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Satellite Color Images, Vegetation Indices, and Metabolism Indices from Bautzen, Germany from 1985 – 2023

The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.

Oekophysiologie von Singvoegeln auf dem Zug

'- Physiologische Anpassungen an den Langstreckenflug. - Fettaufbaurate und Rastdauer von ziehenden Singvoegeln in Rastgebieten in Abhaengigkeit von Umweltfaktoren. - Zugstrategien von Singvoegeln.

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Landshut, Germany from 1984 – 2023

The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.

Untersuchungen zum Nachweis und zur Wirkung von Mykotoxinen

Analyse des Vorkommens von Mykotoxinen. Entwicklung neuer Nachweistechniken fuer Mykotoxine. Erforschung der Stoffwechselwege von Aflatoxin.

Zellphysiologische Wirkungen von Metallsalzen

Intracellulaere Lokalisierung von Metallionen; Wirkungen auf den Zellstoffwechsel, vor allem den Photosyntheseapparat unter besonderer Beruecksichtigung spezifischer Enzyme; bisher gepruefte Elemente: Blei, Zink, Cadmium und Aluminium.

Schwerpunktprogramm (SPP) 1530: Flowering time control: from natural variation to crop improvement, Metabolit-Regulation von Cryptochrom 2 Aktivität und Blühzeitpunkt

Der UV-A/Blaulichtrezeptor Cryptochrom 2 (cry2) spielt eine zentrale Rolle bei der photoperiodischen Blühinduktion. Wichtige Komponenten der Signalleitung von cry2 sind mehrere nah verwandte bHLH Transkriptionsfaktoren (CIB1, CIB2, CIB4, CIB5), die Blaulicht-abhängig an cry2 binden, als Heterodimere an nicht-kanonische E-Box Motive in der Promotorregion des FLOWERING LOCUS T (FT) Gens binden und hierdurch die Expression dieses zentralen Blühgens induzieren. Weiterhin interagiert cry2 im Blaulicht mit SPA-Proteinen und inhibiert damit die Aktivität der E3 Ubiquitin Ligase CONSTITUTIVE PHOTOMORPHOGENESIS 1 (COP1), die maßgeblich am Abbau des FT-Transkriptionsaktivators CONSTANS (CO) beteiligt ist. Wir haben gezeigt, dass der FAD-Chromophor im signalaktiven Zustand von cry2 in der neutralen Semichinonform vorliegt und die Bildung dieser Form durch Metabolite wie ATP und NADPH verstärkt wird. Gerichte und strukturbasierte Mutagenese von CRY2 lieferte Hinweise darauf, welche Aminosäuren für die Metabolit-Kontrolle erforderlich sind. Diese Information soll genutzt werden, um die Rolle dieser Metabolite bei der photoperiodischen Blühinduktion aufzuklären. Geplant ist hierfür die Expression entsprechender cry2 Allele in planta und die Analyse der generierten Pflanzenlinien hinsichtlich Blühverhalten, FT-Expression und Interaktion mit down-stream Komponenten. Diese Untersuchungen sollen durch in vitro Studien mit rekombinanten Proteinen komplettiert werden. Im Gegensatz zum Wildtyp Allel von cry1 induziert die cry1L407F Mutante gesteigerte Expression von CO und FT sowie frühes Blühen im Kurztag. In vitro Analysen zeigten ein tryptisches Spaltmuster von cry1L407F im Dunkeln, welches dem von Wildtyp cry1 im Blaulicht entspricht. Das geplante Vorhaben soll klären, ob cry1L407F die gleichen Komponenten wie cry2 für die Induktion von FT nutzt. Hierfür sind Analysen der cry1L407F Mutante im cib1/cib2/cib5 Hintergrund sowie Interaktionsstudien mit cry2 Partnern geplant. Direkte Zusammenarbeiten ergeben sich mit den Vorhaben von Christian Jung (Blühkontrolle bei Beta vulgaris) und Markus Schmid (Regulation des Blühzeitpunkts durch Trehalose-6-P).

Vorkommen, Induktion und Metabolismus von UV-Schutzverbindungen in antarktischen Makroalgen

Einwirkungen von Luftverunreinigungen auf physiologische Prozesse

Eine moeglichst genaue Kenntnis der Wirkungen von Immissionskomponenten im pflanzlichen Stoffwechsel ist wichtig fuer die Frueherkennung von immissionsbedingten Pflanzenschaedigungen, das Verstaendnis des Schaedigungsverlaufs und die Festsetzung von Immissionsgrenzwerten zum Schutze der Pflanzen. Trotz einer grossen Anzahl von Publikationen auf diesem Gebiet weiss man ueber diese Vorgaenge auf der biochemischen Ebene noch wenig. Bei den in der Begasungsanlage der EAFV durchgefuehrten Versuchen an Waldbaeumen standen Reaktionen der CO2-Fixierung, sowie Aenderungen im Schwefelmetabolismus im Vordergrund.

Satellite Color Images, Vegetation Indices, and Metabolism Indices from Frankfurt-Oder, Germany from 1984 – 2023

The "Germany Mosaic" is a time series of Landsat satellite images and vectorized segments covering the entirety of Germany from 1984 to 2023. The image data are divided into TK100 sheet sections (see further details: Blattschnitt der Topographischen Karte 1:100 000). The dataset provides optimized 6-band imagery for each year, representing summer (May to July) and autumn (August to October) seasons, along with vegetation indices such as NDVI (Normalized Difference Vegetation Index) and NirV (Near-Infrared Reflectance of Vegetation) for the same periods. Additionally, vectorized "zones" of approximately homogeneous pixels are available for each year. The spectral properties of the image data and the morphological characteristics of these zones are included as vector attributes (see Documentation: "Mosaic (1984–2023) - Data Description"). An overview of the coverage and quality of all sheet sections is provided as a vector layer titled D-Mosaik_Sheet-Sections within this document. The Germany Mosaic can also be considered a spatial-temporal Data Cube, enabling advanced analysis and integration into workflows requiring multi-dimensional data. This structure allows users to perform operations such as querying data across specific time periods, analyzing trends over decades, or aggregating spatial information to generate tailored insights for a wide range of research applications. In mid-latitudes, seasonal variations in vegetation—and consequently in the image data—are typically more pronounced than changes occurring over several years. The temporal segmentation of the dataset has been designed to encompass the entire vegetation period (May to October), with the division into summer and autumn periods capturing seasonal metabolic shifts in natural biotopes. This segmentation also records most agricultural changes, including sowing and harvesting activities. Depending on weather conditions, the individual image data represent either the median, mean value, or the best available image for the specified time period (see Documentation: "Mosaic (1984–2023) - Data Description). Remote sensing has become an indispensable tool for environmental research, particularly in landscape analysis. Beyond conventional applications, the Germany Mosaic supports the development of digital twins in environmental system research. By providing detailed spatial and temporal data, this dataset enables the modeling of virtual ecosystems, facilitating simulations, scenario testing, and predictive analyses for sustainable management. Moreover, the spatial and temporal trends captured by remotely sensed parameters complement traditional approaches in biological, ecological, geographical, and epidemiological research.

Einfluss von Organochlorverbindungen auf inkubierte Rinderlinsen

Bei der Benutzung von Organochlorverbindungen als Schaedlingsbekaempfungsmittel geraten diese Substanzen an und in die Augen der Landarbeiter. Es ist das Ziel der vorliegenden Studie, den Einfluss dieser Verbindungen auf den Stoffwechsel und die Funktion des Auges zu untersuchen; Rinderlinsen dienen dabei als Testobjekt.

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