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  • 1
    Publication Date: 2024-07-08
    Type: Thesis , NonPeerReviewed
    Format: text
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  • 2
    Publication Date: 2024-07-08
    Description: Key message: A decolonial approach is needed to fulfil IASC’s commitment to recognizing that Traditional Knowledge, Indigenous Knowledge and academic scientific knowledge are co-equal and complementary knowledge systems that all can and should inform its work (website ICARP IV, retrieved October 2023). This document summarizes key recommendations for actions regarding five themes: 1. Indigenous Peoples’ right to self-determination as a prerequisite for high-quality Arctic research 2. Ethics, methods and methodology as key for decolonial research 3. Indigenous-led research in design and practice 4. Indigenous Peoples’ co-equal participation in Arctic research funding structures and decision-making for securing decolonial Arctic research in practice 5. Funding for Co-Creative and Indigenous-Led Arctic Research
    Language: English
    Type: info:eu-repo/semantics/report
    Format: application/pdf
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  • 3
    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
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  • 4
    Publication Date: 2024-07-07
    Description: Fatty acid (FA) composition has increasingly been used to estimate the dietary preference of marine organisms. Specific fatty acids and fatty acid ratios serve as trophic markers (FATM) and have the potential to provide insights on the long-term dietary preference of organisms. FATM have been applied for this purpose on various zooplankton, fish and up to whales. We aim to build up a database of new and published data on fatty acid content of mesopelagic fish and their predators from the central and Northeast Atlantic, and the Mediterranean Sea, to use in FATM food web studies, investigating the importance of mesopelagic organisms as predators and prey in the marine ecosystem. Here we compiled FA content (i.e., the proportion of each FA measured in sampled tissues or in the whole body of organisms in relation to total FAs analysed) of 36 fish species or genera, 15 seabirds, five marine mammals, two cephalopods, one turtle, one jelly fish, and one shark. For each record, we included all FAs with values above 0.1% of total FAs and report the percentage values as provided in the original data source. Each data record is associated with information on the sampling location, geographic coordinates, month and year of sample collection, method of sample collection, taxonomic ranks (phylum, class, order, family), number and size (or size range) of sampled organisms, as well as the reference and DOI of the original data source, for further details on the samples analysed and/or the analytical techniques used.
    Keywords: (9Z)-heptadec-9-enoic acid; (9Z)-heptadec-9-enoic acid, standard deviation; 12,15 Octadecadienoic acid of total fatty acids; 3,6,9,12 Hexadecatetraenoic acid of total fatty acids; 4,7,10,13,16-Docosapentaenoic acid; 6,9,12,15-Hexadecatetraenoic acid of total fatty acids; 6,9,12-Hexadecatrienoic acid of total fatty acids; 9,12-Hexadecadienoic acid of total fatty acids; 9-Tetradecenoic acid of total fatty acids; 9-Tetradecenoic acid of total fatty acids, standard deviation; Adriatic_Sea_comp; all-cis-11,14,17-Eicosatrienoic acid of total fatty acids; all-cis-11,14,17-Eicosatrienoic acid of total fatty acids, standard deviation; all-cis-11,14-Eicosadienoic acid of total fatty acids; all-cis-11,14-Eicosadienoic acid of total fatty acids, standard deviation; all-cis-11,14-Octadecadienoic acid of total fatty acids; all-cis-13,16,19-Docosatrienoic acid of total fatty acids; all-cis-3,6,9,12,15-Octadecapentaenoic acid of total fatty acids; all-cis-4,7,10,13,16,19-Docosahexaenoic acid of total fatty acids; all-cis-4,7,10,13,16,19-Docosahexaenoic acid of total fatty acids, standard deviation; all-cis-4,7,10,13,16-Docosapentaenoic acid, standard deviation; all-cis-5,8,11,14,17-Eicosapentaenoic acid of total fatty acids; all-cis-5,8,11,14,17-Eicosapentaenoic acid of total fatty acids, standard deviation; all-cis-5,8,11,14-Eicosatetraenoic acid of total fatty