taxify_regions()’s two search examples
("belgium", "Europe") are wrapped in
\donttest{}, after R CMD check --as-cran
flagged the file at 6.4s elapsed against the 5s per-example limit; the
coordinate-lookup example ahead of them still runs unwrapped.
enrich_by_group()’s homonym-collision warning (used
by add_wcvp() and every other grouped door) now
distinguishes two reasons a name’s rows were left NA (#87).
“match more than one concept” stays for a genuine tie – at least one
candidate is a plausible near-miss or shares the query’s basionym
author, but more than one does. A new “none share any authorship”
warning covers the case where no candidate shares anything with the
queried authorship at all: not a tie to break, but a sign the matched
concept may not be recognised by the enrichment under any spelling (WCVP
sinking an infraspecific WFO concept into its species, for instance),
which previously read as a near-miss the matcher gave up on.
Breaking: add_alien_first_records() joins on the
source’s own locations and takes location = in place of
country =. FirstRecords records islands and other parts of
a country as regions of their own (“282 non-overlapping regions
(countries and sub-national regions such as islands)”, Seebens et
al. 2017), so its United States of America excludes Hawaii and Alaska
and its Spain excludes the Canary and Balearic Islands. The enrichment
used to credit each of those to its country and keep the earliest year,
which in v4.0 dated 665 of the source’s species x country first records
from an island’s earlier year (337 of them from Hawaii, by a median of
25 years) and gave 3,541 country records to species the source records
only on an island. A country is still keyed on its ISO 3166-1 alpha-2
code (location = "AT"); a sub-national location is keyed on
its name (location = "Hawaii"), listed by
enrichment_groups("alien_first_records"). Every row carries
country_code for an explicit roll-up to countries.
dispersal_syndrome reads BROT 2.0
(gcol33/taxifydb#57). BROT writes dispersal mode as vector letters, most
important first, and no pattern matched a letter, so BROT supplied
nothing; the slot now maps the first letter through the legend of the
BROT 2.0 data paper (Tavsanoglu & Pausas 2018). G (“autochory, by
Gravity (=unassisted dispersal)”) reads as gravity, the
class Baseflor, AusTraits and LEDA fill from barochory.
dispersal_syndrome leaves a term that names no
mechanism unplaced, so a source that does name one fills the species.
Autochory is the self-dispersal umbrella in LEDA and AusTraits, not
ballistic; LEDA’s blastochor was read as gravity, herpochor (a diaspore
crawling on hygroscopic awns) as ballistic, and bythisochor
(non-floating seeds carried along the bottom of running water) as
gravity; AusTraits’ undefined (“Dispersal mechanism
unknown”) was read as unspecialized. All are now NA; a
co-listed vector still wins (autochory, myrmecochory is
ant). GIFT’s unspecialized keeps its class.
Each source note carries the definitions and the shared-species
calibration.
LEDA is read as taxifydb’s corrected reader builds it
(gcol33/taxifydb#57). leda_seed_mass_mg calibrates at 1.00
against Kew SID, GIFT and BIEN and now feeds seed_mass;
ssd_g_cm3 is g/cm3 as built, so wood_density
no longer divides it by 1000 and carries a caution (most records are
air-dry densities, 1.14x GWDD on 37 shared species).
add_leda() attaches clonal_growth_organ and
floating_capacity_1week_pct in place of the empty
clonal_growth and buoyancy.
add_bien() and add_ecoflora() document
the unit of every curated numeric column. The rebuilt assets write BIEN
leaf dry mass in mg (BIEN records g) and Ecoflora typical maximum and
minimum height in mm (Ecoflora records cm).
taxify requires vectra (>= 0.12.4), which ties each
.vtri index to the store it was built for and drops stale
indexes when a .vtr is rewritten.
Five fixes in the core matching path, all of them cases where a result depended on something other than the name being matched: how often it was submitted, which backbone happened to answer a neighbouring name, or which build was loaded earlier in the session.
Several queries may now resolve to the same backbone row (#56).
Fuzzy matching kept only the closest query per target and returned
match_type = "none" for the rest, to stop two different
species collapsing onto one row. But two inputs sharing a target is the
normal shape of a dirty checklist: a repeated misspelling, or two
spellings of one name. The rejected input came back as if the backbone
held nothing near it, and which input was rejected depended on how the
batch was ordered. Every query within threshold now matches its best
target and carries its own fuzzy_dist.
The loaded backbone and its compact fuzzy copy are keyed on the
build, not on the file’s basename (#57). Both were memoized under
.blk_<basename>, so a
taxify_restore(install = TRUE), a mid-session update and a
data-dir switch – all of which swap builds under one basename – left the
rest of the session matching against the replaced build while the
metadata reported the new one. clear_backbone_memo() now
owns that state and runs wherever a backbone path is invalidated, so the
loaded copy cannot outlive the path that resolved it.
The authorship tiebreak writes accepted_authorship
(#58). Resolving a homonym by the author the query carried rewrote
accepted_name but left the author of the candidate it had
just rejected, so name and author named two different taxa.
Abbreviated-genus resolution reads the genus context off the
whole query (#59). "Q. petraea" is disambiguated by a genus
written out in full elsewhere in the batch, but each backbone in a
fallback chain sees only the names still unmatched – so a genus an
earlier backbone had already answered was invisible to the later ones,
and mode = "fallback" disagreed with
mode = "agreement" on the same query.
Three smaller inconsistencies in the core path (#60).
clean_one(), an unreachable and drifted copy of
clean_names(), is deleted and names_df is now
required, so clean_names() is the single cleaner. An
NA input gets match_type = "none" like
"", which is what the documented vocabulary says
(match_type is never NA). And
summary() prints each backbone’s own version next to it,
rather than labelling a whole chain with the first matched row’s
build.
Five fixes in the side paths around matching: joining custom data, pinning and locking a build, the less common enrichment joins, and empty input.
add_data() joins on the accepted taxon, not a bare
accepted_id (#61). Backend ids are integers in most
backbones and carry no namespace, so a name matched by ITIS could join
onto an unrelated taxon GBIF happened to number the same, with no
warning. The id is now qualified by the backbone that issued it, and
rows matched by different backbones on the two sides join through
accepted_name, which is what the synonym promise in the
documentation needs.
A pinned version downloads that version (#62).
taxify_download(version = ) and
taxify_download_enrichment(version = ) fetched the current
release and labelled it with the requested version, marked pinned, so
the next session never corrected it. The URL is now derived from the
release tag (<name>-<version>/<name>.vtr,
enrichment-<version>/<name>.vtr), and a version
that was never published is an error.
taxify_lock() pins the builds a result was produced
from (#63). Version and content id are recorded when an enrichment is
joined, not read from whatever is installed when the lock is written, so
a refresh or restore in between no longer changes the pin. Sources that
contributed no value are left out, as cite() already did,
and add_trait() sources carry their version instead of
NA. taxify_restore() reports a row as
"unverified" when the lock holds a content id and the
install has none, rather than "ok" on matching version
labels.
Four enrichment join paths now follow the main one (#64). A
mixed-grain source (genus_fallback) fills from the genus
row only after cross-backbone recovery has looked for the species, so
species resolution wins. groups = "all" reads the groups of
the installed build before the manifest, so a pinned or restored build
no longer gets columns for groups it lacks. Grouped
add_data() errors on conflicting values within a group,
like the flat join, and uses the shared group fill. The emergency
grouped path keeps the NA group, so
add_common_names(lang = NA) returns names there
too.
Empty input returns an empty result (#65).
comm2sci(output = "result") with no match, and
add_trait() or any add_*() door on a zero-row
result, errored or warned once per source. They now return the full
output schema at zero rows, built by one constructor.
Five fixes in the verbs around taxify(): browsing the
backbone, inspecting a list, and the lookups between names, ids and
common names.
No more indistinguishable duplicate rows (#66).
comm2sci(output = "result") returned one identical row per
language a vernacular was stored in, because it deduplicated on a key
that included lang and then dropped lang; it
now has one row per (query, scientific name). synonyms()
repeated every synonym once per copy of a repeated input name; each
distinct name is now reported once.
inspect() no longer flags valid names or input
(#67). The register check read the genus as the raw, case-sensitive
first word, so "quercus robur" and
"cf. Quercus robur" came back unknown /
unresolved; the genus is now taken from the cleaned name
and looked up case-insensitively, as taxify() does. A
mistyped region code ("GRE" for Greece, which is
GRC) was kept as a region, and inspect() then
flagged every plant with WCVP data as geographic.
region = now drops a code the WGSRPD crosswalk does not
list, with a warning, as it already did for an unrecognised name;
inspect() reports the geographic check under
not checked. region and coords
are no longer resolved when nothing reads them (a character vector
inspected without matching), which could download the region
boundaries.
Four input shapes in the secondary verbs (#68).
lookup_genus(NA) returned every register row filled with
NA; it returns NULL. id2name()
matched a numeric id through as.character(), which writes
1e+05, so a round GBIF key or TSN read from a CSV found
nothing; numeric ids are now written out in full, and a fractional one
is an error. class2tree()’s $phylo tip labels
read Quercus_robur where $tip_labels read
Quercus robur; the phylo now carries the
names, and only the Newick string uses _.
taxify_long() stopped with “No suffixed columns found” on
single-group input that carried a companion column such as
<trait>_sources, and matched base names as regular
expressions in one of its two checks; one literal predicate now decides
both.
children() and downstream() are one
query (#69). children() is downstream() with
the parent restricted to a genus or family, so the two no longer
disagree: under rank = "any" / downto = "any"
neither returns the parent itself. Both take kingdom =, as
taxify() does, for a name used in more than one kingdom: on
COL or GBIF, children("Morus") returned mulberries and
gannets together, and downstream() chose the parent’s rank
by a vote across the homonyms. Without kingdom, a result
that mixes kingdoms now warns. Both return the same columns, adding
kingdom_group, and children() gains
parent.
The sibling verbs forward matching arguments the same way (#70).
synonyms(), upstream(),
sci2comm(), comm2sci(),
reconcile(), lowest_common() and
class2tree() pass named arguments in ... on to
taxify(), so fuzzy = FALSE,
fuzzy_threshold, kingdom or
region reach the matcher from each of them;
synonyms(), upstream() and
sci2comm() no longer set fuzzy = TRUE
regardless. resolve = now means one thing: run the input
through taxify() first, as in sci2comm().
comm2sci()’s argument, which instead changed the return
type, is renamed output = c("lookup", "result").
The eight genus-keyed doors reach every genus their source covers
(#77). add_blanchard(), add_cefas_btrait(),
add_disperse(),
add_freshwater_insects_conus(),
add_fungal_traits(), add_fungalroot(),
add_noddb() and add_ramond() read assets
rebuilt by taxifydb 0.1.23. Their cross-backbone name expansion had
keyed rows under subgenus renderings and species, which no genus can
match, and had pulled in genus homonyms from the other nomenclature
code. For fungalroot, fungal_traits and noddb the expanded names also
never reached the genus column the door joins on.
list_enrichments() reports every column an
enrichment attaches (#76). The manifest’s trait_cols had
fallen behind 40 of the assets, missing the _min /
_max / _n spread columns, FishBase’s and
SeaLifeBase’s lw_* length-weight columns,
bet‘s substrate and
arthropod_traits’ taxon_order. They are now
taken from each asset’s schema, and the manifest sync keeps them that
way.
normalize_kingdom_group() and
backbone_fixed_kingdom() are exported as low-level building
blocks, for taxifydb’s kingdom check on enrichment name
expansion.
