Labrisomus xanti
Largemouth blenny
Labrisomus xanti, the Largemouth blenny, is a species of labrisomid blenny native to the Pacific coast of Mexico from Baja California to Jalisco. It inhabits shallow waters.W CalCOFI holds 17 observations of it in 1 dataset between 1959 and 2019, as larva.R
- 17
- observations
- 17
- records
- 17
- sampling events
- 1959–2019
- years
- 1
- datasets
- larva
- life stages
Observed ini
One row per dataset, one cell per year, darker with more observations — the same strip the front
door draws per dataset. Each row ends with the name that dataset uses (dataset_taxon);
the accepted name is written once, in the title above. A quiet pill marks a name the authority does not accept.
i
One row per dataset, one cell per year, darker with more observations — the same strip the front door draws per dataset. Each row ends with the name that dataset uses (dataset_taxon); the accepted name is written once, in the title above. A quiet pill marks a name the authority does not accept.
-
name used: Labrisomus xanti Largemouth blenny · code
834
How big is iti
Every mark is a measured length with its own source — hover one to read it.
The reference objects are _data/size_reference.csv: two of them,
the 505 µm bongo mesh and the net's ring, are CalCOFI's own sampling gear.
i
Every mark is a measured length with its own source — hover one to read it. The reference objects are _data/size_reference.csv: two of them, the 505 µm bongo mesh and the net's ring, are CalCOFI's own sampling gear.
Ways ini
Read from taxa.json of release
v2026.09.11, written at release
by calcofi4db::build_taxa_catalog(). The catalog's index is
/species/.
Explorerdb-queryi
Read from taxa.json of release v2026.09.11, written at release by calcofi4db::build_taxa_catalog(). The catalog's index is /species/.
library(calcofi4r) con <- cc_get_db() # the promoted release tbl(con, "obs_bio") |> filter(taxon_key == "worms:281266")
import calcofi4py as cc
con = cc.cc_get_db()
con.sql("SELECT * FROM obs_bio WHERE taxon_key = 'worms:281266'").df()