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  • 2020-2024  (32,940)
  • 2020-2022  (5,403)
  • 2022  (38,343)
  • 2022  (38,343)
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  • 1
    Publication Date: 2024-05-28
    Description: The stability of the West Antarctic Ice Sheet is threatened by the incursion of warm Circumpolar Deepwater which flows southwards via cross-shelf troughs towards the coast there melting ice shelves. However, the onset of this oceanic forcing on the development and evolution of the West Antarctic Ice Sheet remains poorly understood. Here, we use single- and multichannel seismic reflection profiles to investigate the architecture of a sediment body on the shelf of the Amundsen Sea Embayment. We estimate the formation age of this sediment body to be around the Eocene-Oligocene Transition and find that it possesses the geometry and depositional pattern of a plastered sediment drift. We suggest this indicates a southward inflow of deep water which probably supplied heat and, thus, prevented West Antarctic Ice Sheet advance beyond the coast at this time. We conclude that the West Antarctic Ice Sheet has likely experienced a strong oceanic influence on its dynamics since its initial formation.
    Type: info:eu-repo/semantics/article
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  • 2
    Publication Date: 2024-05-28
    Description: Benthic cyanobacterial mats are increasingly reported to cover major coral reef areas. Although suggestions have been made that cyanobacterial mats impair coral reef health in multiple ways, information is lacking regarding the distribution, morphotypical variation and bacterial species composition of these microbial mats. As such, this study aimed to (1) Reveal the bacterial community diversity and composition of different mat morphotypes, (2) Identify the most abundant community members and closely related organisms, (3) Assess to what extent, morphotype, colonized substrate (coral or abiotic substrate), depth, and site were significant predictors of bacterial composition. Data were collected on reefs surrounding the island of Koh Tao (Gulf of Thailand). A total of 201 mats from 16 different locations around the island were classified into eight distinct morphotypes. Of these, the bacterial communities of 44 mats, representing colour groups from multiple sites, were characterized using 16S rRNA gene high-throughput sequencing. Our data revealed that Proteobacteria, Cyanobacteria, Bacteriodetes and Planctomycetes were the four most abundant phyla and occurred in all samples. Abundant cyanobacterial zero-radius operational taxonomic units (ZOTUs) were closely related to prokaryotic sequences found in previous studies of coastal mats (98–100%) and were assigned to genera in the order Oscillatoriales, e.g. Hormoscilla, Okeania, and Oscillatoria. Abundant proteobacterial ZOTUs were assigned to orders in the classes Alpha- and Gammaproteobacteria, e.g. Rhodobacterales, Rhizobiales and Alteromonadales. Abundant Bacteriodetes ZOTUs were mainly assigned to the class Bacteroidia and order Cytophagales. Our results showed that mats consist of a diverse and variable bacterial consortium, with mat colour (morphotype), substrate type and geographic location only explaining a small part of the total variation in composition.
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 3
    Publication Date: 2024-05-28
    Description: Traditional morphological methods for species identification are highly time consuming, especially for small organisms, such as Foraminifera, a group of shell-building microbial eukaryotes. To analyze large amounts of samples more efficiently, species identification methods have extended to molecular tools in the last few decades. Although a wide range of phyla have good markers available, for Foraminifera only one hypervariable marker from the ribosomal region (18S) is widely used. Recently a new mitochondrial marker cytochrome oxidase subunit 1 (COI) has been sequenced. Here we investigate whether this marker has a higher potential for species identification compared to the ribosomal marker. We explore the genetic variability of both the 18S and COI markers in 22 benthic foraminiferal morphospecies (orders Miliolida and Rotaliida). Using single-cell DNA, the genetic variability within specimens (intra) and between specimens (inter) of each species was assessed using next-generation sequencing. Amplification success rate was twice as high for COI (151/200 specimens) than for 18S (73/200 specimens). The COI marker showed greatly decreased intra- and inter-specimen variability compared to 18S in six out of seven selected species. The 18S phylogenetic reconstruction fails to adequately cluster multiple species together in contrast to COI. Additionally, the COI marker helped recognize misclassified specimens difficult to morphologically identify to the species level. Integrative taxonomy, combining morphological and molecular characteristics, provides a robust picture of the foraminiferal species diversity. Finally, we suggest the use of a set of sequences (two or more) to describe species showing intra-genomic variability additionally to using multiple markers. Our findings highlight the potential of the newly discovered mitochondrial marker for molecular species identification and metabarcoding purposes.
