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opencc-zeroJan 2021View details →

FIG. 5 in A nearly complete skeleton of the oldest definitive erycine boid (Messel, Germany)

FIG. 5. — Parabasisphenoid: A-C, parabasisphenoid of HLMD-Me 9723, holotype of Rageryx schmidi n. gen., n. sp., in dorsal, ventral, and left lateral views, respectively. Portions of the parietal that articulated with the basisphenoid wings are probably artifactually associated here (blurred), but a more precise separation is not possible; D-F, parabasisphenoid of Eryx johnii BM 1930.5.8.31 in dorsal, ventral, and left lateral views, respectively; G-I, parabasisphenoid of Lichanura trivirgata CM 145332 in dorsal, ventral, and left lateral views, respectively. Scale bar: A-C, 1 mm; D-I, 2 mm.

opencc-zeroJan 2021View details →

FIG. 2 in A nearly complete skeleton of the oldest definitive erycine boid (Messel, Germany)

FIG. 2. — Maxilla: A-C, left maxilla of HLMD-Me 9723, holotype of Rageryx schmidi n. gen., n. sp., in dorsal, lateral and medial views, respectively; D-F, left maxilla of Eryx jaculus (Tü-VI.1935) in dorsal, lateral and medial views, respectively; G-I, left maxilla of Lichanura trivirgata (CM 145332) in dorsal, lateral and medial views, respectively. Scale bar: A-C, 1 mm; D-I, 2 mm.

FIGURES 20 24 in Brazilian Sesiidae in the collection of the Universität des Saarlandes, Saarbrücken, Germany (Lepidoptera)

FIGURES 20 24. Female genitalia of clearwing moths. 20, Carmenta plaumanni, Allotype; 21, C. asema; 22, C. laticraspedontis, Holotype; 23, C. angarodes; 24, C. splendens.

FIGURES 1 - 6. Adult clearwing moths. 1 in Brazilian Sesiidae in the collection of the Universität des Saarlandes, Saarbrücken, Germany (Lepidoptera)

FIGURES 1 - 6. Adult clearwing moths. 1, Carmenta aerosa, male, Lectotype; 2, C. asema, female, Holotype; 3, Synanthedon martenii, female, Holotype;; 4, C. plaumanni, male, Holotype (dorsal aspect); 5, C. plaumanni, male, Holotype (ventral aspect); 6, C. laticraspedontis, female, Holotype (dorsal aspect, abdomen removed);

FIGURES 7 - 13. Adult clearwing moths. 7, C in Brazilian Sesiidae in the collection of the Universität des Saarlandes, Saarbrücken, Germany (Lepidoptera)

FIGURES 7 - 13. Adult clearwing moths. 7, C. laticraspedontis, female, Holotype (ventral aspect, abdomen removed); 8, Synanthedon hemigymna, female, Holotype; 9, S. flavostigma, female, Holotype. 10, Carmenta angarodes, male, (Lectotype of semitrista Zuk., n. syn); 11, C. angarodes, female (post. portion of abdomen removed); 12, C. splendens, female, Allotype; 13, C. leptosoma, male, Holotype.

opencc-zeroDec 2003View details →

FIGURE 9 – 10. 9 in New fossil lace bugs (Heteroptera: Tingidae) from the Middle Eocene of the Grube Messel (Germany), with a catalog of fossil lace bugs

FIGURE 9 – 10. 9, Dorsal habitus of holotype of Chorotingiotes prisca (SMF MeI 7690); 10, Detail of areolate hemelytra of C. prisca (SMF MeI 7690).

opencc-zeroDec 2003View details →

FIGURE 3 – 6. 3 in New fossil lace bugs (Heteroptera: Tingidae) from the Middle Eocene of the Grube Messel (Germany), with a catalog of fossil lace bugs

FIGURE 3 – 6. 3, Dorsal habitus of holotype of Exmesselensis disspinosus (SMF MeI 6301); 4, Detail of areolate hemelytra of E. disspinosus (SMF MeI 6301); 5, Lateral habitus of paratype (SMF MeI 6958); 6, Detail of head and antennae structures (SMF MeI 6958).