GIFT is no longer a suggested package. add_gift()
has read the bundled .vtr since GIFT was built into an
enrichment, and the enrichments vignette no longer describes the earlier
on-demand API route.
A backbone upgrade patches through xdelta3 when the data
directory contains a space (#79). download_backbone()
passed the store paths to xdelta3 unquoted, so a path like
C:\Users\First Last\... split into several arguments,
xdelta3 exited with “too many filenames”, and every upgrade fell back to
a full download (about 2 GB for col). The paths are now
quoted, the patch is fetched through the same route as the full asset
(so a file:// manifest can serve it), and a failed patch
names its reason when verbose.
install_backbones() refreshes an installed backbone
the manifest has moved past (#82). It resolved each name through
ensure_backbone(), which returns whatever .vtr
is on disk, so an installed backbone was never compared and only a later
taxify() call fetched the new release. It now runs the same
comparison as the once-per-session check in taxify() (one
shared refresh_backbone()), downloads where the installed
build is behind, leaves a current one alone, and keeps a build pinned by
taxify_restore() with a message saying so.
A backbone patch is applied only to the build it was cut against
(#83). download_backbone() tried the xdelta3 patch against
any local .vtr, and against a different build xdelta3
stopped with “target window checksum mismatch”, printed its own stderr
and fell back to a full download that verbose = FALSE did
not report. The manifest now records the base build’s content id as
delta_from_content_id (written by taxifydb), and the patch
is fetched only when the local build carries it; a delta recorded
without one is not applied. xdelta3’s output is captured into the
reason. Whichever path ran, the new file is checked against the manifest
content_id before it replaces the installed build: a
patched file that does not match is replaced by the full asset, and a
full download that does not match stops with an error and leaves the
previous build in place. meta.json records
install_path ("patched" or
"full"), and the ready message naming the path and any
reason the patch was not used is shown regardless of
verbose.
Installing a backbone or enrichment no longer leaves the replaced
file’s vectra indexes beside the new one. A download renamed the new
.vtr into place and kept
<name>.vtr.<column>.vtri, and vectra accepts an
index whose row and row-group counts match the store, whatever its
content (gcol33/vectra#13): a re-cut of the same shape would have pruned
by the old keys and dropped exact matches without an error. Every
install path (backbone and enrichment downloads, sidecar extras, builds
fetched by content id) removes the indexes of the file it replaces, and
activating a stored build drops any index the archived build left in the
slot. The published assets carry no index, so an installed asset now has
the same files on every machine.
taxify_pin() pins or releases installed backbones
and enrichments by name. A pin was reachable only by fetching a build by
content id, so a project building against a shared data directory had no
call that held the builds it had already installed, and set
"pinned": true in meta.json by hand. The pin
is still that meta.json flag, now written together with the
build’s content id and reported back; the version checks in
taxify(), install_backbones() and the
enrichment doors leave a pinned build in place. It refuses a name that
is not installed, and a name installed as both a backbone and an
enrichment (wcvp) until kind = says
which.
taxify_restore(install = TRUE) pins every build that
matches the lock, including one that already matched and needed no
download. It pinned only the builds it fetched, so a lock that matched
the install reported success and left those builds free to be refreshed
away at the next session. The report gains a pinned
column.
A name the backbone holds without placing it no longer reads as
accepted (#81). The result carries the matched record’s own status in a
new taxonomic_status column (WFO’s
"UNCHECKED", COL’s "PROVISIONALLY ACCEPTED",
…). Where such a record’s basionym is placed, the name resolves to the
taxon the basionym is placed under, with
match_type = "basionym" and is_synonym = TRUE:
against WFO 2024-12, Sabulina tenuifolia now resolves to
Minuartia hybrida. This reads the backbone’s basionym link
(original_name_usage_id), which WFO and COL builds carry
once rebuilt; a build without it is matched as before. And where one
record of a name is a synonym homotypic with its accepted name and
another is unplaced, the homotypic record is picked and the unplaced
homonym stays in ambiguous_targets: Lycopsis
orientalis resolves to Anchusa arvensis subsp.
orientalis rather than to the unplaced Lycopsis
orientalis Steph.
An audit for the #55 shape – a failure returned as a plausible
answer, with the only notice gated on verbose – found it in
three more places. The cause behind #55 itself, a cache key handed to an
environment, exists nowhere else: every other session cache is keyed on
a backbone name or a file basename.
region = and coords = now warn when the
constraint could not be applied. With no range data for the declared
region, region_range_sets() returned NULL and
the fuzzy filter passed its candidates through unconstrained, so a match
the region would have excluded could win. This is the one that could
change which taxon a name resolved to, and the only notice was a message
gated on verbose.
inspect() names the checks it could not run, in the
report header under not checked. An anomaly-only report has
no other way to separate a check that ran clean from one that never ran:
both contribute no rows, and the report then prints “nothing stood out”.
The genus-recognition check without the register, and both range checks
without the WCVP range data, were skipped that way. The skipped set
travels on the result, so a saved report carries it.
Cross-backbone name recovery names a backbone it could not resolve against, instead of silently contributing no alternatives for it. That pass runs over the whole gap set at once, which is where a size-dependent failure like #55 would next hide.
add_trait() no longer returns NA for
every source past a batch size (#55). The per-name-set memos behind
hybrid-parent resolution and cross-backbone name recovery were keyed on
the query set itself, and R caps the name of a variable in an
environment at 10000 bytes – so a large enough batch pushed the key past
the cap, where reading the cache raised rather than missed and took the
whole join down with it. Because the cap is on total bytes, the batch
size that tripped it moved with how many names the backbone resolved and
how long they were, which is why a large call could come back with one
source populated and the rest empty and read as a coverage result. Both
memos now use a session store that carries keys of any length.
A trait source that cannot be joined is named in a warning
whether or not verbose = TRUE. Such a source leaves an
all-NA column, which reads exactly like the source genuinely holding
nothing for those taxa, so silence there turns a failure into a coverage
statement.
add_trait(verbose = TRUE) reports what each source
supplied against the number of names the backbone resolved
(gift 152, austraits 40, leda 281, baseflor 336, brot 0 (of 2400 resolved names)),
which separates thin coverage from a source that returned
nothing.
A content id recorded by taxify_lock() now resolves
back to bytes (#54). taxify_download_enrichment() and
taxify_download() take a content_id=, fetch
that exact build from the immutable copy published beside the rolling
asset – reading the manifest’s content_url, or deriving
<tag>/<name>-<content_id>.vtr when the
manifest describes a later build – verify the bytes hash back to the id
asked for, and make it the active build. A build the release has since
re-cut is reachable again; one overwritten before taxifydb began
publishing immutable copies is not, and says so.
taxify_restore(file, install = TRUE) puts a whole
lockfile back in one call, fetching the pinned build of every asset that
drifted. A restored build is pinned, so the next session’s version check
does not refresh it away.
Enrichments now keep the build a refresh replaces, under a
directory named for its content id, instead of overwriting the only copy
on disk. A re-cut under an unchanged tag no longer destroys what a
lockfile pinned. Backbones use the same store but discard the superseded
build by default, being gigabytes;
taxify.keep_enrichment_versions and
taxify.keep_backbone_versions set either policy. Restoring
a pinned build archives the build it displaces either way, so a restore
is reversible.
New taxify_store() lists the builds on disk – which
are active, which are pinned, and which content ids a lockfile could be
restored to without a download.
taxify() no longer resolves a homonym to a synonym
of a different species without saying so. Two things drove it (#53). The
status score read only ACCEPTED, so WFO’s
UNCHECKED – the status it gives a name it keeps as its own
concept but has not reviewed – scored level with a synonym, and
Prunus dulcis came back as Prunus avium; status is
now an ordered vocabulary (accepted, then unreviewed or provisional,
then synonym, then misapplied) that also places COL’s
PROVISIONALLY ACCEPTED, AMBIGUOUS SYNONYM and
MISAPPLIED, and falls through to the backbone’s own
is_synonym flag for a spelling it does not list. And the
nomenclaturalStatus = "Valid" tiebreak was settling the
ambiguity tier, so Rubus laciniatus returned Rubus
ulmifolius with is_ambiguous = FALSE; validity now
orders which candidate the scalar columns hold but no longer clears the
flag, because a valid name and an illegitimate one carrying the same
string can be synonyms of different species. Both names now answer as
they should, and taxify_candidates() expands the
conflict.
An authorship carried by the query now settles a homonym whether
or not the row was flagged ambiguous: an author the caller typed is a
choice of record, and a name unique in the backbone re-reads to what it
already had. The comparison also moved from substring containment to
author tokens, so L. no longer reads into
Lindl..
New candidate_order() gives the candidate sort a
single source of truth, shared with taxifydb’s name-lookup
build.
Enrichment joins now recover an infraspecific name across GBIF’s
dropped rank marker. GBIF’s backbone renders an infraspecific accepted
name without its rank connecting term – Erica tenella var.
tenella comes out Erica tenella tenella – where
every other backbone and every botanical source keeps the marker, so a
join keyed on the rendered name missed in either direction.
taxifydb reinstates the marker at build time
(gcol33/taxifydb#45), but a user still on an older
gbif.vtr holds the marker-less form, so the runtime now
retries the rows a direct (and cross-backbone) join left empty under the
name’s alternative rank-marker renderings – the bare trinomial and each
canonical marker – and matches when the marker is the sole difference. A
rank-insensitive comparison can collide distinct taxa (Aus bus
var. cus and Aus bus subsp. cus are different
names), so a row whose alternatives reach more than one accepted name in
the source is left NA rather than resolved to a guess.
Zoological trinomials (Panthera leo persica) are correctly
marker-less and match directly, so they never reach the fallback. Only
still-empty rows pay for the pass; disable it with
options(taxify.infra_marker_recovery = FALSE)
(gcol33/taxifydb#45).
Enrichment joins now recover a name the source covers under a
different backbone’s accepted name. An enrichment .vtr is
keyed on its source’s own accepted names, expanded at build time onto
every backbone’s treatment of the same concept, and where that expansion
missed one the join found nothing along the same code path, and with the
same empty output, as a name the source genuinely does not cover.
Minuartia hybrida was the reported case: WFO keeps the name,
WCVP, COL and Euro+Med have all moved it to Sabulina, and
add_wcvp() returned no range at all when matched through
WFO. Sampling names from an enrichment’s own .vtr puts the
gap at 4.5% to 22.5% of names depending on the enrichment. Names left
empty by the direct join are now re-resolved through the other installed
backbones, exact matching only, and the join retried under their
accepted names, so the WFO route returns the 49 regions the WCVP route
does. Where backbones disagree about where a moved name went (COL puts
it at Sabulina tenuifolia subsp. hybrida, WCVP at
subsp. tenuifolia, and WCVP gives the two different ranges) the
pick follows backbone priority rather than a vote, the way
accepted_name itself is picked, except that a source taxify
also carries as a backbone goes first. Recovery reports once per call,
never once per name, since a name absent from a source is the normal
case for any query set wider than the source’s scope;
summary() and the taxify_meta attribute
(n_recovered) carry the count. Only unmatched rows pay for
the pass and backbones scoped to a kingdom none of them belong to are
skipped; disable it with
options(taxify.cross_backbone_recovery = FALSE)
(#52).