    Keywords: protist ; high-throughput sequencing ; metabarcoding ; intra-genomic variation ; benthic foraminifera
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 4
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    In:  Ecology and Evolution vol. 12 no. e9549 | H2020 European Institute of Innovation and Technology, Grant/Award Number: 813360; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/ Award Number: 16.161.301
    Publication Date: 2024-05-28
    Description: Monitoring community composition of Foraminifera (single-celled marine protists) pro-vides valuable insights into environmental conditions in marine ecosystems. Despitethe efficiency of environmental DNA (eDNA) and bulk-sample DNA (bulk-DNA) me-tabarcoding to assess the presence of multiple taxa, this has not been straightforwardfor Foraminifera partially due to the high genetic variability in widely used ribosomalmarkers. Here, we test the correctness in retrieving foraminiferal communities by me-tabarcoding of mock communities, bulk-DNA from coral reef sediment samples, andeDNA from their associated ethanol preservative using the recently sequenced cy-tochrome c oxidase subunit 1 (COI) marker. To assess the detection success, we com-pared our results with large benthic foraminiferal communities previously reportedfrom the same sampling sites. Results from our mock communities demonstrate thatall species were detected in two mock communities and all but one in the remainingfour. Technical replicates were highly similar in number of reads for each assigned ASVin both the mock communities and bulk-DNA samples. Bulk-DNA showed a signifi-cantly higher species richness than their associated eDNA samples, and also detectedadditional species to what was already reported at the specific sites. Our study con-firms that metabarcoding using the foraminiferal COI marker adequately retrieves thediversity and community composition of both the mock communities and the bulk-DNA samples. With its decreased variability compared with the commonly used nu-clear 18 S rRNA, the COI marker renders bulk-DNA metabarcoding a powerful tool toassess foraminiferal community composition under the condition that the referencedatabase is adequate to the target taxa.
    Keywords: bulk-sample ; DNA ; community composition ; coral reef ; environmental DNA ; foraminifera ; metabarcoding
    Repository Name: National Museum of Natural History, Netherlands
    Type: info:eu-repo/semantics/article
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  • 5
    Publication Date: 2024-05-28
    Description: In a marine environment that is rapidly changing due to anthropogenic activities and climate change, area-based management tools are often used to mitigate threats and conserve biodiversity. Marine protected areas (MPAs) are amongst the most widespread and recognized marine conservation tools worldwide, however, MPAs alone are inadequate to address the environmental crisis. The promotion of other effective area-based conservation measures (OECMs) under draft Target 3 of the Post-2020 Global Biodiversity Framework, i.e., conserving 30% of marine areas by 2030, holds promise to acknowledge sites and practices occurring beyond MPAs that contribute to conservation. Here, we evaluate the potential recognition of OECMs into Indonesia's national policy framework on marine resource management and provide the first-ever overview of distribution and types of potential marine OECMs in Indonesia, including a review of the existing evidence on conservation effectiveness. We identified 〉 390 potential marine OECMs, led by government, customary and local communities, or the private sector, towards diverse management objectives, including habitat protection, traditional/customary management, fisheries, tourism, or other purposes. While some evidence exists regarding the conservation effectiveness of these practices, the long-term impacts on biodiversity of all potential marine OECMs in Indonesia are unknown. Many OECM elements have been included in several national policies, yet there are no established mechanisms to identify, recognize and report sites as OECMs in Indonesia. We propose four transformational strategies for future OECM recognition in Indonesia, namely: (i) safeguard customary and traditional communities, (ii) leverage cross-sector and cross-scale collaboration, (iii) focus on delivering outcomes, and (iv) streamline legal frameworks. Our study shows that OECMs have the potential to play a significant role in underpinning marine area-based conservation in Indonesia, including supporting the Government of Indonesia in reaching national and international conservation targets and goals.
