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EUROBIS data served via ERDDAP
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Dataset Title: | Western Baltic Sea Copepods
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Institution: | DZMB (Dataset ID: manuela_dw) |
Information: | Summary ![]() ![]() ![]() |
To view the map, check View : Map of All Related Data above.
WARNING: This may involve lots of data.
For some datasets, this may be slow.
Consider using this only when you need it and
have selected a small subset of the data.
To view the counts of distinct combinations of the variables listed above,
check View : Distinct Data Counts above and select a value for one of the variables above.
Distinct Data
(Metadata)
(Refine the data subset and/or download the data)
ScientificName | BasisOfRecord | YearCollected | MonthCollected | DayCollected | aphia_id |
---|---|---|---|---|---|
Not applicable | None | None | None | None | Not applicable |
Ameirinae | O | 2002.0 | 10.0 | 29.0 | |
Ameirinae | O | 2002.0 | 10.0 | 31.0 | |
Amphiascoides dispar | O | 2002.0 | 10.0 | 31.0 | |
Amphiascus tenuiremis | O | 2002.0 | 10.0 | 29.0 | |
Bradya (Bradya) scotti | O | 2002.0 | 10.0 | 29.0 | |
Calanoida | O | 2002.0 | 10.0 | 29.0 | 1100.0 |
Calanoida | O | 2002.0 | 10.0 | 30.0 | 1100.0 |
Calanoida | O | 2002.0 | 10.0 | 31.0 | 1100.0 |
Cletodes | O | 2002.0 | 10.0 | 29.0 | |
Cletodes limicola | O | 2002.0 | 10.0 | 29.0 | |
Cletodes longicaudatus | O | 2002.0 | 10.0 | 29.0 | |
Cletodes tenuipes | O | 2002.0 | 10.0 | 29.0 | |
Copepoda | O | 2002.0 | 10.0 | 29.0 | 1080.0 |
Copepoda | O | 2002.0 | 10.0 | 30.0 | 1080.0 |
Copepoda | O | 2002.0 | 10.0 | 31.0 | 1080.0 |
Cyclopoida | O | 2002.0 | 10.0 | 29.0 | 1101.0 |
Cyclopoida | O | 2002.0 | 10.0 | 30.0 | 1101.0 |
Cyclopoida | O | 2002.0 | 10.0 | 31.0 | 1101.0 |
Danielssenia quadriseta | O | 2002.0 | 10.0 | 29.0 | |
Danielssenia quadriseta | O | 2002.0 | 10.0 | 31.0 | |
Danielssenia typica | O | 2002.0 | 10.0 | 29.0 | |
Danielssenia typica | O | 2002.0 | 10.0 | 31.0 | |
Diosaccidae | O | 2002.0 | 10.0 | 29.0 | |
Diosaccidae | O | 2002.0 | 10.0 | 31.0 | |
Ectinosoma | O | 2002.0 | 10.0 | 29.0 | |
Enhydrosoma curticauda | O | 2002.0 | 10.0 | 31.0 | |
Enhydrosoma longifurcatum | O | 2002.0 | 10.0 | 29.0 | |
Enhydrosoma longifurcatum | O | 2002.0 | 10.0 | 30.0 | |
Enhydrosoma longifurcatum | O | 2002.0 | 10.0 | 31.0 | |
Enhydrosoma sarsi | O | 2002.0 | 10.0 | 29.0 | |
Enhydrosoma sarsi | O | 2002.0 | 10.0 | 31.0 | |
Halectinosoma | O | 2002.0 | 10.0 | 29.0 | |
Halectinosoma | O | 2002.0 | 10.0 | 31.0 | |
Haloschizopera junodi | O | 2002.0 | 10.0 | 29.0 | |
Harpacticoida | O | 2002.0 | 10.0 | 29.0 | 1102.0 |
Harpacticoida | O | 2002.0 | 10.0 | 30.0 | 1102.0 |
Harpacticoida | O | 2002.0 | 10.0 | 31.0 | 1102.0 |
Heteropsyllus nanus | O | 2002.0 | 10.0 | 29.0 | |
Laophonte longicaudata | O | 2002.0 | 10.0 | 29.0 | |
Longipedia coronata | O | 2002.0 | 10.0 | 29.0 | |
Longipedia helgolandica | O | 2002.0 | 10.0 | 31.0 | |
Longipedia scotti | O | 2002.0 | 10.0 | 29.0 | |
Mesochra pygmaea | O | 2002.0 | 10.0 | 29.0 | |
Microsetella | O | 2002.0 | 10.0 | 29.0 | |
Normanella | O | 2002.0 | 10.0 | 29.0 | |
Proameira simplex | O | 2002.0 | 10.0 | 29.0 | |
Pseudobradya | O | 2002.0 | 10.0 | 29.0 | |
Pseudobradya | O | 2002.0 | 10.0 | 31.0 | |
Sarsameira parva | O | 2002.0 | 10.0 | 29.0 | |
Stenhelia (Delavalia) longicaudata | O | 2002.0 | 10.0 | 29.0 | |
Stenhelia (Delavalia) reflexa | O | 2002.0 | 10.0 | 29.0 | |
Tachidiella | O | 2002.0 | 10.0 | 29.0 | |
Typhlamphiascus typhlops | O | 2002.0 | 10.0 | 31.0 | |
Zosime | O | 2002.0 | 10.0 | 29.0 |
In total, there are 54 rows of distinct combinations of the variables listed above.
All of the rows are shown above.
To change the maximum number of rows displayed, change View : Distinct Data above.
To view the related data counts,
check View : Related Data Counts above and select a value for one of the variables above.
WARNING: This may involve lots of data.
For some datasets, this may be slow.
Consider using this only when you need it and
have selected a small subset of the data.
Related Data
(Metadata)
(Refine the data subset and/or download the data)
To view the related data, change View : Related Data above.
WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.