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Dataset Title: | Nematode data from the Firth of Clyde (Scotland)
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Institution: | MBA, NHM (Dataset ID: manuela_nc) |
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 |
Actinonema pachydermatum | O | 1978.0 | 9.0 | |
Adoncholaimus | O | 1978.0 | 9.0 | 2564.0 |
Aegialoalaimus | O | 1978.0 | 9.0 | 2380.0 |
Ammotheristus | O | 1978.0 | 9.0 | |
Antomicron | O | 1978.0 | 9.0 | 2400.0 |
Ascolaimus elongatus | O | 1978.0 | 9.0 | |
Bathylaimus | O | 1978.0 | 9.0 | 2586.0 |
Calomicrolaimus acanthus | O | 1978.0 | 9.0 | |
Calomicrolaimus parahonestus | O | 1978.0 | 9.0 | |
Camacolaimus tardus | O | 1978.0 | 9.0 | |
Campylaimus | O | 1978.0 | 9.0 | 2436.0 |
Chaetonema riemanni | O | 1978.0 | 9.0 | |
Chitwoodia tripapillata | O | 1978.0 | 9.0 | |
Chitwoodia warwicki | O | 1978.0 | 9.0 | |
Chromadoridae | O | 1978.0 | 9.0 | 2162.0 |
Chromaspirina inglisi | O | 1978.0 | 9.0 | |
Cobbia | O | 1978.0 | 9.0 | 2454.0 |
Coninckia | O | 1978.0 | 9.0 | 2436.0 |
Cyartonema elegans | O | 1978.0 | 9.0 | |
Cyartonema germanicum | O | 1978.0 | 9.0 | |
Cyartonema zosterae | O | 1978.0 | 9.0 | |
Cyatholaimidae | O | 1978.0 | 9.0 | 2164.0 |
Daptonema | O | 1978.0 | 9.0 | 2456.0 |
Daptonema curvatus | O | 1978.0 | 9.0 | |
Daptonema invagiferoum | O | 1978.0 | 9.0 | |
Daptonema normandicus | O | 1978.0 | 9.0 | |
Dasynemella | O | 1978.0 | 9.0 | 2386.0 |
Desmolaimus zeelandicus | O | 1978.0 | 9.0 | |
Dichromadora | O | 1978.0 | 9.0 | 2296.0 |
Dichromadora cucullata | O | 1978.0 | 9.0 | |
Dichromadora hyalocheile | O | 1978.0 | 9.0 | |
Diplopeltula | O | 1978.0 | 9.0 | 2440.0 |
Eleutherolaimus | O | 1978.0 | 9.0 | 2480.0 |
Enoploides | O | 1978.0 | 9.0 | 2512.0 |
Enoploides spiculohamatus | O | 1978.0 | 9.0 | |
Enoplolaimus propinquus | O | 1978.0 | 9.0 | |
Eubostrichus | O | 1978.0 | 9.0 | 2352.0 |
Gammanema | O | 1978.0 | 9.0 | 2332.0 |
Gonionchus longicaudatus | O | 1978.0 | 9.0 | |
Halalaimus capitulatus | O | 1978.0 | 9.0 | |
Leptolaimus ampullaceus | O | 1978.0 | 9.0 | |
Leptolaimus scotlandicus | O | 1978.0 | 9.0 | |
Leptonemella aphanothecae | O | 1978.0 | 9.0 | |
Metachromadora scotlandica | O | 1978.0 | 9.0 | |
Metachromadora suecica | O | 1978.0 | 9.0 | |
Metachromadora vivipara | O | 1978.0 | 9.0 | |
Metadesmolaimus | O | 1978.0 | 9.0 | 2460.0 |
Metadesmolaimus aduncus | O | 1978.0 | 9.0 | |
Metadesmolaimus pandus | O | 1978.0 | 9.0 | |
Microlaimus | O | 1978.0 | 9.0 | 2366.0 |