    Keywords: Area-based management ; Biodiversity conservation ; Customary management ; Fisheries ; Co-management ; Sustainable marine management
    Repository Name: National Museum of Natural History, Netherlands
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  • 6
    Publication Date: 2024-05-28
    Description: Ecological regime shifts in the marine realm have been recorded from a variety of systems and locations around the world. Coral reefs have been especially affected, with their benthic habitat changing from a dominance of stony corals to a dominance of other organisms such as fleshy algae. To detect changes in the benthic habitat of coral reefs, simple tools applicable on a global scale are necessary for future monitoring programs. Hence, the aim of this research is to explore the hypothesis that shifts in assemblages of large benthic foraminifera (LBF) can detect early signs of degradation in the reef benthic habitat. To do so, data on living assemblages of LBF collected between 1997 and 2018 at 12 islands in the Spermonde Archipelago (South Sulawesi, Indonesia) were analyzed. Foraminiferal specimens were morphologically identified to the species level and statistical analyses performed to assess changes in their assemblage composition. A clear temporal shift was observed. Typical foraminiferal assemblages in a coral-dominated (e.g., Amphistegina lobifera, Calcarina spengleri, Heterostegina depressa) and fleshy algaedominated (e.g., Neorotalia gaimardi, C. mayori) reef habitats were identified and significantly linked to the substrate type. Other species (e.g., Elphidium spp., Peneroplis planatus and Sphaerogypsina globulus) seem to reflect a spatial and temporal gradient of anthropogenic pollution from local inhabited islands and ongoing urban development on the mainland. Hence communities of LBF consistently follow gradual shifts in environmental conditions. Additionally to foraminiferal assemblages being an indicator for actual reef condition, closely monitoring LBF may provide early information on reef degradation, in time to take action against identified stressors (e.g., eutrophication or intensive fishing) at local and regional scales. The circumtropical distribution of LBF is such that they can be included worldwide in reef monitoring programs, conditional to calibration to the regional species pool.
    Keywords: Temporal dynamics ; Bioindicator ; Early detection ; Coral reef ; Spermonde Archipelago ; Indonesia
    Repository Name: National Museum of Natural History, Netherlands
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  • 7
    Publication Date: 2024-05-28
    Description: Foraminifera are a species-rich phylum of rhizarian protists that are highly abundant in most marine environments. Molecular methods such as metabarcoding have revealed a high, yet undescribed diversity of Foraminifera. However, so far only one molecular marker, the 18S ribosomal RNA, was available for metabarcoding studies on Foraminifera. Primers that allow amplification of foraminiferal mitochondrial cytochrome oxidase I (COI) and identification of Foraminifera species were recently published. Here we test the performance of these primers for the amplification of whole foraminiferal communities, and compare their performance to that of the highly degenerate LerayXT primers, which amplify the same COI region in a wide range of eukaryotes. We applied metabarcoding to 48 samples taken along three transects spanning a North Sea beach in the Netherlands from dunes to the low tide level, and analysed both sediment samples and meiofauna samples, which contained taxa between 42 mm and 1 mm in body size obtained by decantation from sand samples. We used single-cell metabarcoding (Girard et al., 2022) to generate a COI reference library containing 32 species of Foraminifera, and used this to taxonomically annotate our community metabarcoding data. Our analyses show that the highly degenerate LerayXT primers do not amplify Foraminifera, while the Foraminifera primers are highly Foraminifera- specific, with about 90% of reads assigned to Foraminifera and amplifying taxa from all major groups, i.e., monothalamids, Globothalamea, and Tubothalamea. We identified 176 Foraminifera ASVs and found a change in Foraminifera community composition along the beach transects from high tide to low tide level, and a dominance of single-chambered monothalamid Foraminifera. Our results highlight that COI metabarcoding can be a powerful tool for assessing Foraminiferal communities.