A rebuilt enrichment asset republished under the release tag it
already carries now refreshes the local cache.
check_enrichment_version() reconciled content ids only for
a static enrichment; a versioned one compared its recorded version
against the manifest’s latest, and a same-tag republish leaves that
label untouched while the bytes change underneath it. GRIIS 2026.08 was
rebuilt after its GBIF-backed source stopped returning
recordid and republished under the tag it already held, so
the pre-rebuild .vtr stayed in place indefinitely and
add_griis(cols = "recordid") went on resolving a column the
source no longer carries instead of raising the unknown-column error.
Content identity now decides and the version string is the fallback, the
order the backbone gate already used; a cache predating content ids is
still left to the label rather than rehashed every session.
The bundled manifest points at the rebuilt
enrichment-2026.08 assets and the republished
gbif-2026.08 backbone. Every enrichment asset was rebuilt
with the build-side reverse hop behind the recovery pass above and
carries a resolved_backbones field naming the backbones it
was expanded against; downloads grow with the wider key sets, 1.96x over
the assets with a shipped counterpart (wcvp 69 to 141 MB,
gift 20 to 40 MB). avonet and
glonaf each drop a trait_cols entry naming a
column their .vtr never carried, and griis
drops recordid, which its upstream source stopped returning
(gcol33/taxifydb#44).
(L.) Hill where WCVP, COL and
Euro+Med all say (L.) Hull, so one of the commonest plants
in Europe came back with no add_wcvp() range at all when
matched through WFO. Authorship is now compared on a normalised key
(case, punctuation, et vs &), then as a
spelling variant of the same author (one edit apart, or an abbreviation
of the same surname), then on a shared basionym author – sources also
credit different people with the same recombination (Glaucium
corniculatum is (L.) Curtis in WFO,
(L.) Rudolph in WCVP), and epithet plus basionym author
pins the same type whoever made the combination. A name that no pass
resolves to exactly one concept is still left NA with a
warning, and a genuine homonym pair with no basionym author – 0.4.6’s
Erigeron pulchellus Michx. vs Hoppe & Hornsch. – is
untouched by the two new passes (#51).Grouped enrichment joins (enrich_by_group(), behind
add_wcvp(), add_griis() and others) now
resolve name-level homonyms instead of guessing. The join key is a bare
accepted-name string, so a name covering two distinct concepts in the
source – told apart only by authorship – collapsed onto whichever row
happened to survive the per-group dedup, regardless of which concept
taxify() had actually matched: add_wcvp()
reported Erigeron pulchellus Michx. (eastern North America) as
native in Germany, when the matched concept was Erigeron
pulchellus Hoppe & Hornsch. ex Bluff & Fingerh., a European
native. When the enrichment carries an authorship-like column, a name
whose rows disagree on authorship is now resolved against
accepted_authorship: the uniquely picked concept’s rows are
kept, or, when the ambiguity can’t be resolved, every row for that name
is dropped (left NA rather than guessed) and a single
warning reports the count.
kingdom = now trusts a single-kingdom backbone’s own
scope ahead of the genus register. WCVP, LCVP, WFO, Euro+Med and Species
Fungorum carry no kingdom column of their own, so a query
against one of them fell straight to the genus register – a single
cross-backbone genus index – which can record a different kingdom for
the same genus string as used elsewhere (the botanical and zoological
codes are independent, so genus homonyms across kingdoms are not rare).
taxify(x, backbone = "wcvp", kingdom = "plants") could
report kingdom_group "animalia" for a
genuinely plant-only match. A new fixed_kingdom registry
field pins the backbones whose scope is genuinely unambiguous, and is
now consulted ahead of both the backbone’s own kingdom column and the
register fallback. AlgaeBase and SeaLifeBase are deliberately left
unfixed, since each spans more than one kingdom.
fuzzy_threshold now accepts the integer
raw-edit-count mode its own documentation describes. Any value greater
than 1 was rejected outright, because vectra::fuzzy_join()
itself only accepts a normalized distance in (0, 1] – the mode was
documented but never implemented end to end. A whole number
>= 1 now runs the join at the loosest normalized bound
and reconstructs the raw edit count from the reported
fuzzy_dist (exactly
raw_edits / max(len_a, len_b)) to filter matches.
alien_first_records is rebuilt from Seebens et al.’s
restructured Darwin Core-style release (record 18759840, source version
4.0), 93,350 rows over 245 countries against 82,684 over 233 before.
Every column was renamed upstream, so trait_cols is
rewritten rather than preserved; a new
alien_first_record_status column carries the occurrence
status of the record each row’s year was taken from.
glonaf is rebuilt after a wrong join key left it
holding 10,238 rows over 84 regions, some names paired with other taxa’s
families. Rebuilt from GloNAF v2.02 (Zenodo record 17105725) at 300,094
rows over all 1,343 regions.
thermofresh’s citation now points at the
peer-reviewed release (record 16959762, ThermoFresh v1.0) rather than
the pre-review deposit the build had been reading since taxifydb bumped
the source.
A backbone whose content is unchanged is no longer re-downloaded
when its version string moves. check_version() compared the
version label first and only consulted the content id when the labels
matched, so it could not see that a bumped version carried bytes already
on disk. Content decides now, and the label is the fallback for a cache
or manifest entry carrying no id. This matters because a build stamps
date +%Y.%m: a backbone reading a pinned source (Euro+Med
from a frozen snapshot, WFO from a fixed Zenodo record) rebuilds to
identical bytes under a new version, which used to cost every user a
full refetch – 740 MB for WFO. A genuine change is still caught by the
same comparison, as is a same-tag republish that leaves the label
alone.
The multi-backbone fallback chain is staged by match quality.
Every backbone is asked for an exact match before any backbone is asked
for a fuzzy one, so a name absent from an early backbone but present in
a later one now resolves to the later backbone’s exact record.
Previously the chain stopped at the first backbone returning any match
at all, and a near neighbour in an early backbone settled the name:
taxify("Acilius sulcatus", backbone = c("col", "gbif"))
returned the weevil Acalles sulcatus from COL, where GBIF
holds the diving beetle under the queried name itself. Backbone priority
still decides between two matches of the same quality. Over 481 names
spanning eighteen backbones, 15 results change, every one of them a
fuzzy match in COL becoming an exact match elsewhere, and three of those
land in a different family. Runs that name a single backbone are
unaffected. mode = "wide" and
mode = "agreement" stage their base
accepted_name the same way, so it keeps agreeing with
mode = "fallback"; their per-backbone columns report each
backbone’s own treatment as before.
The covered-genus union behind the out-of-scope filter is cached per coverage file and backbone set. It was rebuilt on every matching stage, over roughly half a million genera, which made it the largest single cost of a multi-name run. The same 481 names now take 79 seconds where they took 114.
Five sources open, each reaching something the bundled set did
not. add_hydraulics() brings the drought-mortality axis for
2,024 seed plants (Sanchez-Martinez et al. 2020).
add_noddb() brings root-nodule nitrogen fixation for 824
plant genera, joined on genus, which makes it the counterpart to
add_fungalroot()’s mycorrhizal type: together they are the
belowground symbiosis pair. add_faprotax() brings 92
metabolic and ecological function groups over 4,470 prokaryotic taxa.
add_virion() brings host-virus association breadth for
4,223 vertebrates, and add_sworm() the ecological group of
171 earthworms, a taxon with no coverage before.
p50 gains a third source and, with it, its first
empirical confirmation. AusTraits and BROT share no species, so the
trait rested on their two medians landing together at -3.4 MPa. The
Sanchez-Martinez compilation overlaps both and agrees with each at ratio
1.00, while taking coverage from 123 species to
894. The registry records that this is not corroboration: all three are literature compilations over the same primary studies, and 63% of the values shared with AusTraits are identical to the last digit. It is registered because the duplication is confined to 74 of its 894 species, where the sources rejected on these grounds duplicated nearly everything they carried.
The same overlap measures a unit rather than assuming one. 79 of the 208 species the compilation shares with AusTraits match exactly once multiplied by 1e-4, which establishes that its Huber values are square centimetres of sapwood per square metre of leaf.
New traits: leaf_specific_conductivity,
min_water_potential, hydraulic_safety_margin,
nitrogen_fixation and
earthworm_ecological_group. climatic_temp_mean
gains its first plant source. min_water_potential is kept
apart from turgor_loss_point: the two share 39 species and
agree on none of them, a field water potential and a pressure-volume
threshold being different quantities. sapwood_conductivity
and huber_value gain a second source each.
virus_richness and the FAPROTAX function sets stay
on their doors rather than entering add_trait(). Virus
richness tracks how much a host has been studied as much as what infects
it, with Homo sapiens at 936 viruses over 633,053 records, so
virus_record_count ships beside it to keep that
visible.
GlobalAnts is documented as unusable rather than left as an open question. Its guidelines gate access behind a per-project application, let a contributor require co-authorship, and state that redistribution is not allowed without each contributor’s permission.
Four genus-keyed doors return data rather than failing.
add_blanchard(), add_cefas_btrait(),
add_disperse() and
add_freshwater_insects_conus() join on genus,
but their assets were written with the genus names in
canonical_name and no genus column for the
join to reach. The build now materializes that column from the
registry’s own grain declaration, so a source declared at genus rank is
written joinable at genus rank.
The genus register is rebuilt over all nineteen backbones. Two rebuilds are folded together here. The first took it from the thirteen the published build covered to eighteen, so mammals, birds, prokaryotes, algae and fungi reached it through more than the general aggregators; the second adds COL XR, which was wired after that build ran. 496,127 genera become 503,262, coverage rows 1,421,182 become 1,871,955, and the share carrying a kingdom rises from 75.55% to 91.88%.
A backbone the coverage table does not carry no longer has every
name in it called out of scope. covered_genera_for()
returned an empty vector for such a backbone where the caller guarded on
NULL, so “I have no coverage for this backbone” was read as
“this backbone covers no genus”: every unmatched name was stamped
out_of_scope, and the abbreviated-genus and fuzzy stages
were skipped for all of them. COL XR sat in exactly that position
between being wired and the register being rebuilt, and it heads the
default priority order. The empty case now takes the path a missing
coverage file already took, which is to disable the filter and warn once
per session. A set of backbones is only as answerable as its
least-covered member, so one uncovered backbone disables the filter for
the whole set rather than falling back to the others’ union.
A genus filed under two kingdoms by one backbone is now read by that backbone’s own majority. Ordering by source priority alone left the winner to whichever row happened to sort first, which gave 93 genera their source’s minority reading and, because a row recording no kingdom stays eligible to fill the ranks below, produced classifications no source holds: Pteropus, 66 species of flying fox, was indexed as a fungus carrying the order Chiroptera. All 93 resolve, and the tiebreak applies only within a source, so a higher-priority backbone still outranks a lower one.
