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Molecular determinants of host specificity of maize-, rice- and mango-pathogenic species of the genus Fusarium

Fusarium species of the Gibberella fujikuroi species complex cause serious diseases on different crops such as rice, wheat and maize. An important group of plant pathogens is the Gibberella fujikuroi species complex (GFC) of closely related Fusarium species which are associated with specific hosts; F. verticillioides and F. proliferatum are particularly associated with maize where they can cause serious ear-, root-, and stalk rot diseases. Two other closely related species of the GFC, F. mangiferae and F. fujikuroi, which share about 90Prozent sequence identity with F. verticillioides, are pathogens on mango and rice, respectively. All of these species produce a broad spectrum of secondary metabolites such as phytohormones (gibberellins, auxins, and cytokinins), and harmful mycotoxins, such as fumonisin, fusarin C, or fusaric acid in large quantities. However, the spectrum of those mycotoxins might differ between closely related species suggesting that secondary metabolites might be determinants for host specificity. In this project, we will study the potential impact of secondary metabolites (i.e. phytohormones and certain mycotoxins) and some other species-specific factors (e.g. species-specific transcription factors) on host specificity. The recently sequenced genomes of F. mangiferae and F. fujikuroi by our groups and the planned sequencing of F. proliferatum will help to identify such determinants by genetic manipulation of the appropriate metabolic pathway(s).

Abfluss Pegel Krems 2 - Börnsee

Alle Daten sind Rohdaten ohne Gewähr. Das Land Schleswig-Holstein übernimmt keine Gewähr für die Aktualität, Korrektheit, Vollständigkeit oder Qualität der dargestellten Informationen. Haftungsansprüche sind grundsätzlich ausgeschlossen. [Informationen zum Pegel](https://hsi-sh.de/pegel/pegel.html?mstnr=114397) Der Datensatz enthält folgende Felder * **Zeit** im Format `yyyy-MM-dd HH:mm:ss` * **Abfluss** in m³/s * **Status** Angabe "1" bedeutet qualitätsgesichert, "0" bedeutet nicht qualitätsgesichert * **Wertetyp** Angabe "mw" bedeutet Mittelwert, "thw" bedeutet Tidehochwasser, "tlw" bedeutet Tideniedrigwasser Zeichensatz ist ISO-8859-1, Spaltentrenner ist Semikolon.

Gemeindeverzeichnis

Amtliches Verzeichnis der Gemeinden und Ämter des Landes Mecklenburg-Vorpommern (5 Teile) Veröffentlicht unter V012 Gemeindeverzeichnis Mecklenburg- Vorpommern Teil I Gemeindeverzeichnis nach Kreisen Teil II Gemeindeverzeichnis nach Ämtern Teil III Gemeindeverzeichnis alphabetisch Teil IV Ortsteilverzeichnis nach Gemeinden Teil V Ortsteiverzeichnis alphabetisch Preis: 10,00/ 23,00 EUR Papier/ Diskette

Immobilisation of arsenic in paddy soil by iron(II)-oxidizing bacteria

Arsenic-contaminated ground- and drinking water is a global environmental problem with about 1-2Prozent of the world's population being affected. The upper drinking water limit for arsenic (10 Micro g/l) recommended by the WHO is often exceeded, even in industrial nations in Europe and the USA. Chronic intake of arsenic causes severe health problems like skin diseases (e.g. blackfoot disease) and cancer. In addition to drinking water, seafood and rice are the main reservoirs for arsenic uptake. Arsenic is oftentimes of geogenic origin and in the environment it is mainly bound to iron(III) minerals. Iron(III)-reducing bacteria are able to dissolve these iron minerals and therefore release the arsenic to the environment. In turn, iron(II)-oxidizing bacteria have the potential to co-precipitate or sorb arsenic during iron(II)- oxidation at neutral pH followed by iron(III) mineral precipitation. This process may reduce arsenic concentrations in the environment drastically, lowering the potential risk for humans dramatically.The main goal of this study therefore is to quantify, identify and isolate anaerobic and aerobic Fe(II)-oxidizing microorganisms in arsenic-containing paddy soil. The co-precipitation and thus removal of arsenic by iron mineral producing bacteria will be determined in batch and microcosm experiments. Finally the influence of rhizosphere redox status on microbial Fe oxidation and arsenic uptake into rice plants will be evaluated in microcosm experiments. The long-term goal of this research is to better understand arsenic-co-precipitation and thus arsenic-immobilization by iron(II)-oxidizing bacteria in rice paddy soil. Potentially these results can lead to an improvement of living conditions in affected countries, e.g. in China or Bangladesh.

