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540 Schlachtensee physico-chemical and phytoplankton data

Title
Schlachtensee physico-chemical and phytoplankton data
Period
1979-09-18 till 2007-12-19
Period length
28 years 3 months 1 day
Description

Schlachtensee:

- physico-chemical data 

- phytoplankton

 

Krumme Lanke:

- physico-chemical data

 

Species Groups
Study site
Schlachtensee
Sampling locations
Sampling buoy III
location
52.44504538625874, 13.221788406372072
location
type
Buoy
state
code
description
Sampling buoy I
location
52.44070296953342, 13.206982612609863
location
type
Buoy
state
code
description
Sampling buoy II
location
52.44208945042938, 13.216166496276857
location
type
Buoy
state
code
description
Sampling buoy IV
location
52.45372893649206, 13.237366676330568
location
type
Buoy
state
code
description
Sampling buoy V
location
52.45081281501627, 13.231272697448732
location
type
Buoy
state
code
description
Parameters

physics:

secchi depth
name
secchi depth
description

synonyms
Sichttiefe, Transparancy
water temperature
name
water temperature
description

determination by temperature-probe

synonyms
water temp, Wassertemperatur

chemistry:

C, DOC (dissolved organic carbon)
name
C, DOC (dissolved organic carbon)
description

0,45µm filtrated,   purging with hydrochloric acid, nondispersive infrared sensor  (NDIR) after combustion

synonyms
dissolved organic material (DOM), non-purgeable organic carbon (NPOC)
N, ammonia-nitrogen
name
N, ammonia-nitrogen
description

0,45µm filtrated, photometric determination

synonyms
NH4+-N, Ammonium, ammonia, NH4-N, NH4
N, nitrate-nitrogen
name
N, nitrate-nitrogen
description

0,45µm filtrated, photometric determination

synonyms
NO3-N, NO3--N, nitrate, Nitrat
O, oxygen
name
O, oxygen
pH
name
pH
description

pH-probe determination
phosphate-phosphorus
name
phosphate-phosphorus
P, (total phosphorus)
name
P, (total phosphorus)
description

photometric determination after digestion

synonyms
total phosphorus, gesamter Phosphor
Si, silicon
name
Si, silicon
description

0,45µm filtrated, inductively coupled plasma optical emission spectrometry (ICP-OES)
Si bis 06/2018 photometrisch

biology:

chlorophyll a
name
chlorophyll a
description

Attention: There are two different methods:

HPLC - High Performance Liquid Chromatography (ex situ)

YSI - Chlorophyll Sensor in Multiparameter probe (in situ)

synonyms
Chlorophyllkonzentration, alpha-chlorophyll
Contact
Ingrid Chorus, Jutta Fastner
Licence for data
All rights reserved. Please send a request to Ingrid Chorus, Jutta Fastner if you like to use this data. Mind our data policy: Lakebase Data Policy

Metadata files

TitleUpload dateFiletypeLicenceActions
Schlachtensee_-_features_and_sampling.pdf09. Jun. 2020 11:59.pdf Download
Methods_for_Analyses_of_Schlachtensee.pdf09. Jun. 2020 11:59.pdf Download

Data files (e.g. excel)

TitlecreatedFiletypeActions
SchlSee_Phyto_QUANT.xlsx 09. Jun. 2020 11:53 datatable: .xlsx
Error: To access file, please get in touch with the contact person.
Schlachtensee_I.xlsx 09. Jun. 2020 11:52 datatable: .xlsx
Error: To access file, please get in touch with the contact person.
Schlachtensee_II.xlsx 09. Jun. 2020 11:52 datatable: .xlsx
Error: To access file, please get in touch with the contact person.
Schlachtensee_III.xlsx 09. Jun. 2020 11:52 datatable: .xlsx
Error: To access file, please get in touch with the contact person.
Krumme_Lanke_IV.xlsx 09. Jun. 2020 11:52 datatable: .xlsx
Error: To access file, please get in touch with the contact person.
Krumme_Lanke_V.xlsx 09. Jun. 2020 11:52 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.

  • Schlachtensee_physico-chemical__and_phytoplankton_data.xml
  • Schlachtensee_physico-chemical__and_phytoplankton_data.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)