All content

Biome-BGC ESI version 1.4.1 (3)

• Download

Biome-BGC is a process-based biogeochemical model that can be used to simulate carbon, nitrogen and water fluxes of different terrestrial ecosystems. The model can help us to quantify a broad range of ecosystem service indicators. These newly developed measures include: annual wood increment, yearly production of grasslands or croplands, total average carbon stock, annual evapotranspiration, damping of ecosystem daily water outflow, living and dead biomass protecting the soil against erosion,...

Created: 2013-08-12 | Last updated: 2014-10-04

Credits: Ferenc HORVATH Dora Krasser Peter Ittzes BioVeL

Biome-BGC CARBON 1.2 (4)

• Download

Biome-BGC is a process-based biogeochemical model that can be used to simulate carbon, nitrogen and water fluxes of different terrestrial ecosystems. A new version of the model, called Biome-BGC MuSo was developed to perform more realistic simulations in terms of soil hydrology, and improved ecosystem management options essentially (Hidy et al. 2012; Hidy & Barcza 2014). The Biome-BGC CARBON service executes a single simulation run at a given geographic location under that distinctive environ...

Created: 2013-06-04 | Last updated: 2015-06-12

Credits: Ferenc HORVATH Dora Krasser Peter Ittzes Zoltan BARCZA BioVeL

Attributions:

Biome-BGC SA 1.3 (1)

• Download

Biome-BGC is a process-based biogeochemical model that can be used to simulate carbon, nitrogen and water fluxes of different terrestrial ecosystems. Two models have been implemented: the Biome-BGC v4.1.1 Max Planck Institute model, and the newly developed Biome-BGC MuSo 3.0 model. Performance, success or failure of these models are highly dependent on parameter settings and variation. Due to the high number of parameters (around 40 and 60 for 4.1.1 MPI and MuSo respectively) and the non-line...

Created: 2014-10-04

Credits: Ferenc HORVATH Dora Krasser Peter Ittzes Zoltan BARCZA BioVeL

Microbial Metagenomic Trait Calculation an... (3)

• Download

This workflow calculates the microbial traits of your metagenome and retrieves additional traits data from the Microbial Metagenomic Trait Database http://mb3is.megx.net/mg-traits. The list of traits: - GC content - Variance of GC content - Dinucleotides - Number of rRNA - Codon usage - Amino acid composition - Acidic to basic amino acids ratio - % of Transcriptional factors - % of classified reads - Functional content - Functional diversity - Taxonomic content - Taxonomic diversity As ...

Created: 2014-10-03 | Last updated: 2015-06-12

Credits: Renzo Antonio Fernandez-Guerra

Attributions: Microbial Metagenomic Trait Statistical Analysis Workflow

Biome-BGC GLUE 1.3 (2)

• Download

Biome-BGC is working with a lots of ‘a priori’ unknown and hard to obtain model parameters. Therefore the parameterization is a critical step of using the model. Parameteres can be estimated using inverse calibration techniques based on measurement data, which means that the model is being calibrated. Measurement data have to be collected with respect to the model in order to compare them. Comparison is based on misfit measure (e.g. a sort of likelihood value), which is the function of the di...

Created: 2014-10-02 | Last updated: 2014-10-09

Credits: Peter Ittzes Ferenc HORVATH Dora Krasser Zoltan BARCZA Doborl BioVeL

Exploration of fishing scenarios (1)

• Download

This workflow must run after the workflow: Resident killer whale-chinook salmon interactions. The interaction workflows generates a PostWorkspace file, this is a zip file and it is an R Workspace that transfers values from the Resident killer whale-chinook salmon interactions (main) workflow to the Exploration of fishing scenario (post-processing) workflow. This workflow merges statistical inference derived from linkages between RKW vital rates (survival probability and fecundity rates) a...

Created: 2014-09-26

Credits: Maria Paula Balcazar-Vargas Antonio Velez-Espino Andres Araujo Jon Giddy Francisco Quevedo

Attributions: Resident killer whale-chinook salmon interactions