Three backbones join the default fallback chain, giving birds, mammals and prokaryotes a domain authority for the first time: AviList (40,572 rows), the Mammal Diversity Database (61,862) and LPSN (44,885). Every other major group already had one, and the cost of the gap was specific to taxify’s design – the default is a first-match chain, deliberately not a consensus vote, so with no authority in the domain band the answer for these groups was whichever aggregator ranked highest.
All three sit in the domain-authority band, ahead of GBIF, ITIS, NCBI
and OTT. This changes what taxify() returns by
default for bird, mammal and prokaryote names, which is the
intended effect. They were in the backbone registry without a manifest
entry, so until now nothing could resolve them at all.
Three more ground-beetle sources join
add_chowdhury(). add_finand() brings 34
Helsinki species whose body lengths were measured from the specimens the
authors caught — small, and carried because it is the only carabid
source independent of carabids.org, which every other reachable table
inherits its sizes and wing classes from.
add_imageomics_neon() brings the first North American
ground beetles, 75 species measured from images of pinned NEON
specimens, feeding elytra_length and a new
elytra_width. add_eberswalde() brings a
24-year monitoring record from 13 forest plots: abundance trend,
sensitivity to the 72-month SPEI drought index, a feeding guild refined
by field observation to name the prey, and Sustek’s humidity
scale.
Eberswalde’s size, wing class and latitude are surfaced on its
door but feed no trait. The deposit’s own README says they are
carabids.org verbatim, and the data agree exactly: over the 19 species
shared with add_chowdhury() every size is identical and
every wing class matches. Registering them would double-count one
lineage.
Ground beetles are now covered. add_chowdhury()
attaches traits and national occupancy trends for 382 German carabids
from Chowdhury et al. (2025): body length, wing morphology, trophic
level, habitat preference, both Red List codes, and the paper’s own
modelled two-year occupancy trend. Carabids are one of the most
intensively sampled insect groups in ecology, and taxify’s only beetle
source until now was saproxylic, restricted to the deadwood
guild.
add_trait() gains wing_morph,
three-state on purpose. A wing-dimorphic carabid produces both a
long-winged and a short-winged form, and which one dominates is the
question carabid dispersal ecology asks, so dimorphic (83
of 382 species) is a value of its own rather than a midpoint or a gap.
It is kept separate from the bird trait flightless, which
asks whether a species can fly at all. body_length,
diet_guild and primary_habitat gain the same
source; primary_habitat gains the vocabulary term
open, the modal class for German carabids, in preference to
narrowing it to grassland.
diet_guild also gains the NW European arthropod
compilation (Logghe et al. 2025), 3,800 species and the first broad
arthropod coverage the trait has had, along with the vocabulary term
fungivore. It agrees with the German carabid classification
on 86.6% of their 292 shared species.
Two columns were deliberately left out of the cross-source verb,
both documented in R/trait-registry.R so the decisions are
not relitigated. The German red_list_iucn restates a
national assessment in IUCN letters (perfectly diagonal against
the German code over all 382 species) and is not a global one, so it
stays on the door. And arthropod_traits
body_size_mm is a true body length for spiders and beetles
but forewing length for Lepidoptera (0.515 of the wingspan across 50
species), with no taxon column to separate them — see
gcol33/taxifydb#40.
add_trait() gains seventeen traits and widens four,
all from enrichment data already bundled: the registry now covers 204
traits across 456 source slots. Nothing needs re-downloading.
Fire ecology and regeneration are now reachable.
resprouting (AusTraits and BROT) is the post-fire
resprouter / partial / non-resprouter call, serotiny the
canopy seed-storage call, and soil_seed_bank the
persistence class. Worked examples: Quercus suber and
Arbutus unedo come back resprouters, Pinus halepensis
and Cistus albidus obligate seeders, Banksia serrata
serotinous.
Plant hydraulics, the drought-mortality axis, is now registered
from AusTraits and BROT: p50 (xylem embolism resistance,
MPa), turgor_loss_point, sapwood_conductivity,
huber_value, plus bark_thickness. Coverage is
thin (123 species for p50) and the trait documents
that.
Bryophytes enter the trait verb for the first time, from
Bryophytes of Europe Traits: bryophyte_life_form (During’s
turf / mat / cushion / weft scheme, kept separate from the
vascular-plant life_form for the same reason
lichen_growth_form is), shoot_length and
spore_diameter.
New from the coral and bird sources:
larval_development_mode (spawner or brooder),
substrate_attachment, linear_extension_rate,
polyp_retractability, and primary_habitat
(BIRDBASE’s 14-term vocabulary over 13,067 species). Also
self_compatibility from Tree of Sex.
sexual_system roughly doubles its plant coverage
with AusTraits sex_type (87% agreement with Tree of Sex
across 572 shared species) and gains bryophytes from BET.
flowering_start and flowering_end are no
longer Europe-only: AusTraits’ 12-character monthly string now feeds
them, read as the longest circular run so a southern-hemisphere
season that wraps the year boundary comes back as December to February
rather than January to December. diet_guild gains BIRDBASE,
listed last so it fills the birds AVONET and EltonTraits miss.
soil_seed_bank is the first trait to ship a
documented disagreement. BROT and AusTraits classify persistence by
different operational definitions and agree on only 67% of their 48
shared species, so the pair carries a caution: the default
coalesce reports the most complete source rather than blending them, and
explains itself in soil_seed_bank_caution.
add_trait() gains
aggregate_trait_fallback, which the
hybrids-and-aggregates vignette has been documenting as a
per-call argument since it was written (“turn it off, per call or
globally”). Only the global option existed, so the documented call
errored with unused argument. The argument now threads
through to enrich_simple() and defaults to the same option,
so existing behaviour is unchanged. Grain-pinned sources go through
enrich_by_group(), which has no aggregate fallback, and are
unaffected either way.
Rejections are documented in the registry header rather than left
to be rediscovered, including three octocoral columns that carry no
information at all – tentacles_per_polyp is 8 for every one
of 3,606 species, because eight tentacles is the defining character of
Octocorallia.
Bundled enrichment data now resolves taxonomic names across all
fifteen backbones during the build, up from the seven broadest. An
enrichment value keyed to a name accepted only by a domain-specific
backbone (Euro+Med, Species Fungorum, AlgaeBase, FishBase, SeaLifeBase,
Reptile Database, LCVP, or WCVP) now joins a taxify()
result that resolved through that backbone, instead of falling through.
The manifest points at the rebuilt enrichment release.
Documentation: corrected references that presented WFO as the
default backbone. The default is COL, matched first in the fallback
chain, and the first taxify() call installs the default set
COL, GBIF, and ITIS.
Removed taxify_download_vtr(), the deprecated alias
of taxify_download(). Use
taxify_download().
Slimmed the bundled example database. The BIEN and AusTraits
example .vtr fixtures were the full production tables (116k
and 35k rows); they now carry only the few dozen species the offline
examples and add_trait() tests use. Installed size drops
from ~9.9 MB to ~3.2 MB. The offline examples and test coverage are
unchanged.
add_hybrid_info() gains hybrid_parent_1_id
/ hybrid_parent_2_id: the backbone taxon_id of
the accepted taxon each parent of a hybrid formula resolves to. An
unresolved hybrid formula has no single backbone record, so the result’s
own taxon_id is NA; the two component ids now
travel in these columns, each ready to pass straight to
id2name().backend is renamed to backbone throughout the
API (issue #24)Two real concepts had one name. A backbone is a data
source and its .vtr file; a backend is the
taxify_backend S3 handle that knows how to read one. The
name-string layer conflated them –
install_backbones(backends =) and
backbone_path(backend) collided inside single lines.
backbone now names the data source and its name string
everywhere, backend names the S3 handle only, and
resolve_backend() is the single crossing point between
them.
This breaks existing code, with no aliases.
taxify(backend = "wfo") is now
taxify(backbone = "wfo"), and the same for
synonyms(), children(),
upstream(), downstream(),
id2name(), reconcile(),
comm2sci(), sci2comm(),
class2tree(), lowest_common() and
taxify_download().
install_backbones(backends =) becomes
install_backbones(backbones =).
The backend output column is renamed to
backbone in taxify(),
taxify_long(), reconcile(),
inspect() and taxify_register_coverage(). A
lockfile’s backends key becomes backbones, so
a lockfile written before this release no longer loads.
Three other conflations went with it. comm2sci() and
sci2comm() returned the accepted name as
scientific_name; it is accepted_name, the name
every other verb uses. Their query column and
parse_name()’s input and
upstream()’s query are all the caller’s input
string, so they are all input_name now.
register_enrichment()’s source argument is the
human-readable description, which enrich_simple() already
called source_label; the key is name.
bb_path and vtr_path named the same
value; it is vtr_path everywhere.
Not renamed: the backends key inside
inst/manifest.json, and the backend column
inside the published backend_coverage.vtr. Both are
serialized schemas that taxifydb writes and taxify only
reads, so renaming them is a coordinated release rather than a rename.
The runtime translates at the boundary, and
taxify_register_coverage() reports
backbone.
add_fungal_traits() joins on genus, but
the bundled example database shipped a fungal_traits.vtr
keyed on canonical_name with no genus column,
so its own documented example errored. The fixture is rebuilt from the
released asset at genus grain.The README’s headline “1,862x faster than WorldFlora” had nothing
in the repository behind it, and neither did the memory figures in the
large-scale vignette. Both are now produced by committed scripts –
scripts/benchmark-worldflora.R and
scripts/benchmark-memory.R – which write their runs to JSON
alongside package versions and the backbone snapshot. On 1,000 names
that each carry a one-character typo, taxify takes 18.8 s against
WorldFlora’s 4,192 s, both reading the same Zenodo Darwin Core archive;
exact matching is 2.2 s against 17.1 s.
The invented console output is gone from the large-scale
vignette. The timing chunks show how to measure rather than asserting a
number that was never run, and the memory section reports resident set
size, which is what a backbone actually costs – gc() sees
only a fraction of it, since vectra reads the .vtr through
the operating system. Opening a backbone costs 1.8 to 2.2 times its
.vtr size, and a 5,000-name all-fuzzy pass adds 1.3 GB
against WFO.
Backbone row counts, download sizes and the enrichment count are
generated from inst/manifest.json and taxify’s own backbone
registry, between HTML comment markers, by
scripts/sync-readme-stats.R. The hand-kept copies had
drifted up to 4.1x (WFO listed at 400k names against 1.6M, its download
at ~120 MB against 797 MB). A manifest-docs workflow fails
if a block goes stale.
Smaller: the taxify() match-type list in the README
was missing hybrid_formula, and the Euro+Med row count in
the backends vignette still described the 2020 build.
The register carries the kingdom_group,
taxon_group and life_form that
taxify() reports, and it was built on each machine from
whichever backbones that machine happened to have installed. Two users
running identical code therefore got different labels for the same name.
genus_register.vtr and backend_coverage.vtr
are now built by taxifydb over a fixed backbone set,
published, and resolved through the same chain as any other asset: disk,
download, then a local build. Every install reads the same 496,127
genera.