FIGURES 14 19 in Brazilian Sesiidae in the collection of the Universität des Saarlandes, Saarbrücken, Germany (Lepidoptera)

FIGURES 14 19. Male gentialia of clearwing moths. 14, Carmenta angarodes; 15, C. asema; 16, C. leptosoma, Paratype; 17, C. aerosa; 18, C. splendens, Holotype; 19, C. plaumanni, Paratype.

FIGURES 20 24 in Brazilian Sesiidae in the collection of the Universität des Saarlandes, Saarbrücken, Germany (Lepidoptera)

FIGURES 20 24. Female genitalia of clearwing moths. 20, Carmenta plaumanni, Allotype; 21, C. asema; 22, C. laticraspedontis, Holotype; 23, C. angarodes; 24, C. splendens.

FIGURES 7 - 13. Adult clearwing moths. 7, C in Brazilian Sesiidae in the collection of the Universität des Saarlandes, Saarbrücken, Germany (Lepidoptera)

FIGURES 1 - 6. Adult clearwing moths. 1 in Brazilian Sesiidae in the collection of the Universität des Saarlandes, Saarbrücken, Germany (Lepidoptera)

opencc-by-sa-4.0Aug 2017View details →

Scenario delay times regarding the expansion of the transmission system in Germany based on social acceptance

The data is closely related to Mester et al. 2017. Integrating Social Acceptance of Electricity Grid Expansion into Energy System Modeling: A Methodological Approach for Germany. In Wohlgemuth, V., Fuchs-Kittowski, F. and Wittmann, J. (eds.) Advances and New Trends in Environmental Informatics: Stability, Continuity, Innovation. Cham: Springer International Publishing, pp. 115 - 129. doi: 10.1007/978-3-319-44711-7_10. Each dataset contains the assumed delays in commissioning of German transmission grid projects given in years influenced by social acceptance based on three different scenarios - low, mid and high. In the attached file VerNetzen-Verzoegerungszeiten-Kreise.csv these delay times are given per district, which can be identified by their key, "Regionalschlüssel", and corresponding geo data (EPSG: 25832) of the administrative area provided by the Federal Agency for Cartography and Geodesy. © GeoBasis-DE / BKG 2014 (data was changed) Additionally other files contain scenario data for each transmission grid project. Geo data in these files is provided by the Bundesnetzagentur (data was changed). The dataset was created in the context of the interdisciplinary research project VerNetzen and is described in detail in the final project report: VerNetzen Degel, M., Christ, M., Grünert, J., Becker, L., Wingenbach, C., Soethe, M., Bunke, W.-D., Mester, K., und Wiese, F. (2016). VerNetzen: Sozial-ökologische und technisch-ökonomische Modellierung von Entwicklungspfaden der Energiewende. IZT Berlin, Europa-Universität Flensburg, Deutsche Umwelthilfe e.V., pp. 72-92, 102-105, 135-142. Deutsch: Die Daten stehen in engem Zusammenhang mit Mester et al. 2017. Integrating Social Acceptance of Electricity Grid Expansion into Energy System Modeling: A Methodological Approach for Germany. In Wohlgemuth, V., Fuchs-Kittowski, F. and Wittmann, J. (eds.) Advances and New Trends in Environmental Informatics: Stability, Continuity, Innovation. Cham: Springer International Publishing, pp. 115 - 129. doi: 10.1007/978-3-319-44711-7_10. Je Datensatz ist angegeben, welche akzeptanz-bedingten Verzögerungen in Jahren für die Inbetriebnahme von Übertragungsnetzausbauvorhaben in den drei Szenarien - low, mid und high - zu erwarten sind. In der Datei VerNetzen-Verzoegerungszeiten-Kreise.csv werden Verzögerungen je Landkreis aufgeführt. Diese können durch den Regionalschlüssel oder durch Geodaten (EPSG: 25832) des Bundesamtes für Kartographie und Geodäsie zugeordnet werden. © GeoBasis-DE / BKG 2014 (Daten geändert) Darüber hinaus enthalten die anderen Dateien Daten je Vorhaben. Die entsprechenden Geodaten in diesen Dateien wurden von der Bundesnetzagentur bereitgestellt (Daten geändert). Der Datensatz ist im Kontext des interdisziplinären Forschungsprojekts VerNetzen entstanden und ist ausführlich im Projektabschlussbericht beschrieben: VerNetzen Degel, M., Christ, M., Grünert, J., Becker, L., Wingenbach, C., Soethe, M., Bunke, W.-D., Mester, K., und Wiese, F. (2016). VerNetzen: Sozial-ökologische und technisch-ökonomische Modellierung von Entwicklungspfaden der Energiewende. IZT Berlin, Europa-Universität Flensburg, Deutsche Umwelthilfe e.V., S.72-92, S.102-105, S.135-142.