acids; all-cis-5,8,11,14-Eicosatetraenoic acid of total fatty acids, standard deviation; all-cis-6,9,12,15,18-Heneicosapentaenoic acid of total fatty acids; all-cis-6,9,12,15,18-Heneicosapentaenoic acid of total fatty acids, standard deviation; all-cis-6,9,12,15-Hexadecatetraenoic acid of total fatty acids, standard deviation; all-cis-6,9,12,15-Octadecatetraenoic acid of total fatty acids; all-cis-6,9,12,15-Octadecatetraenoic acid of total fatty acids, standard deviation; all-cis-6,9,12-Octadecatrienoic acid of total fatty acids; all-cis-6,9,12-Octadecatrienoic acid of total fatty acids, standard deviation; all-cis-7,10,13,16,19-Docosapentaenoic acid of total fatty acids; all-cis-7,10,13,16,19-Docosapentaenoic acid of total fatty acids, standard deviation; all-cis-7,10,13,16-Docosatetraenoic acid of total fatty acids; all-cis-7,10,13,16-Docosatetraenoic acid of total fatty acids, standard deviation; all-cis-7,10,13-Hexadecatrienoic acid of total fatty acids; all-cis-7,10-Hexadecadienoic acid of total fatty acids; all-cis-8,11,14,17-Eicosatetraenoic acid of total fatty acids; all-cis-8,11,14,17-Eicosatetraenoic acid of total fatty acids, standard deviation; all-cis-8,11,14-Eicosatrienoic acid of total fatty acids; all-cis-8,11,14-Eicosatrienoic acid of total fatty acids, standard deviation; all-cis-9,12,15-Hexadecadienoic acid of total fatty acids; all-cis-9,12,15-Octadecatrienoic acid of total fatty acids; all-cis-9,12,15-Octadecatrienoic acid of total fatty acids, standard deviation; all-cis-9,12-Hexadecadienoic acid of total fatty acids, standard deviation; all-cis-9,12-Hexadecatrienoic acid of total fatty acids, standard deviation; all-cis-9,12-Octadecadienoic acid of total fatty acids; all-cis-9,12-Octadecadienoic acid of total fatty acids, standard deviation; Azores_comp; Balearic_Sea_comp; Barbate_comp; Barents_Sea_comp; Canary_Islands_comp; Cape_Verde_comp; Catalonian_Sea_comp; Central_Northeastern_Atlantic_comp; Cephalopods; cis-10-Heptadecenoic acid of total fatty acids; cis-10-Heptadecenoic acid of total fatty acids, standard deviation; cis-11-Docosenoic acid of total fatty acids; cis-11-Docosenoic acid of total fatty acids, standard deviation; cis-11-Hexadecenoic acid of total fatty acids, standard deviation; cis-11-Hexadecenoic acid of total fatty acids (IUPAC: (11Z)-hexadec-11-enoic acid); cis-11-Icosenoic acid of total fatty acids; cis-11-Icosenoic acid of total fatty acids, standard deviation; cis-11-Octadecenoic acid of total fatty acids, standard deviation; cis-11-Octadecenoic acid of total fatty acids (IUPAC: Octadec-11-enoic acid); cis-13-Docosenoic acid of total fatty acids; cis-13-Docosenoic acid of total fatty acids, standard deviation; cis-13-Icosenoic acid of total fatty acids; cis-13-Icosenoic acid of total fatty acids, standard deviation; cis-13-Octadecenoic acid of total fatty acids; cis-13-Octadecenoic acid of total fatty acids, standard deviation; cis-15-Docosenoic acid of total fatty acids; cis-15-Docosenoic acid of total fatty acids, standard deviation; cis-15-Tetracosenoic acid of total fatty acids; cis-15-Tetracosenoic acid of total fatty acids, standard deviation; cis-7-Hexadecenoic acid of total fatty acids; cis-7-Hexadecenoic acid of total fatty acids, standard deviation; cis-9-Hexadecenoic acid of total fatty acids, standard deviation; cis-9-Hexadecenoic acid of total fatty acids (IUPAC: (9Z)-hexadec-9-enoic acid); cis-9-Icosanoic acid of total fatty acids; cis-9-Icosanoic acid of total fatty acids, standard deviation; cis-9-Octadecenoic acid of total fatty acids (IUPAC: Octadec-9-enoic acid); Class; Comment; Decanoic acid of total fatty acids; DEPTH, water; Docosanoic acid, standard deviation; Docosanoic acid of total fatty acids; Dodecanoic acid of total fatty acids; Dodecanoic acid of total fatty acids, standard deviation; dolphins; Ebro_Delta_comp; elasmobranchs; Event label; Family; fatty acids; Finnmark_comp; Gear; Heptadecanoic acid, standard deviation; Heptadecanoic acid of total fatty acids; Hexadecadienoic acid of total fatty acids; Hexadecanoic acid, standard deviation; Hexadecanoic acid of total fatty acids; Hexadecatetraenoic acid of total fatty acids; Hexadecatetraenoic acid of total fatty acids, standard deviation; Hexadecatrienoic acid of total fatty acids; Hexadecatrienoic acid of