The build pipeline itself – the thirteen genus extractors,
kingdom normalization and inference, the GBIF hierarchy walk, and the
family life-form table – moved to taxifydb (about 1,900
lines). taxify_build_register() remains as an escape hatch
that delegates there, and taxify_download("register")
fetches the published pair.
The register now lives at
<data_dir>/genus_register/latest/ rather than
<data_dir>/unified/latest/, so it follows the same
versioned layout as every backbone and picks up a new release through
the usual version check.
options(taxify.offline = TRUE))file:// manifest URL still resolves. The
test suite runs under it, which is what makes a run independent of any
release published between two runs.clean_names() stripped a capitalized specific epithet
as if it were an author, so "Quercus Robur" cleaned to
"Quercus" and then matched the genus rather than the
species. Trailing authorship is now removed by token position: the token
after the genus is the specific epithet whatever its case, so Title-Case
("Quercus Robur") and all-caps legacy
("QUERCUS ROBUR") binomials keep their epithet, while a
genus followed by an author ("Rosa L.") still reduces to
the bare genus. Internal-capital author abbreviations
("Picea abies (L.) H.Karst.",
"Solidago canadensis A.Gray"), which the previous pattern
left in the cleaned name, are removed too.c("Quercus robur", "QUERCUS ROBUR")) was flagged as a
many-to-one merge, because the merge detector grouped on the raw input
string while the status comparison used the normalized form. Input
distinctness is now measured in the same normalized space, so a case- or
spelling-only variant counts as one input; genuine merges are
unchanged."" (rather than NA)
for an unresolved rank could make lowest_common() report
the blank as the shared ancestor. Empty rank values are now treated as
unresolved, so the most recent common ancestor falls through to the next
rank every taxon actually shares.synonyms(), children(),
downstream(), upstream() and
id2name() defaulted to a single hardcoded backbone
("wfo" or "col"), so on a fresh install
synonyms("Quercus robur") triggered a WFO download the
default backbone set does not include. They now default to
backend = NULL, which resolves to the highest-priority
installed backbone, matching taxify(),
reconcile() and comm2sci().near_duplicate_targets() measures the edit-distance and
length gates on the epithet, not the whole binomial, so
"Carex flava" is no longer flagged as a near-duplicate of
"Carex flacca". A genuine one-edit epithet typo still
fires.join_col absent from the
.vtr now errors instead of silently falling back to
canonical_name (the mechanism behind past all-NA doors),
and a mapped column absent from the schema warns, naming the enrichment
and column, rather than attaching a silent all-NA column. The diagnostic
is gated off the bundled example database.[.taxify_result method carries
taxify_meta through subsetting, so
add_combine() (and any manual subset) no longer strips it.
Reported columns are selected by exact set, so an already-imputed value
is never mislabelled as a measurement.summary() no longer errors on an enrichment entry
without a version; taxify_restore() reports a distinct
"unverified" status when nothing could be compared (instead
of a false "ok"), and tolerates zero-length lockfile
fields.download_enrichment() copies license,
available_groups and citation into the
installed meta.json (licence is no longer NA
for downloaded enrichments); ensure_enrichment() refuses to
download an unbundled enrichment into the example database.group_col for all
seven grouped enrichments (griis, gidias,
alien_first_records, wcvp,
marine_distribution, common_names,
glonaf), and enrichment_groups() falls back to
the manifest when the installed meta.json lacks it. A
grouped enrichment installed before the metadata was copied reported
itself as ungrouped with no way to recover, because
available_groups had a manifest fallback and
group_col did not.score_candidates() ordered by status, rank, validity,
epithet and then taxonID, so among several fuzzy candidates
the winner was decided by ID and a farther name could beat a nearer one.
"Carex flavaa" resolved to Carex flacca
(distance 0.167) while Carex flava (0.083) was in range,
and the two were reported ambiguous although one was strictly closer.
Distance now sorts first, so the nearest name wins and ambiguity is
declared only among equidistant candidates. Exact matching is
unaffected.dedup_fuzzy_targets() ran once per fuzzy pass, so a
query dropped by the genus-blocked pass competed again in the
prefix-blocked fallback and claimed the backbone row the first pass had
already taken. The claimed rows are now carried forward, so two queries
can no longer collapse onto one row.tests/e2e/test-asaas-validation.R asserted nothing: it
printed its agreement rates with cat(), so a matching
regression reported a worse number and passed, and it read from a
hardcoded J:/ path. It now locates the corpus through
TAXIFY_ASAAS_CORPUS, asserts floors on match rate and on
accepted-name, family, genus and WFO-ID agreement over the whole corpus,
and asserts both sides of the fuzzy trade so neither recall nor
precision can erode unnoticed. Divergence is split into backbone drift,
the corpus hybrid-formula convention, and genuine misses, and only the
last is capped. See tests/e2e/README.md for the baseline
and how to read a disagreement.NA only,
test-doors.R accepted one populated column out of twenty,
children() case-insensitivity held at zero rows,
summary() was matched with grepl("3", .), and
the multi-backend fallback test used fixtures that both carried the
species. Self-fulfilling comparisons in
test-default-backend.R, test-add-trait.R,
test-region.R, test-gap-verbs.R and
test-new-verbs.R now assert independent literals.add_common_names(),
add_wcvp(region=), add_glonaf(),
add_alien_first_records(),
install_backbones(), and taxify_restore()’s
version_drift / content_drift /
missing branches. Negative and threshold-boundary fuzzy
tests cover equidistant candidates, typos that must not resolve to a
close-but-wrong species, and the accept/reject flip.fuzzy_join
errors now warn instead of silently returning no matches, and
taxify() validates fuzzy and
fuzzy_threshold.backend-*.R clones collapse into one
registry-driven factory; adding a backbone is now a registry row plus a
manifest entry. The three backend-info doors
(add_wfo_info() / add_gbif_info() /
add_col_info()) share one
enrich_from_backbone() helper, and add_data()
uses a vectorized, typed-NA join keyed on accepted_id.taxifydb::build_register(),
which taxifydb added during 0.1.18 rather than at its start, so a 0.1.18
built before that point satisfied an unversioned dependency and then
failed the call. Suggests now names
taxifydb (>= 0.1.19), the first version whose number
identifies code that carries the function.\donttest example now runs offline against the
example database or is \dontrun, so
R CMD check --run-donttest never triggers a download. UTF-8
BOMs removed from three R files and three vignettes;
taxify()’s @return documents all 26 columns;
the FISHMORPH trait list matches the columns
add_fishmorph() emits.A name whose genus the leading backbone did not cover was marked
"out_of_scope" and then skipped by every backbone behind
it, because the fallback loop only retried rows whose
match_type was NA. The chain ended at
whichever backbone happened to be first. The package’s own documented
example,
taxify(c("Quercus robur", "Panthera leo"), backend = c("wfo", "gbif")),
returned Panthera leo as out_of_scope without ever
consulting GBIF.
The default backend = NULL path was hit hardest,
since COL leads the priority order: on a full install 41.4% of register
genera (207,980 of 502,088) sit outside COL’s coverage, and every one of
them is carried by a backbone further down the chain. 14,354 of those
are marine genera that never reached WoRMS, so region=
could not constrain a marine name COL does not list.
taxify("Parvocaris samnitica") now resolves through WoRMS
instead of returning out_of_scope.
"out_of_scope" means what the documentation always
said it meant: no backbone in the query covers the genus. The
per-backbone mark still runs, so the abbreviated-genus and fuzzy stages
are still skipped for a backbone that cannot carry the name (which also
stops a spurious fuzzy near-match there from outranking the exact match
waiting further down the chain), but it is released again for any name
another backbone in the chain still covers. A single-backend query is
unchanged.
backend and backbone_version now name
only the rows a backbone lookup actually resolved. They were stamped
whenever match_type was non-NA, which swept in
the verdicts a backbone never produced: an out_of_scope row
read the leading backend’s name and its resolved version even though no
lookup found it there. Selecting
result[result$backend == "wfo", ] then counted those rows,
so a per-backbone hit rate over-reported every backbone in the chain.
"exact", "exact_ci", "fuzzy" and
"abbrev" carry the two columns;
"out_of_scope", "hybrid_formula" and
"none" leave them NA.
0.3.20 added the marine range providers but the data they read
did not exist yet, so the marine path stayed inert for everyone. Both
assets are now published and registered in the manifest, and
region= / coords= constrain marine matches out
of the box.
New meow boundary entry: 196,807 polygon vertices
across all 232 Marine Ecoregions of the World, resolved through
download_backbone() the way wgsrpd is.
Reference geometry, so it does not join the taxonomic backbone set that
list_backbones() reports.
New marine_distribution enrichment entry: WoRMS
distribution records rolled up to MEOW ecoregions, keyed on
canonical_name with a region_code and a
native/introduced status, the marine counterpart of the WCVP range
table.
taxify_regions() lists both vocabularies
region= accepts, and gains a scheme argument
("all", "wgsrpd", "meow") and a
scheme column. It resolved marine names as soon as the
asset was installed but only ever listed the botanical crosswalk, and
the warning for an unrecognised region pointed users there. MEOW rows
reuse the three name columns, since the two schemes nest the same way:
ecoregion as name, province as level2_name,
realm as level1_name. Marine rows appear only when the
asset is installed, which is also when they resolve.
region= and coords= now constrain fuzzy
matching for marine taxa, not only vascular plants. When the
marine_distribution asset is installed,
region_range_sets() unions two providers behind the
unchanged arguments: WCVP (plants, keyed on TDWG Level 3
tdwg_code) and the marine distribution table (keyed on MEOW
ecoregion region_code). Each resolved region code is routed
to its provider by vocabulary – alphabetic TDWG codes to WCVP, numeric
MEOW ECO_CODEs to the marine table – through one shared
engine, so a plant-only query never touches the marine asset and vice
versa.
region= accepts MEOW ecoregion codes and ecoregion /
province / realm names (a province or realm expands to its member
ecoregions), resolved from the installed marine asset.
coords= maps points to MEOW ecoregions by point-in-polygon
against a new meow.vtr boundary set, unioned with the
WGSRPD botanical lookup, so a coastal coordinate can resolve to both a
botanical region and a marine ecoregion. The point-in-polygon machinery
is now scheme-generic across the botanical and marine boundary
sets.