Microlaimus acinaces | O | 1978.0 | 9.0 | |
Microlaimus macrocirculus | O | 1978.0 | 9.0 | |
Microlaimus monstrosus | O | 1978.0 | 9.0 | |
Microlaimus ostracion | O | 1978.0 | 9.0 | |
Monhystera venusta | O | 1978.0 | 9.0 | |
Monoposthia mirabilis | O | 1978.0 | 9.0 | |
Nannolaimoides | O | 1978.0 | 9.0 | 2316.0 |
Nannolaimus fusus | O | 1978.0 | 9.0 | |
Neochromadora | O | 1978.0 | 9.0 | 2300.0 |
Neochromadora paratecta | O | 1978.0 | 9.0 | |
Neochromadora tecta | O | 1978.0 | 9.0 | |
Neochromadora trichophora | O | 1978.0 | 9.0 | |
Neotonchus boucheri | O | 1978.0 | 9.0 | |
Odontophora exharena | O | 1978.0 | 9.0 | |
Odontophora rectangula | O | 1978.0 | 9.0 | |
Odontophoroides paramonhystera | O | 1978.0 | 9.0 | |
Oxystomina elongata | O | 1978.0 | 9.0 | |
Paracanthonchus thaumasius | O | 1978.0 | 9.0 | |
Paracyatholaimus occultus | O | 1978.0 | 9.0 | |
Paracyatholaimus pentodon | O | 1978.0 | 9.0 | |
Polysigma fuscum | O | 1978.0 | 9.0 | |
Pomponema debile | O | 1978.0 | 9.0 | |
Pomponema sedecima | O | 1978.0 | 9.0 | |
Pomponema tesselatum | O | 1978.0 | 9.0 | |
Prochromadorella ditlevseni | O | 1978.0 | 9.0 | |
Pselionema | O | 1978.0 | 9.0 | 2388.0 |
Pseudonchus | O | 1978.0 | 9.0 | 2344.0 |
Rhabdocoma riemanni | O | 1978.0 | 9.0 | |
Rhabdodemania imer | O | 1978.0 | 9.0 | |
Rhynchonema | O | 1978.0 | 9.0 | 2464.0 |
Richtersia inaequalis | O | 1978.0 | 9.0 | |
Sabatieria longiseta | O | 1978.0 | 9.0 | |
Sabatieria longispinosa | O | 1978.0 | 9.0 | |
Sigmophoranema litorale | O | 1978.0 | 9.0 | |
Siphonolaimus ewensis | O | 1978.0 | 9.0 | |
Spiliphera hirsuta | O | 1978.0 | 9.0 | |
Spilophorella | O | 1978.0 | 9.0 | 2302.0 |
Spilophorella candida | O | 1978.0 | 9.0 | |
Spirinia laevis | O | 1978.0 | 9.0 | |
Stephanolaimus | O | 1978.0 | 9.0 | 2408.0 |
Stephanolaimus elegans | O | 1978.0 | 9.0 | |
Tarvaia angusta | O | 1978.0 | 9.0 | |
Terschellingia | O | 1978.0 | 9.0 | 2480.0 |
Terschellingia communis | O | 1978.0 | 9.0 | |
Thalassoalaimus | O | 1978.0 | 9.0 | 2552.0 |
Theristus | O | 1978.0 | 9.0 | 2468.0 |
Theristus bastiani | O | 1978.0 | 9.0 | |
Theristus flevensis | O | 1978.0 | 9.0 | |
Theristus interstitialis | O | 1978.0 | 9.0 | |
Theristus pertenuis | O | 1978.0 | 9.0 | |
Trefusia | O | 1978.0 | 9.0 | 2592.0 |
Trichotheristus mirabilis | O | 1978.0 | 9.0 | |
Trileptium parisetum | O | 1978.0 | 9.0 | |
Viscosia | O | 1978.0 | 9.0 | 2570.0 |
Viscosia cobbi | O | 1978.0 | 9.0 | |
Xyala riemanni | O | 1978.0 | 9.0 |
In total, there are 106 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.