Tags


Click a tag to remove it from package

Edit Species Groups of Package

Edit Parameter of Package

Edit DOI Package

Choose a project for this package

FRED
  • Contact
  • GDPR policy
  • Imprint
  • About
  • Sign Up
  • Login
  • SEARCH
  • Search and find
  • Packages
  • Map
  • By Category ...
    • Study sites
    • Sampling locations
    • Parameters
    • Sampling types
    • Species groups
    • Current DOIs

1067 Lake Constance dry weight particulate organic matter chlorophyll organismal C:P ratios

Title
Lake Constance dry weight particulate organic matter chlorophyll organismal C:P ratios
Species Groups
Study site
Lake Constance
Sampling locations
Lake Constance Überlingen Sampling location
location
47.762909, 9.130241
location
type
lake
state
natural
code
description
Contact
Ursula Gaedke ORC ID; Link to ORCID Landing Page of user
Licence for data
All rights reserved. Please send a request to Ursula Gaedke if you like to use this data. Mind our data policy: IGB Data Policy

Data files (e.g. excel)

TitlecreatedFiletypeActions
Supplement_Table.xlsx 12. Mar. 2026 14:16 datatable: .xlsx Download
Chlorophyll.xlsx 12. Mar. 2026 14:16 datatable: .xlsx Download
DW_POM_depth_resolved_1980-1997.xlsx 12. Mar. 2026 14:16 datatable: .xlsx Download
C_to_P_ratio_phytoplankton_seston_1995.xlsx 12. Mar. 2026 14:16 datatable: .xlsx Download

Machine Readable Metadata Files

FRED provides all metadata of this package in a maschine readable format. There is a pure XML file and one EML file in Ecological Metadata Language. Both files are published under the free CC BY 4.0 Licence.

  • Lake_Constance_dry_weight_particulate_organic_matter_chlorophyll_organismal_C:P__ratios.xml
  • Lake_Constance_dry_weight_particulate_organic_matter_chlorophyll_organismal_C:P__ratios.eml

You are about to leaving FRED and visting a third party website. We are not responsible for the content or availability of linked sites.

To remain on our site, click Cancel.

Parsing data File

Estimated Time:

Why does it take so much time?

While parsing a file, the database has to perform various tasks, some of them needs a lot of CPU and memory for larger files.

  • preprocessing: means automatic detection of headlines, table body, format values or csv-separators
  • copying: means read the file cell by cell and copy all elements to the database. During this format settings can be calculated (for example iso-time)
  • analyzing: check out for different data types (can be time, numeric or text)