Marine support is inert until the
marine_distribution enrichment is installed: the plant-only
default path is unchanged.
parse_name() decomposes a name into its parts – genus,
specific epithet, infraspecific rank and epithet, authorship, hybrid
status, open-nomenclature qualifier, and the canonical form – without
matching against a backbone, the role rgbif::name_parse()
or gnparser fill. It reuses the same cleaning pipeline
taxify() runs, so a name breaks apart the way it
matches.upstream() returns the higher classification
(ancestors) of a taxon as a tidy long frame, one row per rank from
kingdom down to genus; to = restricts it to a single rank
(“what family is this in?”). The ancestor-direction complement of
downstream().sci2comm() resolves scientific names to their common
(vernacular) names – the forward complement of comm2sci(),
reading the bundled common_names data offline.
resolve = TRUE (default) taxifys the input to its accepted
name first.reconcile() reports how a checklist maps onto a
backbone’s current treatment, classifying each name as
unchanged, synonym, misspelling,
ambiguous, or unresolved, and flagging
many-to-one merges where several inputs collapse onto one accepted name
– a checklist-migration summary.taxify_lock() / taxify_restore() write and
verify a reproducibility lockfile: taxify_lock() serializes
the resolved backbones and enrichment layers (name, version, content id,
download date) behind a result to JSON, and
taxify_restore() compares a lockfile to the current install
and reports ok / version_drift /
content_drift / missing.taxify() now
resolves it to the single author-matching accepted target instead of
returning the tie. The tiebreak only touches ambiguous author-bearing
rows; the fast path and every unambiguous result are unchanged.R CMD check warning about an unresolvable
taxifydb::build_meow reference. The scheme’s boundary
builder is now looked up by name at run time, so the marine builder is
used when taxifydb provides it and skipped cleanly when it does
not.comm2sci() resolves common (vernacular) names to
scientific names – the reverse of add_common_names(). Reads
the bundled common_names data offline;
resolve = TRUE runs the matches through
taxify() and returns an enrichable
taxify_result.id2name() looks a backend ID (a GBIF key, ITIS TSN,
WoRMS AphiaID, …) back up to its name, rank, classification, and
accepted-name resolution – the inverse of the taxon_id /
accepted_id columns taxify() emits.downstream() lists every accepted taxon at a chosen
rank (species by default) beneath a higher taxon, where
children() gives only the immediate level.class2tree() assembles a taxonomy tree (Newick, plus an
ape phylo object when ape is
installed) from a set of resolved names, and
lowest_common() reports the deepest rank at which a set of
names shares a common ancestor.taxify()taxify(..., kingdom = ) restricts matches to one or
more kingdoms ("animals", "plants",
"fungi", …), so a name shared across kingdoms (a
Prunella that is both a bird and a plant) resolves to the
intended one. A match whose kingdom is wrong is passed on to the next
backbone in the fallback chain; the kingdom is read from the backbone
where it stores one, falling back to the genus register otherwise.list_enrichments().download_backbone() now clears the stale .meta
build sidecar it leaves behind, restoring the invariant that a
downloaded backbone carries only its meta.json. Previously
the leftover .meta shadowed meta.json in
format_backbone_version(), so a freshly downloaded release
(e.g. Euro+Med 2026.07) was still labelled with the old built version
(2020.1) in the backbone_version output column.meta.json or manifest carrying a leading UTF-8
byte-order mark (as written by Windows PowerShell’s
Set-Content / Out-File) no longer emits an
“illegal byte-order-mark” warning on every version read. All meta.json
and manifest reads strip a leading BOM before parsing.taxify_build_register() is now exported. It builds
the unified genus register from the backbones you have installed and is
the front door for the life_form /
kingdom_group / taxon_group output columns,
out-of-scope detection, and inspect()’s no-backbone checks.
Previously the only builder was internal, so
taxify_load_register() on a fresh setup pointed users at a
function they could not call, and the manifest’s register entry was a
Zenodo placeholder that never resolved.
taxify_download("register") is a convenience alias for
it.
Building the register no longer force-downloads every known
backbone. It unions only the backbones actually installed (via the new
internal installed_backbone_path()), matching the
documented “union of installed backends” behaviour instead of silently
pulling several gigabytes.
The build-from-source shims no longer pass a hardcoded version
label into taxifydb::build_<name>(); taxifydb stamps
its own current version. A backbone built from source is now labelled
with the data it actually contains, not a constant that drifts as
releases advance.
format_backbone_version() falls back to the
download-time meta.json (the manifest version) before the
backend constructor’s static default, so a downloaded backbone reports
the version it was downloaded at.
Manifest: the reptiledb backbone points at the
reptiledb-2026.07 release (byte-identical to 2026.06) and
records its content id; the placeholder register entry is
removed.
add_gidias()
can ask what a species impactsGIDIAS scores each impact record against an affected native
taxon, so add_gidias(group = ) reads impact at that grain:
Felis catus is "MO" against invertebrates (reduced
populations) where the default is "MV", the global
extinctions it drove among vertebrates. 28% of species with an affected
taxon recorded impact two or more of the five groups
(Plant, Invertebrate, Vertebrate,
Microbe, Fungi), so for those the
species-level category is the most severe impact on anything, not the
impact on each thing. enrichment_groups("gidias") lists
them; several groups suffix the columns, as
add_alien_first_records() does for countries.
add_gidias() with no group is
unchanged: it reads the "Any" grain, the same all-records
summary it returned before, with the same columns. "Any" is
the only grain carrying SEICAT and the impact records with no affected
taxon recorded, so gidias_seicat_category is
NA on the other groups. Requires the rebuilt
gidias enrichment.
cols now works on the grouped doors even when the
source carries no columns beyond the curated set, which previously
ignored it.
format_bibtex_entry()
now emits the citation’s note field, so an access date
recorded in the manifest reaches the BibTeX entry. Entries carrying no
note are unchanged.-1 missing-data code in its two
temperature columns, so 90 introduced fish (goldfish, zebrafish, brown
trout) reported a July maximum of -1 degrees C, which is impossible in
the conterminous US. add_fishtraits() surfaced it as
ft_min_temp_c / ft_max_temp_c. The rebuilt
data reads NA for those species, and the warmest-month value now bottoms
out at a believable 20.4 degrees C. Species whose January minimum
genuinely is -1 keep it.ft_itis_tsn and ft_common_name, and
produced five unusable rows named after a family (“Percidae .”). Both
are cleaned.climatic_temp_min and
climatic_temp_max (degrees C): the coldest-month and
warmest-month temperature at a species’ range centroid, from FishTraits.
They join climatic_temp_mean in the climatic-niche family,
which stays apart from the organismal thermal_max /
thermal_min. Largemouth bass shows why the split earns its
keep: its range tops out at 32.0 degrees C while it can survive 33.5.
These were held back until the -1 code above was
fixed.chromosome_number reported a count nobody had measured,
and is fixed. Arabidopsis thaliana read 15 and Acer
campestre 39, from species recorded at more than one cytotype: Kew
holds a diploid 2n = 10 and a tetraploid 2n = 20 for
Arabidopsis, and averaging them lands on 15, which is in
neither record. The value is now the base cytotype (10 and 26 for those
two), and the range across cytotypes is reported in
chromosome_number_min / chromosome_number_max,
so nothing is lost. 421 species change value, and every value now comes
from a real record.add_kew_cvalues(cols = "all") attaches
cval_original_reference and
cval_estimation_method, both populated for every species,
covering 941 distinct papers. Where a species carries records from
several papers, all are listed, as with Arabidopsis thaliana
(“Bennett et al.,2003; Schmuths et al.,2004”).add_ccdb(): somatic chromosome numbers from the
Chromosome Counts Database for 65,051 plant species, with the range of
cytotypes each spans. CCDB states no licence, so taxify publishes no
copy; the door builds it on your machine through taxifydb, like the
other build-only sources.chromosome_number trait continues to come from Kew
alone. CCDB covers seven times more species, but a source reachable only
where a build tool is installed would make add_trait()
return a different number on two machines running the same code.add_kew_cvalues()
in picograms rather than joining the prokaryote genome_size
trait in base pairs. The picogram to base-pair conversion is a constant,
but a plant 1C value counts every subgenome a polyploid carries, while a
bacterial genome size counts one chromosome.add_gmpd() (Global Mammal Parasite Database 2.0:
per-host parasite richness, counts by parasite type, mean prevalence),
add_plantatt() (British and Irish vascular plants:
Ellenberg values, maximum height, life-form/woodiness/status codes),
add_bryoatt() (the bryophyte companion – a group otherwise
almost absent from the bundled traits), and add_clopla()
(CLO-PLA clonal and bud-bank traits of the Central European flora, 29
codes kept verbatim).climatic_temp_mean: the mean annual temperature of
a species’ range, in degrees C, from the NW European arthropod dataset
(WorldClim BIO1 over occurrence buffers) and ReptTraits (CHELSA over
GARD ranges). It is kept strictly apart from thermal_max /
thermal_min, which are organismal CTmax and CTmin: a range
climate is bounded by dispersal, competition and history, so it sits
well inside what an animal can survive.forearm_length (mm): the standard bat measurement, from
COMBINE, PanTHERIA and the European bat dataset (the first two carried
it for 1130 and 1012 species without any trait reaching it).chromosome_number (2n): from the Kew Plant DNA C-values
database.thermal_max / thermal_min gain the
freshwater thermal-tolerance database (CTmax and CTmin of freshwater
fish, invertebrates and amphibians).body_mass, longevity,
clutch_litter_size and diet_guild gain the
European bat dataset; longevity and
age_at_maturity gain FishTraits;
clutch_litter_size gains the zooplankton per-clutch egg
count.taxify(backend = NULL) (the new default) matches
against every installed backbone as a first-match
fallback chain, instead of only WFO. A name is resolved by the first
backbone that matches it in priority order – COL, then the domain
authorities (marine, vascular plants, fungi, algae, fishes, reptiles),
then the broad aggregators (GBIF, ITIS, NCBI, OTT) – so cross- kingdom
input works without knowing which backbone to name, and disagreement
cases resolve to the more current treatment
(e.g. Macropus rufus -> Osphranter rufus).
It is a first-match pick, not a consensus vote (a vote would regress
toward the most conservative treatment across backbones that copy one
another); use mode = "wide" / "agreement" to
see disagreement.taxify() call downloads a default set once – COL,
GBIF, and ITIS – covering all kingdoms with a genuine
cross-backbone agreement signal. Pre-install a different set with the
new install_backbones(), or set it via
options(taxify.default_backbones = ...). The priority order
is configurable with
options(taxify.backbone_priority = ...).install_backbones() downloads one or more
backbones for offline use (defaults to the first-run set).backend explicitly is unchanged, so existing
calls keep working; only the unset default moved off WFO.add_combine() is now the full COMBINE door rather than
a thin alias of add_combine_reported(). It attaches the
reported (measured) values and fills each still-missing cell from
COMBINE’s phylogenetically imputed table, so a single call reaches
COMBINE’s fullest coverage. A measurement is never overwritten – the
reported value wins and the model only fills gaps – and a companion
combine_<trait>_src column tags every cell as
"reported", "imputed", or NA,
keeping the measured-vs-modelled distinction explicit per cell.
add_combine_reported() (measured only) and
add_combine_imputed() (the imputed table on its own) are
unchanged. Runtime-only; no data rebuild.add_cefas_btrait() now joins on genus. The
Cefas benthic-traits database codes traits at genus level, so the
previous species-level join returned NA for every species;
it now annotates every species in a coded genus.add_epa_freshwater() now uses a species-first,
genus-fallback join. The US EPA Freshwater Biological Traits Database
records each trait at the finest resolution available, so a species
keeps its species-level values and any trait still missing is filled
from the taxon’s genus-level row (a species value is never overwritten).