Trophic interactions in the soil of rice-rice and rice-maize cropping systems

Subproject 3 will investigate the effect of shifting from continuously flooded rice cropping to crop rotation (including non-flooded systems) and diversified crops on the soil fauna communities and associated ecosystem functions. In both flooded and non-flooded systems, functional groups with a major impact on soil functions will be identified and their response to changing management regimes as well as their re-colonization capability after crop rotation will be quantified. Soil functions corresponding to specific functional groups, i.e. biogenic structural damage of the puddle layer, water loss and nutrient leaching, will be determined by correlating soil fauna data with soil service data of SP4, SP5 and SP7 and with data collected within this subproject (SP3). In addition to the field data acquired directly at the IRRI, microcosm experiments covering the broader range of environmental conditions expected under future climate conditions will be set up to determine the compositional and functional robustness of major components of the local soil fauna. Food webs will be modeled based on the soil animal data available to gain a thorough understanding of i) the factors shaping biological communities in rice cropping systems, and ii) C- and N-flow mediated by soil communities in rice fields. Advanced statistical modeling for quantification of species - environment relationships integrating all data subsets will specify the impact of crop diversification in rice agro-ecosystems on soil biota and on the related ecosystem services.

Pollen and environmental reconstruction, Holocene dynamics of tropical rainforest, climate, fire, human impact and land use in Sulawesi and Sumatra, Indonesia

The present-day configuration of Indonesia and SE Asia is the results of a long history of tectonic movements, volcanisms and global eustatic sea-level changes. Not indifferent to these dynamics, fauna and flora have been evolving and dispersing following a complicate pattern of continent-sea changes to form what are today defined as Sundaland and Wallacea biogeographical regions. The modern intraannual climate of Indonesia is generally described as tropical, seasonally wet with seasonal reversals of prevailing low-level winds (Asian-Australian monsoon). However at the interannual scale a range of influences operating over varying time scales affect the local climate in respect of temporal and spatial distribution of rainfall. Vegetation generally reflects climate and to simplify it is possible to distinguish three main ecological elements in the flora of Malaysia: everwet tropical, seasonally dry tropical (monsoon) and montane. Within those major ecological groups, a wide range of specific local conditions caused a complex biogeography which has and still attract the attention of botanists and biogeographers worldwide. Being one of the richest regions in the Worlds in terms of species endemism and biodiversity, Indonesia has recently gone through intensive transformation of previously rural/natural lands for intensive agriculture (oil palm, rubber, cocoa plantations and rice fields). Climate change represents an additional stress. Projected climate changes in the region include strengthening of monsoon circulation and increase in the frequency and magnitude of extreme rainfall and drought events. The ecological consequences of these scenarios are hard to predict. Within the context of sustainable management of conservation areas and agro-landscapes, Holocene palaeoecological and palynological studies provide a valuable contribution by showing how the natural vegetation present at the location has changed as a consequence of climate variability in the long-term (e.g. the Mid-Holocene moisture maximum, the modern ENSO onset, Little Ice Age etc.). The final aim of my PhD research is to compare the Holocene history of Jambi province and Central Sulawesi. In particular: - Reconstructing past vegetation, plant diversity and climate dynamics in the two study areas Jambi (Sumatra) and Lore Lindu National Park (Sulawesi) - Comparing the ecological responses of lowland monsoon swampy rainforest (Sumatra) and everwet montane rainforests (Sulawesi) to environmental variability (vulnerability/resilience) - Investigating the history of human impact on the landscape (shifting cultivation, slash and burn, crop cultivation, rubber and palm oil plantation) - Assessing the impact and role of droughts (El Niño) and fires - Adding a historical perspective to the evaluation of current and future changes.

