Sammlung von Daten für die Auswertung bei der Ökosystemforschung Wattenmeer 1989-2000
Sonderdaten für die Auswertung im Rahmen der Ökpsystemforschung Wattenmeer (1989-2000)
Beikarte des Rechtskräftigen Regionales Raumordnungsprogramm des Landkreises Rotenburg (Wümme) in zeichnerischer Darstellung zur Information über die Ermittlung der Vorranggebiete für Windenergienutzung
The project is part of the COST action FP0603 Forest models for research and decision support in sustainable forest management (http://www.cost.esf.org/index.php?id=143&action number=FP0603) which aims at extending the scope of forest models from growth only to population dynamics and ecophysiology. Rationale: For sustainable forest management over large areas and for simulating different forest functions especially under changing conditions, different aspects of the system forest' must be modelled jointly: ecophysiological/biogeochemical processes, population dynamics, spatial interactions, and horizontal/vertical species stand structure. We develop a forest model with a stand-size grain suitable to be applied on large areas for assessment of, e.g., climate change or management effects on forest functions. This is achieved by merging and if necessary up- and down-scaling model functions of ecophysiological and population dynamical processes contained in existing models (single tree physiology, local scale ecophysiological, empirical forest growth, spatio-temporal forest landscape, and dynamic global vegetation models). Drought is predicted to occur more frequently with climate change, thus the main focus is on drought and the mechanisms how it affects the trees. Research questions: What are the mechanisms by which drought affects trees? Which is the best (sufficiently accurate and efficient) way to model and simulate these mechanisms? How can population dynamics and ecophysiology be combined in a landscape scale model concerning - allocation of water and carbohydrates to trees and organs? - spatial heterogeneity of soil water and trees? Methods: The project builds on the climate-driven forest landscape model TreeMig (Lischke et al., 2006). Process descriptions from various existing models are compiled, evaluated and included into TreeMig. This involves a thorough scaling of process formulations. Drought effects, involving soil water balance, stomata regulation, photosynthesis, CO2 fertilization effects, allocation of carbohydrates, dynamics of reserve pools and the relationship between these and regeneration, growth and mortality are studied in literature and other models and included into MEPHYSTO.
# Faszination Nächtlicher Vogelzug A web component for visualizing migratory bird detections on an interactive map. Built with React, MapLibre GL, and the BirdWeather GraphQL API. Designed for embedding into CMS platforms like Contao. ## Tech Stack - **React 19** + **TypeScript** (Vite) - **MapLibre GL** -- WebGL map rendering (Stadia Maps dark theme) - **Supercluster** -- per-species spatial clustering - **Apollo Client 4** -- GraphQL data fetching with caching - **GraphQL Code Generation** -- type-safe queries from BirdWeather schema - **SunCalc** -- astronomical day/night calculations - **Tailwind CSS 4** + **Ant Design 6** -- UI - **Vitest** -- testing ## Features - **Interactive map** with color-coded detection clusters per species - **Timeline animation** with autoplay, step controls, and throttled slider - **Night-only mode** that compresses inactive daytime hours using SunCalc sunrise/sunset calculations - **Day/night overlay** showing the terminator (day/night boundary) as a real-time GeoJSON polygon - **Species search** with autocomplete and availability checking per map viewport - **Supplementary layers** (light pollution, noise mapping via WMS) - **Web component** (`<zug-birdnet>`) for CMS embedding without routing ## Project Structure ``` src/ main.tsx Web component registration App.tsx Root component, species selection state api/ fragments.ts GraphQL fragments (DetectionItem, SpeciesItem) queries.ts GraphQL queries (detections, species, search) useDetections.ts Detection fetch hook with prefetching components/ DatesProvider.tsx Time state context (date range, animation, night mode) MapProvider.tsx MapLibre GL instance context SpeciesDropdown.tsx Species selection with search autocomplete Timeline.tsx Date picker, animation slider, playback controls LayersDropdown.tsx Toggle info layers (light pollution, noise) InfoPopup.tsx Map info marker popups map/ Map.tsx MapLibre GL initialization and rendering clusterUtils.ts Per-species Supercluster index creation colorUtils.ts MapLibre paint expression builder mapStyles.ts Map layer definitions usePersistentColors.ts Stable color assignment per species infopoints.ts Static info marker data lib/ apollo-client.ts Apollo Client with cache type policies buildAvailableSpeciesQuery.ts Dynamic aliased query generation getDayPolygon.ts Day/night terminator polygon calculation getTranslatedSpeciesName.ts i18n species name lookup isNotNull.ts, hasNonNullProp.ts Type guard utilities throttle.ts Throttle utility gql/ Auto-generated GraphQL types (do not edit) ``` ## Architecture Three React context providers compose the application: ``` ApolloProvider GraphQL caching and data fetching DatesProvider Date range, animation state, night-only time segments MapProvider MapLibre GL map instance App Species selection, filtered detections, color mapping ``` **Data flow:** Apollo fetches detections for the current bounding box and date range. Detections are filtered client-side by the visualisation time window (controlled by the timeline slider). Each species gets its own Supercluster index for independent color-coded clustering. Cluster features are rendered via MapLibre GL layers with dynamic `match` paint expressions. **GraphQL:** Queries