opencc-by-4.0Aug 2022View details →

Results from national testing programs on the occurrence of chemical contaminants in food and feed - Germany

In the framework of Articles 23 and 33 of Regulation (EC) No 178/2002 EFSA has received from the European Commission a mandate (M-2010-0374) to collect all available data on the occurrence of chemical contaminants in food and feed. These data are used in EFSA’s scientific opinions and reports on contaminants in food and feed.   The presence of unauthorised substances or chemical contaminants in food may pose a risk factor for public health and can cause a negative impact on the quality of food.  Commission Recommendations and Regulations on occurrence monitoring are in place for several contaminants of interest, some of which can be found here below:   <ul> <li>Commission Regulation (EU) 625/2017, on the application of food and feed law</li> <li>Commission Delegated Regulation (EU) 2022/931</li> <li>Commission Implementing Regulation (EU) 2022/932</li> <li>Commission Regulation (EU) 2023/915, on maximum levels for certain contaminants in food and repealing Regulation (EC) No 1881/2006</li> </ul> These datasets contain the results of sampling that was designed according to national testing programs for a variety of contaminants in food and feed, as reported under the Chemical Monitoring Data Collection 2024, 2023, 2022, 2021, and 2020, split by sampling year (data element ‘sampY’).  More details are available in last year's finalised call for data ‘<a href="https://www.efsa.europa.eu/en/call/annual-call-continuous-collection-chemical-contaminants-occurrence-data-food-and-feed">Annual call for continuous collection of chemical contaminants occurrence data in food and feed | EFSA</a>’. REPORTING AUTHORITIES CONTRIBUTING TO EACH DATA COLLECTION:  OCC-CHEMMON2020 – Federal Office of Consumer Protection and Food Safety OCC-CHEMMON2021 – Federal Office of Consumer Protection and Food Safety OCC-CHEMMON2022 – Federal Office of Consumer Protection and Food Safety OCC-CHEMMON2023 – Federal Office of Consumer Protection and Food Safety OCC-CHEMMON2024 – Federal Office of Consumer Protection and Food Safety

opencc-by-4.0Sep 2024View details →

CAMELS-DE: hydrometeorological time series and attributes for 1582 catchments in Germany