This is a new genus_fallback option on the shared
enrichment engine, available to any mixed-resolution source.add_kew_cvalues() (plant genome
size, chromosome number and ploidy from the Kew Plant DNA C-values
database, CC BY), add_copepod_traits() (marine copepod body
size, egg and clutch traits, Brun et al. 2017, CC BY 3.0),
add_fishtraits() (United States freshwater-fish life
history, temperature and salinity tolerance, and conservation traits,
Frimpong & Angermeier 2009, public domain),
add_epa_freshwater() (freshwater-invertebrate functional
traits, US EPA, public domain), and add_cefas_btrait()
(North-West European shelf benthic biological traits, Cefas, OGL v3.0).
Each is source-prefixed (cval_, cop_,
ft_, epa_, cefas_) and takes
cols = "all" for the full column set.add_combine_reported(),
add_combine_imputed(), enrichment_groups(),
and the low-level building blocks.thermofresh, ramond,
freshwater_insects_conus, and eurobat are
flagged static in the manifest, so their version is not re-checked each
session.add_gidias() joins per-species invasion-impact
aggregates from GIDIAS (Bacher et al. 2025, CC BY 4.0), the IPBES
invasive-species assessment’s global impact compilation. Each species
carries its IUCN EICAT environmental-impact category
(gidias_eicat_category,
MC/MN/MO/MR/MV,
or DD) and SEICAT socio-economic-impact category
(gidias_seicat_category), each the most severe magnitude
among the species’ documented negative impacts, alongside the driving
mechanism, affected well-being constituents, realms, and record and
source counts. Only the derived per-species aggregates are distributed,
not the raw impact records.
add_trait() gains two categorical traits,
"environmental_impact" (EICAT) and
"socioeconomic_impact" (SEICAT), so invasion impact
reconciles across sources the way every other trait does. GIDIAS is the
first source; the ordinal categories are shared so further EICAT
assessments can coalesce onto them later.
add_invacost() joins per-species economic-cost
aggregates from InvaCost (Diagne et al. 2020, CC BY 4.0):
invacost_cost_total_usd (cumulative documented 2017-USD
cost), invacost_cost_n (number of estimates), and the
dominant invacost_cost_type.add_phylacine() surfaces
phylacine_mass_method and
phylacine_mass_method_class, recording whether a body mass
is measured (reported), allometrically
estimated, or phylogenetically imputed.add_trait("body_mass") now flags model-derived
PHYLACINE masses per species: where PHYLACINE contributes an imputed or
estimated mass, body_mass_caution explains it for that
species only; measured masses are left unflagged. A trait registry
source can attach such a per-record caution via caution_col
/ caution_fn, distinct from the existing whole-source
method caution.taxify() gains a mode argument. With more
than one backend, the default
mode = "fallback" is the usual fallback chain, while
mode = "wide" consults every backbone for every name and
adds one accepted_<backbone> column plus a logical
all_agree, and mode = "agreement" adds
n_backbones_matched, n_distinct_accepted, and
all_agree. Both are a strict superset of the standard
result (a single accepted_name, still pipeable into the
add_*() enrichments), so a backbone disagreement, such as
GBIF keeping Macropus rufus where the Catalogue of Life
resolves it to Osphranter rufus, is visible in one call
instead of querying each backbone by hand.enrichment_groups() lists the group values a grouped
enrichment door can filter on, the way enrichment_cols()
lists a door’s columns. It answers “what country / region / language
codes are valid?” for add_griis(country=),
add_wcvp(region=), add_common_names(lang=),
and add_alien_first_records(country=).An aggregate query ("Rubus fruticosus agg.",
"... s.l.") now falls back to the nominal binomial’s trait
when a source carries no aggregate-level value. Aggregate-level values
are still used first where present; the binomial is a pragmatic
stand-in, not a real aggregate-level measurement. This also fixes a
preserve-fell-back aggregate (one with no dedicated aggregate taxon in
the backbone) reaching its binomial’s traits.
The fallback is on by default and can be turned off per call with
aggregate_trait_fallback = FALSE, or globally with
options(taxify.aggregate_trait_fallback = FALSE), which
keeps a resolved aggregate without aggregate-level data as
NA.
options(taxify.trait_provenance = TRUE) now adds a
character <enrichment>_basis column
("primary" a same-level hit, "aggregate" a
species inheriting its aggregate’s value, "binomial" an
aggregate standing in on its binomial) in place of the earlier logical
<enrichment>_inherited flag, so the basis of every
filled value is explicit.
Hybrid names are handled by type instead of being reduced to
their first component. taxify() gains a
hybrid_type column ("nothogenus",
"nothospecies", "formula", or
NA).
Hybrid formulas ("Salix alba × Salix fragilis") no
longer resolve to a single species. Previously the cross was silently
cut to its first parent and returned as an exact match to
Salix alba; now the cross row carries
match_type = "hybrid_formula" with NA
backbone-match columns. The parent binomials, and their accepted names,
are available on demand via add_hybrid_info(), which now
adds hybrid_parent_1, hybrid_parent_2,
hybrid_parent_1_accepted, and
hybrid_parent_2_accepted.
The same-genus formula shorthand is recognized:
"Salix alba × fragilis" (second parent written as a bare
epithet) parses to parents "Salix alba" and
"Salix fragilis".
Nothogenus names match backbones that store the multiplication
sign. "× Cupressocyparis leylandii" previously returned
NA against backbones whose canonical form keeps the sign
(e.g. "× Cupressocyparis leylandii"); matching now tries
the "× Genus ..." and "×Genus ..." forms
alongside the sign-stripped binomial. Nothospecies
("Quercus × hispanica") continue to match as
before.
New list_backbones() lists every supported taxonomic
backbone with its scope, name count, download size, version, install
status, and source, mirroring list_enrichments(). New
taxify_databases() stacks the backbones and enrichments
into one overview so the full breadth is one call away. A canonical
backbone registry now backs resolve_backend(),
installed_backbones(), and these verbs, so the supported
set cannot drift between them.
A “Databases” pkgdown article lists every backbone, enrichment, and trait, generated from the shipped manifest so it stays current.
.vtr files. They previously had no published release and
could only be built from source; both are now in the manifest
(lcvp-3.0.1, wcvp-2026.06), so all fifteen
backbones resolve without taxifydb installed.clean_names() recognizes a much wider set of taxonomic
qualifiers and rank abbreviations. Previously an unrecognized marker
survived into the cleaned name, so the name no longer matched the
backbone’s bare binomial/trinomial (it dropped to fuzzy) and the
annotation was lost from the qualifier column. Now folded
to their canonical tokens: the subspecies abbreviations
ssp. and nssp. and the spelled-out
subspecies (to subsp.); the sensu-stricto form
s.s. (to s.str.); the forma spellings
fo. and forma (to f.); the
infraspecific ranks subvar., subf., and
convar.; the notho- (hybrid) ranks nothosubsp.
and nothovar. (to subsp./var.,
the hybrid signal being carried separately by the multiplication sign);
cultivar cv.; the pathogen infrasubspecific categories
f. sp. (forma specialis, previously mislabelled as a bare
forma) and pv. (pathovar); the determination marker
nr. (“near”); the open-nomenclature markers
indet. and sp. nov.; the long and bare concept
forms s. lat. and coll. (to
s.l.); and the species-group markers group and
gr.. Each token matches only as a whole trailing word, so
it never touches a real epithet (Carex novae-zelandiae and
Convallaria majalis are untouched). The qualifier registry
in R/clean.R remains the single source of truth for every
spelling.taxify(x, backend = "wcvp") matches against Kew’s World
Checklist of Vascular Plants (Govaerts et al. 2021, ~1.4M names, CC BY
4.0); backend = "lcvp" matches the Leipzig Catalogue of
Vascular Plants (Freiberg et al. 2020, MIT). Both slot into the fallback
chain (backend = c("wcvp", "wfo")) and contribute their
genera (kingdom Plantae) to the unified genus register. Fifteen
backbones are now available.taxify() does not. synonyms() lists every
synonym that resolves to a name’s accepted taxon (the reverse of the
forward resolution). add_classification() fills the higher
ranks (kingdom, phylum, class, order) from the matched backbone,
complementing the family and genus already in
the core output. children() lists the accepted taxa within
a genus or family, for building a checklist rather than only validating
one. taxify_candidates() expands an ambiguous match
(is_ambiguous) into one row per candidate accepted taxon,
so homonyms can be resolved by hand.taxify() gains an aggregate_fallback
column that makes the default aggregates = "preserve"
accountable. Where a backbone carries no dedicated aggregate taxon for
an aggregate query, preserve falls back to the nominal binomial; that
collapse is now flagged (TRUE on fallback,
FALSE when the aggregate taxon was matched, NA
for non-aggregate queries and under collapse) rather than
being silent. Only Euro+Med (433 aggregate taxa) and WoRMS (189) carry
them, so preserve is a no-op for the other backbones – the flag now says
so per row.add_kew_sid() opens the Kew Seed Information Database
(SER-SID, CC BY 2.0): seed weight (thousand-seed weight over 42,000
species), storage behaviour (orthodox/recalcitrant/intermediate), oil
and protein content, life form, and fruit type, joined on
accepted_name across 50,146 accepted names. Verified
end-to-end (Quercus robur 3493 g/1000 seeds and recalcitrant;
Helianthus annuus 43.5% seed oil). Its seed weight also joins
the cross-source add_trait("seed_mass") verb as a seventh
source (a thousand-seed weight in grams equals the per-seed mass in mg;
grounded at ratio 1.00 against Diaz, BIEN, and AusTraits), roughly
doubling seed-mass species coverage.add_edwards_phyto() opens the Edwards et al. (2015)
phytoplankton nutrient-utilization database (~130 species): Droop/Monod
uptake and growth parameters for ammonium, nitrate, and phosphorus
(mu/k/vmax/qmin/qmax),
plus cell volume, carbon content, taxonomic group, and marine/freshwater
habitat. A curated core attaches by default; cols = "all"
surfaces every uptake parameter. Door-only (single-source physiology
with no cross-source analogue), so it stays out of the
add_trait() verb. Verified end-to-end (Alexandrium
catenella recovered as a marine dinoflagellate).add_trait() traits covering algae,
marine-benthic invertebrates, and octocorals, each grounded on its
source’s own vocabulary before wiring. Algae (AlgaeTraits):
calcification, gamete_type,
algal_life_cycle (dominant ploidy phase),
algal_substrate. Marine benthos, harmonized across two
sources (Arctic Traits + New Zealand Trait Database):
bioturbation (Solan/Queiros functional groups),
living_habit, feeding_guild. Octocoral
(Gomez-Gras et al. 2024): skeletal_rigidity,
colony_growth_form. Verified end-to-end (Corallina
calcified-articulated, Fucus diplontic, Laminaria haplodiplontic; the
bryozoan Alcyonidium gelatinosum an attached suspension-feeder with no
bioturbation).add_trait() traits, each
grounded on its source’s own values before wiring:
gc_content (prokaryote genome GC %, Madin et al.