    Keywords: Foraminifera ; Metabarcoding ; Beach ; Community composition ; Intertidal ; Molecular ; biodiversity
    Repository Name: National Museum of Natural History, Netherlands
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  • 8
    Publication Date: 2024-05-28
    Keywords: Bio-optical in-situ data; Chlorophyll a, fluorometric or spectrophotometric determination; Chlorophyll a as carbon; Comment; DATE/TIME; DEPTH, water; ESA_OC-CCI; High Performance Liquid Chromatography (HPLC); Identification; LATITUDE; LONGITUDE; Ocean Colour; Ocean Colour multi-mission algorithm prototype system; OMAPS; Quality flag, chlorophyll; Quality flag, time; remote sensing
    Type: Dataset
    Format: text/tab-separated-values, 444442 data points
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  • 9
    Publication Date: 2024-05-28
    Description: Reported here are physical property records and sedimentological parameters generated from core and downhole logging measurements at ODP Site 909 (Fram Strait). The data are listed vs. depth and a newly derived age model. The composite P-wave velocity (Vp) profile of the uppermost 26 m consists of edited and spliced velocity measurements with the P-wave logger on sediment cores from Holes 909A and 909B. For the interval between 102 and 1000 mbsf in-situ velocity information from downhole logs (Sonic Digital Tool, processed postcruise data) at Hole 909C were used. Wet bulk density (WBD) data stem from nondestructive density measurements of whole-round core sections with a gamma-ray attenuation porosity evaluator (0 - 89 m), and from densities calculated from phasor induction resistivity downhole logging measurements (89 - 1016 m). Based on a new chronology, total mass accumulation rates (MAR) and accumulation rates for various grain size classes of the coarse fraction (〉63 µm) were recalculated. Original weight percentage data are from O'Connell et al. (1996) and from Wolf-Welling et al. (1996). Percentage silt data estimated from smear slides were used to calculate accumulation rates of silt. Estimated silt percentages as well as all original physical property measurements are from Myhre et al. (1995).
    Keywords: 151-909; COMPCORE; Composite Core; Fram Strait; Joides Resolution; Leg151; mass accumulation rate; North Greenland Sea; ocean drilling program; Ocean Drilling Program; ODP; Physical properties; Site 909
    Type: Dataset
    Format: application/zip, 4 datasets
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  • 10
    Publication Date: 2024-05-28
    Description: This dataset includes a global compilation of new and published 14C measurements of benthic foraminifera and deep-sea corals (from 0-to 49872 years BP). We synthesized this new dataset into basin-average 14C ventilation age values over the 25,000 years, along density surfaces associated with the upper and lower cells of global ocean overturning circulation (27.5 and 28 kg m^-3, respectively). The published datasets are from all ocean basins, even those not utilized in our synthesis. We also provide the basin-average estimates for the Atlantic, Southern, and Pacific Oceans as produced by the Rafter et al. 2022 study.