<h2>Description</h2> CAMELS-DE provides a comprehensive collection of hydro-meteorological timeseries data (e.g. discharge, water level, precipitation, air temperature) and catchment attributes for 1582 streamflow gauges across Germany. The time series data is in daily resolution and spans up to 70 years, from January 1951 to December 2020. The static catchment attributes include information on topography, soils, land cover, hydrogeology and human influences. Additionally, the dataset includes discharge simulations from a regional Long-Short Term Memory (LSTM) network and a conceptual hydrological model (HBV), providing benchmark data for future hydrological modelling studies in Germany. The accompanying data description gives information on data sources, the structure of the data set and contains extensive information on time series and catchment attribute variables. In addition, up-to-date benchmark results of the LSTM and HBV are provided. <blockquote> Important: As CAMELS-DE is continuously developed and updated, please ensure that you cite the correct version of the dataset that you are using. The CAMELS-DE data description paper is available here: <a href="https://doi.org/10.5194/essd-16-5625-2024">https://doi.org/10.5194/essd-16-5625-2024</a>. </blockquote> Information about the code and methods for generating CAMELS-DE can be found here: <a title="CAMELS-DE Processing Pipeline" href="https://doi.org/10.5281/zenodo.12760336" target="_blank" rel="noopener">CAMELS-DE Processing Pipeline</a>. CAMELS-DE is also part of the Caravan project, a global hydrological dataset. Due to the use of data products that are available beyond the Germany national boundaries, Caravan-DE includes  305 additional streamflow gauges, resulting in a total of 1887 streamflow gauges: <a href="https://doi.org/10.5281/zenodo.13320514">https://doi.org/10.5281/zenodo.13320514</a>. <h3>Disclaimer for discharge and water level data provided by the German federal state agencies:</h3> english: The state agencies do not guarantee the accuracy or completeness of the discharge or water level data provided. In addition, all hydrological data may be subject to future revisions, including adjustments to the rating curves or corrections of errors. Therefore, it is necessary to obtain the most recent discharge time series directly from the federal state authorities for projects that require water law permits. Additionally, the regulations of the respective federal state apply and specific enquiries should be made as needed. It is also important to note that the state agencies explicitly disclaim any warranty as to the accuracy or completeness of the data and therefore any liability claims against any of the federal states are also excluded. german: Die Ländesämter gewährleisten nicht die Genauigkeit oder Vollständigkeit der bereitgestellten Abfluss oder Wasserstandsdaten. Zudem können alle hydrologischen Daten zukünftigen Überarbeitungen unterliegen, einschließlich Anpassungen der Wasserstands-Abflussbeziehung oder der Korrektur von Fehlern. Daher ist es notwendig, die aktuellsten Abflusszeitreihen direkt bei den Landesbehörden zu beziehen, falls Wasserrechtsgenehmigungen erforderlich sind. Zusätzlich gelten die Vorschriften des jeweiligen Bundeslandes, und spezifische Anfragen sollten bei Bedarf gestellt werden. Es ist ebenfalls wichtig zu beachten, dass die staatlichen Behörden ausdrücklich jegliche Gewährleistung hinsichtlich der Genauigkeit oder Vollständigkeit der Daten ausschließen und somit auch jegliche Haftungsansprüche gegenüber einem der Bundesländer ausgeschlossen sind. <h3>Changelog</h3> <ul> <li>v1.1.0 <ul> <li>LSTM benchmark results are now based on a LSTM with 10 ensemble members, changing the median NSE in the testing period from 0.83 to 0.85 <div> <ul> <li>The columns discharge_spec_sim_lstm and discharge_vol_sim_lstm in timeseries_simulated are now based on the median values of the 10 ensemble members.</li> <li>The column NSE_lstm in CAMELS_DE_simulation_benchmark.csv is now calculated from the median simulations of the 10 ensemble members</li> <li>model_parameters/LSTM/CAMELS_DE_epochs_training_lstm.zip now contains the epochs of the 10 ensemble members</li> </ul> </div> </li> <li>The columns NSE_lstm, NSE_hbv and training_perc_complete in CAMELS_DE_simulation_benchmark.csv were calculated from 2001 - 2020, now corrected to 2000 - 2020</li> <li>Fixed a bug in the calculation of high_prec_dur and low_prec_dur in CAMELS_DE_climatic_attributes.csv calculation (thank you to Bastian Klein from BfG for reporting this issue)</li> <li>Bayern: removed blank space after gauge and water body name and removed water body name from some gauge names, where it was included as "[gauge_name]_[water_body_name]", e.g. "Würzburg_Main" -> "Würzburg", water body name is now only included in the `water_body_name` column in<code> </code>CAMELS_DE_topographic_attributes.csv</li> <li>Nordrhein-Westfalen: corrected some wrong river names in CAMELS_DE_topographic_attributes.csv</li> <li>Sachsen: added `gauge_elevation_metadata` information to CAMELS_DE_topographic_attributes.csv</li> </ul> </li> </ul> <ul> <li>v1.0.0 <ul> <li>CAMELS-DE v1.0.0 is the version of the dataset that is described by the <a href="https://doi.org/10.5194/essd-2024-318">CAMELS-DE data description paper</a>.</li> <li>Addition of the federal state of Saarland, resulting in 27 additional catchments and coverage of all federal states except the city states of Berlin, Bremen and Hamburg. This also leads to a change in the title of the dataset from 1555 catchments to 1582 catchments.</li> <li>Addition of HBV model parameters and LSTM model training period epochs.</li> <li>Catchment DE911970: Removal of erroneous zero discharge values at the beginning of the measurement period.</li> <li>Minor fixes such as the elimination of discrepancies between the variable names in the dataset and in the data description.</li> <li>We were able to identify and fix some of these problems based on the feedback from the community, thank you very much!</li> </ul> </li> </ul>

