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The multi-species ecosystem model SS-DBEM integrates a species based model (DBEM) with the spectrum approach (SS). This model includes a large number of mechanisms and ecological processes such as population growth, movement, and dispersal of adults and larvae, as well as the ecophysiological effects of temperature, oxygen, and pH on body size, growth, mortality, and reproduction. The SS-DBEM model provides spatially (at a 0.5x0.5º resolution) and temporally (yearly) resolved predictions of changes in species’ size, abundance and biomass with consideration of competition. The competition algorithm describes the resource allocation between different species co-occurring in a spatial unit (thereafter cell) by comparing the flux of energy (in biomass) that can be supported (estimated with the SS model) with the energy demanded by the species predicted to inhabit that cell (estimated with the DBEM model). In addition, the environmental conditions are considered in the mechanisms and since there are different environmental conditions that are provided by the biogeochemical models, species responses are also different spatially. See readme.txt for scientific publications developing and using the model.

This repository contains the code and secondary data used for analysis and calculations on runoff, erosion and pesticide transport in particulate and dissolved phase. The analysis is done on an observational dataset in which rainfall-runoff events where monitored in a small agricultural catchment in Limburg, The Netherlands. 

The Cage Aquaculture Particulate Output and Transport (CAPOT) model is an easy to use and flexible farm-scale model that can be used to rapidly estimate particulate waste deposition from cage production. CAPOT is a suitable initial, rapid assessment model to give an overview of potential impact of particulate waste from new or expanded fish cage farms, with little operator expertise by a wide range of stakeholders. The model is wholly encapsulated within standard spreadsheet format (.xlsm). Visualisation of the output is achieved using proprietary contour plotting software, such as SurferTM (Golden Software. CA, USA) and open-source Geographic Information System (GIS) software, such as QGIS, but can be achieved in a more limited form within the spreadsheet itself. Visual Basic for Applications (VBA) macro scripts within the spreadsheets perform calculations and data formatting to produce outputs in Surfer and ESRI (GIS) grid formats. The model should not be used for environment regulation/licensing purposes without checking with the relevant regulatory authority. Disclaimer: This model is distributed in good faith as a work in progress and potentially subject to error. As such, the authors and the University of Stirling do not accept any liability for inaccurate predictions or their consequences. This model is employed at the users own risk.

gCube Catalogue (gCat) Client is a library designed to interact with REST API exposed by the gCat Service. gCube is an open-source software toolkit used for building and operating Hybrid Data Infrastructures enabling the dynamic deployment of Virtual Research Environments, such as the D4Science Infrastructure, by favouring the realisation of reuse-oriented policies. gCube has been used to successfully build and operate infrastructures and virtual research environments for application domains ranging from biodiversity to environmental data management and cultural heritage. gCube offers components supporting typical data management workflows including data access, curation, processing, and visualisation on a large set of data typologies ranging from primary biodiversity data to geospatial and tabular data. D4Science is a Hybrid Data Infrastructure combining over 500 software components and integrating data from more than 50 different data providers into a coherent and managed system of hardware, software, and data resources. The D4Science infrastructure drastically reduces the cost of ownership, maintenance, and operation thanks to the exploitation of gCube. The source code of this software version is available at: https://code-repo.d4science.org/gCubeSystem/gcat-client/releases/tag/v2.4.0

This publication contains software that can be used to pre-process data from the Globe at Night citizen science project, and then run an analysis to determine the rate of change in sky brightness. The software requires input data, which can be obtained directly from Globe at Night. The data used for our publication "Citizen scientists report global rapid reductions in the visibility of stars from 2011 to 2022" is published here, and can be used as input to the software. The process requires access to the World Atlas of Artificial Night Sky Brightness, which is also available from GFZ Data Services. Copyright © 2022 the authors and their institutions Licensed under the Apache License, Version 2.0 (the "License"); you may not use these files except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

This is the first release of the ZambeziWatercours_GCAM code

Viscoelastic COMSOL COMice-ve.mph for manuscript entitled "Elastic deformation plays a non-negligible role in Greenland’s outlet glacier flow" from Christmann et al., Communications Earth & Environment, https://doi.org/10.1038/s43247-021-00296-3, 2021. You can find here the mph file and all external data used in the finite element Comsol mph file. These files are also accessible via GitLab: https://gitlab.awi.de/jchristm/viscoelastic-79ng-greenland.git.

{"references": ["Chang W., Cheng J., Allaire J., Xie Y., McPherson J. (2020) Shiny: Web Application Framework for R. R package version 1.5.0. https://CRAN.R-project.org/package=shiny", "R Core Team (2020) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/", "Sievert C (2020) Interactive Web-Based Data Visualization with R, plotly, and shiny, Chapman and Hall/CRC, Florida. https://plotly-r.com", "Wickham H., Averic M., Bryan J., Chang W., McGowan L., Fran\u00e7ois R., Grolemund G., Hayes A., Henry L., Hester J., Kuhn M., Pedersen T., Miller E., Bache S., M\u00fcller K., Ooms J., Robinson D., Seidel D., Spinu V., Takahashi K., Vaughan D., Wilke C., Woo K., Yutani H. (2019) Welcome to the Tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686"]} Groundwater level time series visual inspection web application. It is R Shiny application that assists visual analysis of groundwater level time series and ensures an approach to correct errors, while maintaining original data intact. Few simulated groundwater time series with errors are provided to demonstrate the application. The simulated data is stored in SQLite database. This research is funded by the Latvian Council of Science, project “Spatial and temporal prediction of groundwater drought with mixed models for multilayer sedimentary basin under climate change”, project No. lzp-2019/1-0165.