total fatty acids, standard deviation; Hexadecenoic acid of total fatty acids; Icosanoic acid, standard deviation; Icosanoic acid of total fatty acids; Institution; Investigator; Irminger_Sea_comp; Isle_of_May_comp; Jellyfish; LATITUDE; Lipids, per total wet mass; Location; Lofoten_Vesteralen_comp; LONGITUDE; Madeira_comp; marine mammals; Mauritania_comp; mesopelagic fish; mesopelagic food web; Mid_North_Atlantic_comp; Month; North_Sea_comp; Norwegian_Sea_North_comp; Number of individuals; Ocean and sea region; Octadec-7-enoic acid of total fatty acids; Octadec-7-enoic acid of total fatty acids, standard deviation; Octadec-9-enoic acid, standard deviation; Octadecanoic acid, standard deviation; Octadecanoic acid of total fatty acids; Octadecatetraenoic acid 18:4(n-4) of total fatty acids; Octadecenoic acid of total fatty acids; Order; Organisms; Pentadecanoic acid, standard deviation; Pentadecanoic acid of total fatty acids; Persistent Identifier; Phylum; Raso_Islet_Cape_Verde_comp; Record number; Reference/source; Replicates; Reykjanes_Ridge_comp; Seabirds; Size; Spanish_coast_comp; Spitsbergen_Bear_Island_comp; SUMMER; Sustainable Management of Mesopelagic Resources; Svalbard_comp; Taxon/taxa; Taxon/taxa, unique identification (Semantic URI); Taxon/taxa, unique identification (URI); Tetracosanoic acid, standard deviation; Tetracosanoic acid of total fatty acids; Tetradecanoic acid, standard deviation; Tetradecanoic acid of total fatty acids; trophic markers; Tropic_Seamount_comp; Wet mass; Year of observation
    Type: Dataset
    Format: text/tab-separated-values, 16550 data points
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  • 5
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    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2024-07-06
    Keywords: CTD, SEA-BIRD SBE 9 plus; CTD/Rosette; CTD-RO; DATE/TIME; DEPTH, water; Event label; LATITUDE; LONGITUDE; Oxygen; pH; pH sensor, SBE 27; POS534; POS534_10-2; POS534_16-1; POS534_17-1; POS534_33-1; POS534_34-1; Poseidon; Salinity; Station label; STEMM-CCS; Strategies for Environmental Monitoring of Marine Carbon Capture and Storage; Temperature, water; VCTD02B_2; VCTD06; VCTD07B; VCTD10; VCTD11B
    Type: Dataset
    Format: text/tab-separated-values, 473812 data points
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  • 6
    Publication Date: 2024-07-06
    Keywords: Ammonium; bioinvasion; DATE/TIME; decomposition; Eastern Mediterranean Sea; Nitrate; Nitrite; Nitrogen, organic, dissolved; Nitrogen, total dissolved; Nitrogen oxide; pH; Phosphate; Phosphorus, organic, dissolved; Phosphorus, total dissolved; Rhopilema nomadica; Silicate; Time in hours; Time point, descriptive; Treatment
    Type: Dataset
    Format: text/tab-separated-values, 530 data points
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  • 7
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    PANGAEA
    In:  GEOMAR - Helmholtz Centre for Ocean Research Kiel
    Publication Date: 2024-07-06
    Description: A gas inlet was installed at the bow of RV Poseidon. Atmospheric gas concentrations of CH4 and CO2 were measured continuously with a Picarro G2301-f analyzer.
    Keywords: CT; POS527; POS527-track; Poseidon; STEMM-CCS; Strategies for Environmental Monitoring of Marine Carbon Capture and Storage; Underway cruise track measurements
    Type: Dataset
    Format: application/zip, 20 datasets
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  • 8
    Publication Date: 2024-07-06
    Description: This study estimated the short-term decomposition effects of the invasive jellyfish Rhopilema nomadica on nutrient dynamics at the sediment-water interface in the Eastern Mediterranean Sea using core incubations. The degradation of R. nomadica has led to increased oxygen demand and acidification of overlying water as well as high rates of dissolved organic nitrogen and phosphate production.
    Keywords: bioinvasion; decomposition; Eastern Mediterranean Sea; Rhopilema nomadica
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 9
    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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  • 10
    Publication Date: 2024-07-05
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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