opencc-by-4.0Aug 2022View details →

Text-fig. 1. Situation of Early Miocene plant localities. a: Central Europe with Brno area and other fossil sites mentioned in text (1 – Znojmo and Přímětice, 2 – Oberdorf, 3 – Modrý Kameň Basin, 4 – Lipovany, 5 – Ipolytarnóc; CZ – the Czech Republic, PL – Poland, SK – Slovakia, H – Hungary, A – Austria, D – Germany). b: Brno area with Líšeň municipal district indicated. c: Líšeň municipal district with fossil sites indicated by asterisk. in A New Early Miocene (Ottnangian) Flora Of The "Rzehakia Beds" From Brno-Líšeň

Text-fig. 1. Situation of Early Miocene plant localities. a: Central Europe with Brno area and other fossil sites mentioned in text (1 – Znojmo and Přímětice, 2 – Oberdorf, 3 – Modrý Kameň Basin, 4 – Lipovany, 5 – Ipolytarnóc; CZ – the Czech Republic, PL – Poland, SK – Slovakia, H – Hungary, A – Austria, D – Germany). b: Brno area with Líšeň municipal district indicated. c: Líšeň municipal district with fossil sites indicated by asterisk.

opencc-by-4.0Aug 2023View details →

Individual multilocus genotypes from four populations of Helichrysum arenarium (Asteraceae) from Belgium and Germany

Individual multilocus genotypes based on 11 microsatellites loci from four populations of Helichrysum arenarium (Asteraceae) from Belgium and Germany. For more details, see Van Rossum et al. 2024 "Genetic diversity assessment of Helichrysum arenarium (Asteraceae) for the genetic restoration of declining populations" in Ecology and Evolution

Figure 7 in A new genus of Mantispidae (Insecta: Neuroptera) from the Eocene of Germany, with a review of the fossil record and palaeobiogeography of the family

Figure 7. Fossil record and inferred time ranges of subgroups of Mantispidae, superimposed upon a preliminary phylogenetic tree, based mainly on Lambkin (1986a), modified here. CAL, Calomantispinae; DREP, Drepanicinae; MANT, Mantispinae; SYM, Symphrasinae. Dashed lines and '?' indicate uncertainty in relationships and time ranges.

Figure 5 in A new genus of Mantispidae (Insecta: Neuroptera) from the Eocene of Germany, with a review of the fossil record and palaeobiogeography of the family

Figure 5. The forewing pterostigma of the Jurassic mantispids. A, Liassochrysa stigmatica Ansorge & Schlüter 1990, holotype MB.I 5046 (No. LDA301, formerly from the Ansorge collection, Dobbertin, Germany); (photograph converted to standard right dorsal view); photograph by C. Neumann, MB. B, Promantispa similis, holotype PIN 2784/1080 (Karatau, Kazakhstan; Karabastau Formation). R1, first branch of radius; Sc, subcosta. Scale bar = 1 mm for both parts.

Figure 4 in A new genus of Mantispidae (Insecta: Neuroptera) from the Eocene of Germany, with a review of the fossil record and palaeobiogeography of the family

Figure 4. Apical portion of forewing margin of Symphrasites eocenicus showing trichosors (arrows). Scale bar = 100 µm. Laser scanning photograph.

Figure 2 in A new genus of Mantispidae (Insecta: Neuroptera) from the Eocene of Germany, with a review of the fossil record and palaeobiogeography of the family

Figure 2. Symphrasites eocenicus gen. et sp. nov., holotype MeI 8384. A, photograph. B, drawing of the forewing. Scale bar = 1 mm.