    Keywords: 0050PG; 0066PG; 145-883; 145-887; 146-893A; 167-1019A; 202-1240; 202-1242A; 341-U1419; 35MF20120125, OISO_21, INDIEN SUD 2; 47396B; 50-37KL; 64-480; 90b; AII125-8-55; AII125-8-56; Akademik M.A. Lavrentiev; ALV-3887-1549-004-007; ALV-3887-1549-004-009; ALV-3887-1549-004-012; ALV-3890-1407-003-001; ALV-3891-1459-003-002; ALV-3891-1758-006-003; AMOCINT, IMAGES XVII; ANT-XI/4; ANT-XXIII/9; ANT-XXVI/2; Argentine Basin; ARK-II/5; ARK-X/2; Azores; B34-91; BC; Bering Sea; Binary Object; BO04-PC11; Box corer; Brazil Basin; Burdwood_Bank; CALYPSO; CALYPSO2; Calypso Corer; Calypso Corer II; Calypso square corer; Calypso Square Core System; Canarias Sea; Cape_Horn; Caribbean Sea; CASQ; CASQS; CD159; CD159-10; CD159-15; CD159-17; CD38-17P; Celtic Sea; Cenderawasih Bay; Central Pacific; CH84-14; Charles Darwin; CHAT_10k; CHAT_16k; CHAT-3K; CHAT-5K; Chatham Rise; COMPCORE; Composite Core; Conrad Rise; Core; CORE; Core1471; Core2088; Core21210009; Core2307; Core2631; Core2657; Core2706; Core2774; Core47396; Core654; Core660; Core936; Corner Rise; Denmark Strait; Drake Passage; DRILL; Drilling/drill rig; Eastern Equatorial Pacific; Eastern slope of Kurile Basin; East Pacific; Emperor Seamounts; EN06601; EN066-39GGC; Endeavor; Equatorial East Pacific; ESTASE1; EW0408; EW0408-26JC; EW0408-85JC; EW0408-87JC; Exp341; F2-92-P3; F8-90-G21; File content; Galapagos; Galápagos Islands; GC; GC_POI; GeoB1503-1; GeoB2104-3; GeoB7149-2; GeoB7162-6; GeoB7163-7; GeoB7167-6; GGC; GGC5; gh02-1030; Giant box corer; Giant gravity corer; Giant piston corer; GIK17940-1; GIK23243-2 PS05/431; GKG; Glomar Challenger; GPC; Gravity corer; Gravity corer (Kiel type); Gravity corer (POI); GS07-150-17/1GC-A; GS07-150-20/2A; Gulf of Alaska; Gulf of California; H209; H213; HH12-946MC; HU72-021-7; HU89038-8PC; IMAGES III - IPHIS; IMAGES IV-IPHIS III; IMAGES V; IMAGES VIII - MONA; IMAGES VII - WEPAMA; IMAGES XII - MARCO POLO; IMAGES XV - Pachiderme; Indian Ocean; INOPEX; Interim_Seamount; Japan Trench; Jean Charcot; JM-FI-19PC; Joides Resolution; JPC; JPC30; JT96-09; JT96-09PC; Jumbo Piston Core; KAL; KALMAR II; Kasten corer; KL; KN_USA; KN11002; KN159-5; Knorr; KNR073-04-003; KNR110-50; KNR110-66; KNR110-82a; KNR110-82GGC; KNR140; KNR140-01JPC; KNR140-02JPC; KNR140-12JPC; KNR140-2-12JPC; KNR140-2-22JPC; KNR140-22JPC; KNR140-2-30GGC; KNR140-2-51GGC; KNR140-26GGC; KNR140-30GGC; KNR140-37JPC; KNR140-39GGC; KNR140-43GGC; KNR140-50GGC; KNR140-51GGC; KNR140-56GGC; KNR140-66GGC; KNR159-5; KNR159-5-36GGC; KNR159-5-78GGC; KNR176-17GC; KNR178; KNR178-2GGC; KNR178-32JPC; KNR195-5-CDH23; KNR195-5-CDH26; KNR195-5-CDH41; KNR195-5-GGC43; KNR197-10; KNR197-10CDH42; KNR197-10-CDH42; KNR197-10-CDH46; KNR197-10-GGC17; KNR197-10-GGC36; KNR197-10-GGC5; KNR198-CDH36; KNR198-GGC15; KNR31GPC5; KNR733P; KNR734P; KNR736P; KOL; KOMEX; KOMEX II; KR02-15-PC06; Kronotsky Peninsula; KT89-18-P4; Lakshadweep Sea; Laurentian fan; Leg145; Leg146; Leg167; Leg202; Leg64; Le