Schwerpunktprogramm (SPP) 1374: Biodiversitäts-Exploratorien; Exploratories for Long-Term and Large-Scale Biodiversity Research (Biodiversity Exploratories), Teilprojekt: Synthese und Meta-Analyse mikrobieller Daten für die Biodiversitäts- Exploratorien

In der ersten Förderungsphase konzentrierte sich das mikrobielle Synthese-Projekt auf die theoriebasierte Entwicklung neuer Strategien für die Synthese von heterogenen aber komplementären Datensätzen aus den Exploratorien. Dazu wurden neuartige Werkzeuge zur Modellierung von Interaktionen und mikrobiellen Nischen entwickelt. Die Anwendung auf Datensätze aus den Exploratorien erbrachte bereits zahlreiche Ergebnisse. Darauf aufbauend soll die Synthese mikrobieller Daten und Modellierung auf unterschiedliche Fragestellungen und Komplexitätsebenen angewandt werden. Die Bedeutung der räumlichen und zeitlichen Heterogenität und der Qualität organischen Materials für mikrobielle Nischen soll ermittelt werden. Die in der ersten Phase entwickelten Interaktionsmodelle sollen weiterentwickelt und auf Bodengemeinschaften unterschiedlicher organismischer Komplexität angewandt werden. Die Ergebnisse dieser Analysen mikrobieller Nischenanalysen und Modellierungen von verschiedenen Exploratorien-Datensätzen werden anschließend genutzt, um anspruchsvolle Analyse-Werkzeuge (Turing's theory, dynamische Strukturgleichungsmodelle, Price equation) weiterzuentwickeln. Mit diesen neuen Ansätzen sollen grundlegende ökologisch Fragen, insbesondere zur raum-zeitlichen Dynamik auf kleinsträumlichen Skalen oder zur Dynamik und Resilienz mikrobieller Gemeinschaften bei Änderungen der Landnutzung weitergehend beantwortet werden. Die Ergebnisse der geplanten Analysen mikrobieller Bodenorganismen werden in die übergreifende Synthesearbeiten innerhalb der Exploratorien eingebracht.

Wasserstand Pegel Krems 2 - Börnsee

Alle Daten sind Rohdaten ohne Gewähr. Das Land Schleswig-Holstein übernimmt keine Gewähr für die Aktualität, Korrektheit, Vollständigkeit oder Qualität der dargestellten Informationen. Haftungsansprüche sind grundsätzlich ausgeschlossen. [Informationen zum Pegel](https://hsi-sh.de/pegel/pegel.html?mstnr=114397) Der Datensatz enthält folgende Felder * **Zeit** im Format `yyyy-MM-dd HH:mm:ss` * **Wasserstand** in cm * **Status** Angabe "1" bedeutet qualitätsgesichert, "0" bedeutet nicht qualitätsgesichert * **Wertetyp** Angabe "mw" bedeutet Mittelwert, "thw" bedeutet Tidehochwasser, "tlw" bedeutet Tideniedrigwasser Zeichensatz ist ISO-8859-1, Spaltentrenner ist Semikolon.

Digitales Landschaftsmodell 1:1 000 000

Das Digitale Landschaftsmodell 1:1 000 000 (DLM1000) beschreibt die topographischen Objekte der Landschaft und das Relief der Erdoberfläche der Bundesrepublik Deutschland im Vektorformat.Die Objekte werden einer bestimmten Objektart zugeordnet und durch ihre räumliche Lage, ihren geometrischen Typ, beschreibende Attribute und Beziehungen zu anderen Objekten (Relationen) definiert. Der Datenbestand umfasst Objektarten sowie deren wichtigste Attribute, z. B. Straßen, Wege, Eisenbahnen, Gewässer, Siedlungen, Vegetation, Verwaltungsgrenzen (bis zur Gemeindeebene) und das Relief in Form von Höhenlinien und weiteren Oberflächenformen. Welche Objektarten das DLM1000 im Detail beinhaltet und wie die Objekte gebildet werden, ist im ATKIS®-Objektartenkatalog (ATKIS®-OK1000) festgelegt

Model Output Statistics for KREMS (11070)

DWD’s fully automatic MOSMIX product optimizes and interprets the forecast calculations of the NWP models ICON (DWD) and IFS (ECMWF), combines these and calculates statistically optimized weather forecasts in terms of point forecasts (PFCs). Thus, statistically corrected, updated forecasts for the next ten days are calculated for about 5400 locations around the world. Most forecasting locations are spread over Germany and Europe. MOSMIX forecasts (PFCs) include nearly all common meteorological parameters measured by weather stations. For further information please refer to: [in German: https://www.dwd.de/DE/leistungen/met_verfahren_mosmix/met_verfahren_mosmix.html ] [in English: https://www.dwd.de/EN/ourservices/met_application_mosmix/met_application_mosmix.html ]

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