wave downward radiation, standard deviation; Monitoring station; MONS; Pyranometer, Kipp & Zonen, CM22, SN 020073, WRMC No. 12014; Pyranometer, Kipp & Zonen, CM22, SN 020074, WRMC No. 12013; Pyrgeometer, Eppley, PIR, SN 32802F3, WRMC No. 12011; Pyrheliometer, Kipp & Zonen, CH1, SN 030340, WRMC No. 12016; Short-wave downward (GLOBAL) radiation; Short-wave downward (GLOBAL) radiation, maximum; Short-wave downward (GLOBAL) radiation, minimum; Short-wave downward (GLOBAL) radiation, standard deviation; Station pressure; Thermometer
    Type: Dataset
    Format: text/tab-separated-values, 763044 data points
    Location Call Number Expected Availability
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  • 9
    Publication Date: 2024-07-08
    Description: The deep-sea is the largest habitat on Earth, but its biodiversity and ecosystem dynamics are still underexplored. Deep-sea sponge grounds (syn. aggregations, gardens) are sponge-dominated ecosystems that are found throughout the world´s oceans. They are considered vulnerable marine ecosystems (VMEs) and warrant protection against human intervention. Deep-sea sponge grounds are considered hotspots of diversity and function in the deep ocean. While a significant body of information has been accrued on shallow-water sponges, our understanding of deep-sea sponges and their associated microbiomes at the beginning of this PhD thesis was still very limited. This PhD thesis therefore aims to provide a first comprehensive overview on the diversity, evolution, biogeography, and ecology of deep-sea sponge microbiomes. The overarching aim was to assess whether the concepts obtained in shallow-water sponge microbiology would also hold in the deep-sea. In addition, novel themes such as biogeochemistry, physical oceanography, and trait-based approaches were integrated and further expand the existing theoretical framework in sponge microbiology. Sampling was conducted during 20 deep-sea expeditions, largely to sponge grounds of the North Atlantic in the context of the EU project “SponGES: Deep-sea sponge grounds ecosystems of the North Atlantic - an integrated approach towards their preservation and sustainable exploitation”. In total 1077 sponge-associated microbiomes were sampled along with 355 seawater microbiomes and 114 sediment microbiomes from 52 sponge ground locations. Microbial diversity was assessed by 16S rRNA gene amplicon sequencing and host taxonomy was determined by a combination of taxonomic and molecular markers. To this end, a state-of-the-art high-throughput 16S amplicon pipeline was established and corresponding metadata workflows were developed. The resulting data were analysed by six specific case studies (of which all were published) and one overarching meta-analysis (manuscript in preparation). The microbial community composition of deep-sea sponges was explored across different scales, from the ecosystem- and biogeography-level, to individual sponge species and to the microbial taxon (Amplicon Single nucleotide Variant; ASV) level. By exploring sponge microbiomes on different levels of integration and by using a nested sampling design, I was able to identify overarching factors, that drive microbiome composition in a statistically proven manner. The main identified environmental drivers of microbial community variability were temperature, salinity, nutrients/oxygen, and depth. It is noteworthy, that these parameters were identified from a total set of 24 environmental parameters. Furthermore, sponge phylogeny, taxonomy, and morphology were found to be related with the microbial community composition. Interestingly, microbial diversity can be predicted based on sponge morphology, which offers exciting opportunities for future studies in respect to imaging or trait-based approaches. My conclusions on the microbiome composition of deep-sea sponge microbiomes are that each deep-sea sponge harbours an individual set of microbes and a large pool of hidden diversity. Furthermore, deep-sea sponge microbiomes are globally not well connected and rather display heterogeneity on local scales. Interestingly, a deep-sea specific sponge microbiome was discovered. Overall, the results of my thesis suggest a strong nestedness of deep-sea sponge microbiomes within their ecological context. In the context of this PhD thesis, I established a baseline of deep-sea sponge-associated microbiomes, discovered a large extent of novel diversity and described patterns of specificity, stability and variability. I further identified the environmental and host-related drivers of sponge microbiome composition. From a methodological point, I have designed and developed a software tool (termed SVAmpEx) that allows the archiving and user-friendly accessibility of deep-sea sponge microbiome baseline data. Since microbiome composition is directly related to sponge health, reference baselines are valuable to monitor the integrity and resilience of deep-sea sponges. The collective information gathered in this PhD thesis provides the scientific basis to improve conservation and management strategies of the vulnerable deep-sea sponge ground ecosystems in the long run.
    Type: Thesis , NonPeerReviewed
    Format: text
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  • 10
    Publication Date: 2024-07-06
    Keywords: bioinvasion; DATE/TIME; decomposition; Eastern Mediterranean Sea; Oxygen; Rhopilema nomadica
    Type: Dataset
    Format: text/tab-separated-values, 854107 data points
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