Suroît; LPAZ21P; LV27/GREGORY; LV27-2-4; LV29-114-3; LV29-2; M16/2; M23/2; Marion Dufresne (1972); Marion Dufresne (1995); Maurice Ewing; Mazatlan; MCSEIS; MD012378; MD01-2378; MD012386; MD01-2386; MD012416; MD01-2416; MD012420; MD01-2420; MD022489; MD02-2489; MD022519; MD02-2519; MD03-2697; MD03-2707; MD052896; MD05-2896; MD052904; MD05-2904; MD07-3076; MD07-3076Q; MD07-3088; MD08-3169; MD08-3180; MD09-3256; MD09-3256Q; MD09-3257; MD106; MD111; MD114; MD122; MD12-3396Cq; MD126; MD13; MD134; MD147; MD159; MD168; MD173; MD189; MD77-176; MD972106; MD97-2106; MD972120; MD97-2120; MD972121; MD97-2121; MD972138; MD97-2138; MD982165; MD98-2165; MD982181; MD98-2181; MD99-2334; ME0005A; ME0005A-24JC; ME0005A-43JC; Melville; Meteor (1986); ML1208-01PC; MONITOR MONSUN; MR01-K03; MR06-04_PC04A; MUC; Multichannel seismics; MultiCorer; MV99-GC38; MV99-MC17/GC32/PC10; MV99-MC19/GC31/PC08; NEMO; Nesmeyanov25-1-GGC15; Nesmeyanov25-1-GGC18; Nesmeyanov25-1-GGC20; Nesmeyanov25-1-GGC27; New_England_Seamounts; North Atlantic; North Greenland Sea; North Pacific/Gulf of California/BASIN; North Pacific Ocean; Northwest Atlantic; Norwegian Sea; OCE326-GGC14; OCE326-GGC26; OCE326-GGC5; off Chile; off Nova Scotia; OSIRIS III; Pacific Ocean; PALEOCINAT; PC; Philippine Sea; PICABIA; Piston corer; Piston corer (BGR type); Piston corer (Kiel type); PLDS-007G; PLDS-1; Pleiades; Polarstern; PS05; PS1243-2; PS2606-6; PS2644-2; PS30; PS30/144; PS31; PS31/160; PS69; PS69/907-2; PS69/912-3; PS69/912-4; PS75/059-2; PS75/100-4; PS75/104-1; PS75 BIPOMAC; PUCK; RAPiD-10-1P; RAPiD-15-4P; RAPiD-17-5P; RBDASS05; RC24; RC24-8GC; RC27; RC27-14; RC27-23; Remote operated vehicle; RETRO-2; RNDB-GGC15; RNDB-GGC5; RNDB-PC11; RNDB-PC13; Robert Conrad; ROV; RR0503-36JPC; RR0503-41JPC; RR0503-64JPC; RR0503-79JPC; RR0503-831C; RR0503-83GC; S67-FFC15; S794; S931; Sakhalin shelf and slope; Sars_Seamount; Scotia Sea; Sea of Okhotsk; SEDCO; Sediment corer; Shackleton_Fracture_Zone; SHAK03-6K; SHAK05-3K; SHAK06-4K; SHAK06-5K; SHAK10-10K; SHAK14-4G; Shirshov Ridge; SK129-CR2; SL; Smithsonian_48735.1; SO156/2; SO156/3; SO161/3; SO161/3_22; SO178; SO178-13-6; SO201/2; SO201-2-101; SO201-2-12KL; SO201-2-77; SO201-2-85; SO202/1; SO202/1_18-6; SO213/2; SO213/2_76-2; SO213/2_79-2; SO213/2_82-1; SO213/2_84-1; SO95; Sonne; SOPATRA; South Atlantic; South Atlantic Ocean; South China Sea; Southern Alaska Margin: Tectonics, Climate and Sedimentation; South of Iceland; South Pacific Ocean; South Tasman Rise; Southwest Pacific Ocean; SPOC; Station 6, MD189-3396; SU90-08; Thomas G. Thompson (1964); Thomas Washington; Timor Sea; TNO57-21; TR163-22; TR163-23; TR163-31; TT154-10; TTN13-18; TTXXX; U938; V34; V34-98; V35; V35-5; V35-6; Vema; Vigo; VINO19-4-GGC17; VINO19-4-GGC37; VM21-29; VM21-30; VM23-81; VM28-122; VM28-238; VNTR01; VNTR01-10GC; W8709A; W8709A-13; Wecoma
    Type: Dataset
    Format: text/tab-separated-values, 8 data points
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