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1024 Spree phytoplankton biomass

Title
Spree phytoplankton biomass
Period
1996-01-01 till 2022-12-31
Period length
26 years 11 months 30 days
Sampling interval
14 days Irregular Interval
Note on interval
depending on site, gaps in winter.
Description
River Spree phytoplankton biomass This data forms part of the long-term monitoring programme in Lake Müggelsee and the River Spree.
Species Groups
Phytoplankton
Study site
Spree
Sampling locations
Spree, Neu Zittau, Spreebrücke (IGB-Messstelle 8)
location
52.392355, 13.744298
location
type
running water / river (Fluss)
state
code
S65
description
Spree, Müggelhort (bei Eis alt 204)
location
52.433061499691206, 13.676100969314577
location
type
river
state
code
S67A
description
landing stage, sampling on ice, corresponds to S67
Spree, Müggelhort MS3
location
52.432304672883284, 13.676948547363283
location
type
River
state
channeld
code
S67,MS3,203
description

measuring point inflow lake Müggelsee

Spree, Große Tränke bei Fürstenwalde (IGB-Messstelle 7)
location
52.368603, 13.997045
location
type
running water / river (Fluss)
state
code
S64
description
Parameters

biology:

biomass
name
biomass
description

Plankton biomass
Contact
Sabine Hilt
Licence for data
All rights reserved. Please send a request to Sabine Hilt if you like to use this data. Mind our data policy: IGB Data Policy

Data files (e.g. excel)

TitlecreatedFiletypeActions
BM_Spree_bis_2022_Liste_NZ_bis_MS3.xlsx 16. Oct. 2025 09:23 datatable: .xlsx
Error: To access file, please get in touch with the contact person.

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.

  • Spree_phytoplankton_biomass.xml
  • Spree_phytoplankton_biomass.eml

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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)