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EUROBIS data served via ERDDAP
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Dataset Title: | Cefas09 - Effects of paint-derived tributyltin (TBT) on structure of estuarine nematode assemblages in experimental microcosms ![]() ![]() |
Institution: | CEFAS, MBA (Dataset ID: manuela_c9f) |
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 | aphia_id |
---|---|---|---|---|
Not applicable | None | None | None | Not applicable |
Anoplostoma viviparum | O | 2001.0 | 3.0 | |
Aponema torosa | O | 2001.0 | 3.0 | |
Araeolaimus | O | 2001.0 | 3.0 | 2436.0 |
Ascolaimus elongatus | O | 2001.0 | 3.0 | |
Axonolaimus spinosus | O | 2001.0 | 3.0 | |
Calyptronema maxweberi | O | 2001.0 | 3.0 | |
Camacolaimus | O | 2001.0 | 3.0 | 2392.0 |
Chromadora macrolaima | O | 2001.0 | 3.0 | |
Chromadorita tentabunda | O | 2001.0 | 3.0 | |
Cyartonema germanicum | O | 2001.0 | 3.0 | |
Cyatholaimus gracilis | O | 2001.0 | 3.0 | |
Daptonema hirsutum | O | 2001.0 | 3.0 | |
Daptonema normandicum | O | 2001.0 | 3.0 | |
Daptonema tenuispiculum | O | 2001.0 | 3.0 | |
Desmodora pontica | O | 2001.0 | 3.0 | |
Desmoscolex | O | 2001.0 | 3.0 | 2368.0 |
Dichromadora cephalata | O | 2001.0 | 3.0 | |
Eleutherolaimus stenosoma | O | 2001.0 | 3.0 | |
Euchromadora vulgaris | O | 2001.0 | 3.0 | |
Halalaimus gracilis | O | 2001.0 | 3.0 | |
Hypodontolaimus balticus | O | 2001.0 | 3.0 | |
Leptolaimus elegans | O | 2001.0 | 3.0 | |
Metachromadora remanei | O | 2001.0 | 3.0 | |
Metachromadora scotlandica | O | 2001.0 | 3.0 | |
Metachromadora suecica | O | 2001.0 | 3.0 | |
Metachromadora vivipara | O | 2001.0 | 3.0 | |
Metalinhomoeus filiformis | O | 2001.0 | 3.0 | |
Microlaimus conothelis | O | 2001.0 | 3.0 | |
Microlaimus turgofrons | O | 2001.0 | 3.0 | |
Microlaimus zosterae | O | 2001.0 | 3.0 | |
Molgolaimus demani | O | 2001.0 | 3.0 | |
Monoposthia | O | 2001.0 | 3.0 | 2368.0 |
Neochromadora poecilosoma | O | 2001.0 | 3.0 | |
Odontophora longisetosa | O | 2001.0 | 3.0 | |
Odontophora setosa | O | 2001.0 | 3.0 | |
Odontophora villoti | O | 2001.0 | 3.0 | |
Oxystomina asetosa | O | 2001.0 | 3.0 | |
Pareurystomina | O | 2001.0 | 3.0 | 2562.0 |
Prochromadorella ditlevseni | O | 2001.0 | 3.0 | |
Ptycholaimellus ponticus | O | 2001.0 | 3.0 | |
Richtersia inaequalis | O | 2001.0 | 3.0 | |
Sabatieria ornata | O | 2001.0 | 3.0 | |
Sabatieria pulchra | O | 2001.0 | 3.0 | |
Sabatieria punctata | O | 2001.0 | 3.0 | |
Sphaerolaimus balticus | O | 2001.0 | 3.0 | |
Sphaerolaimus gracilis | O | 2001.0 | 3.0 | |
Sphaerolaimus macrocirculus | O | 2001.0 | 3.0 | |
Spirinia parasitifera | O | 2001.0 | 3.0 | |
Terschellingia communis | O | 2001.0 | 3.0 | |
Terschellingia longicaudata | O | 2001.0 | 3.0 | |
Theristus acer | O | 2001.0 | 3.0 | |
Theristus flevensis | O | 2001.0 | 3.0 | |
Tripyloides gracilis | O | 2001.0 | 3.0 | |
Viscosia abyssorum | O | 2001.0 | 3.0 | |
Viscosia glabra | O | 2001.0 | 3.0 | |
Viscosia viscosa | O | 2001.0 | 3.0 |
In total, there are 56 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.