and fragments are defined in `src/api/` and typed via `@graphql-codegen/client-preset`. Run `npm run codegen` after schema changes to regenerate `src/gql/`. ## Development ```sh npm install npm run dev ``` The dev server uses a self-signed SSL certificate via `@vitejs/plugin-basic-ssl`. Accept the browser warning on first visit. Other commands: ```sh npm run build # Production build npm run test # Run tests npm run lint # ESLint npm run codegen # Regenerate GraphQL types ``` ## Build & Integration Run `npm run build` to produce the `dist/` folder. The build outputs stable filenames (no hashes) and splits vendor dependencies into separate chunks for caching: ``` dist/ index.html assets/ index.css App styles (Tailwind + Ant Design) index.js Application code, React, Supercluster, dayjs, SunCalc maplibre.js MapLibre GL antd.js Ant Design + icons apollo.js Apollo Client + graphql ``` Only `index.js` changes on application updates. Vendor chunks are cache-stable between deploys. To embed the web component, include the built CSS and JS, then use the custom element: ```html <link rel="stylesheet" href="/assets/index.css"> <script type="module" src="/assets/index.js"></script> <zug-birdnet></zug-birdnet> ``` No routing. The component is self-contained and can be placed anywhere on the page. Third-party CMS integration (e.g., Contao) only needs to include the built assets and the custom element tag. ## Configuration App-level settings are in `src/config.ts`: | Option | Default | Description | |---|---|---| | `SHOW_DEMO_INFOPOINTS` | `false` | Show static info markers on the map (demo/development only) |
Beim Regionalen Raumordnungsprogramm (RROP) handelt es sich um ein strategisches Instrument zur räumlichen Steuerung, Ordnung der unterschiedlichen Nutzungsansprüche. Dabei sollen die miteinander konkurrierenden raumbezogenen Planungen, wie beispielsweise Land- und Forstwirtschaft, gewerbliche Wirtschaft, Verkehr, Naturschutz, Wohnraumbedarf u.v.m aufeinander abgestimmt werden. Das RROP ist somit auf der Ebene des Landkreises ein übergeordnetes und zusammenfassendes Planwerk. Basis für die Vielfalt an Themen bildet das Raumordnungsprogramm 2003 mit der 1. Änderung 2010.
Inhaltsverzeichnis des Kartenteils der ersten Gesamtfortschreibung des Regionalpla-nes für die Anhörung entsprechend Sächsisches Landesplanungsgesetz (SächsLPlG): Karte 1 Raumnutzung (1:100 000) Karte 2 Siedlungswesen (1:280 000) Karte 3 Raumstruktur (1:280 000) Karte 4 Tourismus (1:280 000) Karte 5 Landschaftsbereiche mit besonderen Nutzungsanforderungen (1:200 000) Karte 6 Sanierungsbedürftige Bereiche der Landschaft (1:200 000) Karte 7 Tierhaltungsstandorte (1:280 000) Karte 8 Bergbauumgang (1:280 000)
Inhaltsverzeichnis des Kartenteils der ersten Gesamtfortschreibung des Regionalplanes für die Anhörung entsprechend Sächsisches Landesplanungsgesetz (SächsLPlG): Karte 1 Karte "Zentrale Orte und Nahbereiche" (Erläuterungskarte) (1:400 000) Karte 2 Karte "Raumstruktur" (Festlegungskarte) (1:400 000) Karte 3 Karte "Freizeit, Erholung, Tourismus" (Erläuterungskarte) (1:200 000) Karte 4 Karte "Straßennetzausbau" (Erläuterungskarte) (1:400 000) Karte 5 Karte "Sorbisches Siedlungsgebiet" (Erläuterungskarte) (1:400 000) Karte 6 Karte "Ökologisches Verbundsystem und regionale Grünzüge" (Festlegungskarte) (1:100 000) Karte 7 Karte "Landschaftspflege, -sanierung und -entwicklung" (Festlegungskarte) (1:100 000) Karte 8 Karte "Raumnutzung" (Festlegungskarte) Kartenteil zu Anhang 4 (Fachplanerische Inhalte des Landschaftsrahmenplans) Karte "Naturräumliche Gliederung der Region" (1:400 000) Karte "Integriertes Entwicklungskonzept" (1:100 000)
Diese Kurzbeschreibung entspricht dem <abstract> aus dem GetCapabilities-Dokument. - Diese Vorlage ist für WMS / View-Service eingerichtet. Für die Beschreibung eines WFS müssen Sie die entsprechenden Werte ändern und auch das Schlagwort infoFeatureAccessService setzen.
The pattern of plant nutrient uptake in a soil profile is the result of complex processes occurring at the cellular or sub-cellular levels but affecting the whole-plant behaviour in function of the plant environment that varies strongly in time and space. The plant nutrient acquisition depends on root architecture and growth, on soil properties and heterogeneity, and on the 3-D distribution of nutrients and water. Equally important is how these parameters interact, as for instance how the nutrient distribution and soil properties and heterogeneity impact root growth or how nutrient and water limitation affect assimilate allocation. Mathematical modelling using a spatial resolution that resolves the spatial structure of the root structure and the nutrient and water distribution is therefore needed to quantitatively account for these complex and interacting processes and to predict plant nutrient uptake behaviour under environmental constraints. The main goal of the project is to build a modelling platform able to describe 3-D flow and transport processes in the soil to individual roots of an entire root system (WP1). Model parameters will be derived from specific experiments performed at the plant scale in the research group (WP3) and stored in a specific data warehouse (WP2). The impact of different parameters, which describe root growth and nutrient uptake at the single root scale, on nutrient uptake at the soil profile scale, will be investigated based on scenario analyses (WP4). Data on water and nutrient uptake and root growth from plant and field scale experiments will be compared with model predictions to validate the model. Simulations with the 3-D root scale model will be used to validate hypotheses and parameterizations of larger scale 1-D models that do not describe processes at the scale of individual roots (WP5 and SP10).
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