Encrasicholina punctifer
Buccaneer anchovy
Encrasicholina punctifer, known as the buccaneer anchovy, or in Hawaiian as nehu, is an anchovy of the family Engraulidae that is widespread in the Indo-Pacific.W CalCOFI holds 38 observations of it in 1 dataset between 2002 and 2002, as larva.R
- 38
- observations
- 38
- records
- 38
- sampling events
- 2002
- 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: Encrasicholina punctifer Buccaneer anchovy · code
1075
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:219982")
import calcofi4py as cc
con = cc.cc_get_db()
con.sql("SELECT * FROM obs_bio WHERE taxon_key = 'worms:219982'").df()