2020) and sporulation (endospore formation, same source),
extending the prokaryote block; larval_nutrition (bee
larval food, EuPollTrait); colour_lightness (beetle body
greyness 0-255, saproxylic beetle traits, a melanism axis);
cell_surface_area (microalgae, um2, Rimet et al., alongside
cell_length/cell_width/cell_thickness/cell_biovolume);
carapace_length (turtle, mm, TurtleTraits); and
parental_care (fish Balon reproductive guild
guarder/non-guarder/bearer, Beukhof et al. 2019). Verified end-to-end
(Thermus aquaticus GC 67%, Bacillus subtilis sporulates, leatherback
carapace 2.26 m, stickleback a guarder).
add_trait("fruit_type") also gains AusTraits as a third
plant source.add_trait() traits, each grounded on the
source’s own values before wiring: zooxanthellate (coral
symbiotic state, from the Coral Trait Database and the octocoral
dataset, which share the zooxanthellate/azooxanthellate vocabulary),
optimal_growth_ph (prokaryote, from Madin et al. 2020, the
pH companion to optimal_growth_temperature), and
cell_thickness (microalgae, from Rimet et al., alongside
the existing
cell_length/cell_width/cell_biovolume).add_trait("diet_guild") now also draws on EltonTraits
(Wilman et al. 2014), extending diet guilds from birds and reptiles to
mammals. The guild is derived from the ten EltonTraits diet fractions
(built into elton_traits.vtr) and agrees 93% with
EltonTraits’ own diet classification and 83% with AVONET.
add_elton_traits() exposes the same diet_guild
column directly.add_trait("ellenberg_salt") gains Baseflor as a third
source: its salinity column is on the same 0-9 Ellenberg scale as
FloraWeb and Ecoflora (Pearson r = 0.88 on shared species), so it joins
them without rescaling.add_trait() traits egg_length and
egg_width (mm) gather reptile, bird, and turtle egg
dimensions from the Amniote database, ReptTraits, and TurtleTraits,
which agree to within measurement noise on shared species.add_trait("brain_mass") (g) coalesces COMBINE with
AnimalTraits (kg converted to grams), calibrated 1:1 on shared
species.reproductive_frequency now spans mammals through reptiles
and turtles (AnAge, PanTHERIA, ReptTraits, TurtleTraits added);
clutch_litter_size gains turtles (TurtleTraits) and birds
(Birdbase); age_at_maturity gains turtles and fish
(TurtleTraits, Beukhof); and longevity gains fish (Beukhof,
whose ~390 yr maximum is the Greenland shark).add_trait("pollination_vector") gains FloraWeb and
AusTraits, which agree 82-91% with the existing Baseflor and Ecoflora
sources on shared species. Named insect taxa (bee, beetle, fly, …)
resolve to insect; AusTraits’ coarse
biotic/abiotic and animal (bird, bat) records
have no single vector in this vocabulary and stay NA rather
than being guessed.add_trait() traits, each numeric source
shared-species calibrated (ratio ~1.00) against a co-registered source
before it was added: male_maturity (yr; AnAge, Amniote,
COMBINE – the male analogue of age_at_maturity),
incubation_period (days; Amniote, TurtleTraits egg
incubation, kept separate from the combined
gestation_incubation), diet_breadth (count of
dietary categories; COMBINE, PanTHERIA, Birdbase),
tongue_length (mm; Ostwald, EuPollTrait bee proboscis),
aspect_ratio (caudal-fin aspect ratio; Beukhof, Quimbayo),
and foraging_mode (active/ambush/mixed; ReptTraits,
TurtleTraits).add_trait("diet_guild") gains TurtleTraits and
Blanchard ant diets, mapped to the guild vocabulary by ordered regex
(compound “omnivorous to carnivorous” resolves to its primary guild; ant
“predator” to carnivore).add_trait() traits:
reproductive_mode (oviparous/ovoviviparous/ viviparous;
ReptTraits plus Sharkipedia, whose shark strategies collapse to
viviparous); the coral-habitat traits coloniality,
wave_exposure, and water_clarity (Coral Trait
DB and octocoral, sharing one vocabulary); and
head_length/head_width (mm; amphibian and
beetle morphometrics). The depth traits
depth_min/depth_max gain coral
occurrence-depth limits (Coral Trait DB, octocoral) in the same metres
unit as the fish sources.add_trait() traits, including a new
prokaryote domain from Madin et al. (2020): gram_stain,
oxygen_metabolism, cell_shape,
optimal_growth_temperature (deg C), and
genome_size (bp). Also caudal_fin_shape
(Beukhof + Quimbayo fish fin shape), voltinism (generations
per year; Arthropod Traits + EuPollTrait), migration
(AVONET), flightless (BIRDBASE), venomous
(ReptTraits), and sociality (EuPollTrait bees).
thermal_max gains Pottier amphibian CTmax on the same
degrees-C scale.add_trait() traits: wingspan
(mm; LepTraits butterflies, whose source column is labelled mm but is
actually cm, corrected on the known wingspans of monarch, cabbage white,
and swallowtail); leaf_length and leaf_width
(mm; AusTraits); fungal_trophic_mode (FUNGuild and
FungalTraits); feeding_mode and mouth_position
(fish; Beukhof, Quimbayo); air_breathing (FishBase);
motility (prokaryote; Madin); and lecty (bee
pollen host breadth; EuPollTrait).content_id (an md5 of
the built .vtr); a static cache is reconciled against it
entirely offline, re-downloading only when the bytes actually changed. A
pre-existing cache with no stored id is hashed in place, so an unchanged
asset is adopted without a download. Fixes stale
add_nesttrait() nest-modality columns and
add_disperse() bin-midpoint columns for anyone who cached
those before the rebuild. Every enrichment asset now carries a content
id, and the same gate is extended to backbones (a content id catches a
same-tag republish that a version bump would miss). The read-only
example database and its offline fixtures are never touched.add_trait() now joins genus-keyed sources on
genus: the ant-diet contribution to diet_guild
(Blanchard) was silently all-NA, and fungal_trophic_mode’s
FungalTraits source likewise. A registry guard test now asserts every
genus-keyed source is joined correctly.add_trait() attaches a single trait across every
source that carries it, reconciling their vocabularies and units. Where
each add_*() door joins one dataset,
add_trait("seed_mass") gathers the sources: it pulls seed
mass from Diaz et al. and GIFT and returns both in one unit (mg),
woodiness from Zanne and GIFT in one vocabulary, and likewise plant
height and SLA. The default mode = "coalesce" adds one
value per row with the columns that document it –
seed_mass, seed_mass_unit,
seed_mass_sources, and seed_mass_n – which
keeps chained calls tidy; mode = "wide" instead gives one
harmonized column per source (seed_mass_diaz,
seed_mass_gift) to inspect agreement and conflict. When
sources measure a trait by different methods (for example maximum vs
fine-root diameter), the value is not blended: the most complete source
is reported and a seed_mass_caution column explains the
difference. list_traits() lists the available traits and
trait_info() shows a trait’s sources, units, harmonization
notes, and cautions. The registry ships dozens of traits spanning plant
functional and root traits, animal body size, life history and
morphology, diel activity, thermal limits, phenology, indicator values,
and conservation status, each with a crosswalk grounded on the source
values rather than assumed.Enrichment doors are named after their source; the trait name is
reserved for add_trait(). add_woodiness(),
add_conservation_status(),
add_invasive_status(), and add_fish_traits()
are renamed to add_zanne() (Zanne et al. 2014),
add_iucn() (IUCN Red List), add_griis()
(GRIIS), and add_fishmorph() (FISHMORPH; also avoids
confusion with add_fishbase()). The old names are removed,
not deprecated – they never appeared in a release.
New add_gift() joins plant traits from GIFT, the
Global Inventory of Floras and Traits (Weigelt et al. 2020), by accepted
name. GIFT’s API exposes only the subset of its data it may redistribute
(CC BY 4.0; restricted references excluded); taxifydb fetches that
subset once at build time and it ships as a pre-built .vtr,
so add_gift() joins it offline like every other enrichment
– no runtime API calls. Choose which traits to attach via
cols= (any gift_ column names, or
"all"); the default is a convenient set of well-populated
ones (woodiness, growth form, life cycle and form, habit flags, height,
photosynthetic pathway, seed mass, dispersal, flowering months,
deciduousness, SLA). gift_traits() browses the available
columns.
reptiledb backend: the Reptile Database (Uetz et
al.), the global taxonomic reference for reptiles (snakes, lizards,
amphisbaenians, turtles, crocodiles and the tuatara). It carries ~12.6k
accepted species plus ~34k synonyms with full genus/family
classification, filling the one vertebrate class the other backbones
cover only partially. Use it like any backbone:
taxify(x, backend = "reptiledb"). License: CC-BY 4.0.add_repttraits() joins species-level reptile traits
from ReptTraits (Oskyrko et al. 2024) by accepted name. Beyond body-size
and life-history traits, it carries a per-species distribution signal –
biogeographic realm, elevation range and mean climate – across all
reptiles. This replaces the earlier add_lizard_traits(),
which drew on the same ReptTraits source but was mislabelled (it covered
all reptiles, not lizards) and exposed only the morphology columns.
License: CC-BY 4.0.inspect() flags probable typos and other anomalies
in a name list and returns only the anomalous rows, each labelled with
what stands out and, where known, the name to use instead.
inspect() does not match names against backbones itself –
that is taxify()‘s job. On a character vector it runs the
checks that need no matching: unknown (the genus is not in
the genus register, the union of all 13 backbones’ genera, so no
backbone recognises it – a real “probably not a name”),
near_duplicate (a near-twin of a more frequent name in the
same list, computed from the list alone, so it catches typos in names no
backbone contains), and outlier_group (a name whose kingdom
group is a tiny minority of an otherwise coherent list – the lone animal
or fungus among plants). To also surface the match-based anomalies, opt
in with backbones = TRUE (matches against every installed
backbone, listed in the report header) or match yourself first and
inspect the result – taxify(x) |> inspect() – which adds
typo (fuzzy-corrected spelling), synonym
(outdated name), ambiguous (homonym), case,
and the geographic checks geographic (a species with no
WCVP record in a declared region/coords) and
out_of_range (no region declared, yet the species’ range
falls outside the list’s main TDWG continents; skipped for globally
spread lists). Rows are ordered most-notable first and carry a
suggestion; each gets a tier describing what
it needs, not how bad it is: unresolved (no usable name),
review (a name is there but its identity is uncertain), or
note (correct, optional cleanup) – an anomaly may be
intended. inspect() is read-only: it never alters the input
or applies a correction. Narrow with min_tier. The
list-context labels cannot apply to a single name, so
inspect() on one name warns.taxify() gains a region argument for
geographically constrained fuzzy matching. Pass TDWG botanical regions
to restrict fuzzy candidates to species with WCVP
records in those regions; exact matches are always kept.
region accepts Level 3 codes (region = "BGM")
or region names at any level, matched case- and accent-insensitively
against a bundled WGSRPD crosswalk: a botanical country
("Belgium"), a Level 2 region
("Middle Europe"), or a Level 1 continent
("Europe", expanded to all its codes). The new
coords argument takes a c(lon, lat) pair or a
matrix/data.frame of coordinates and maps them to regions by
point-in-polygon against the WGSRPD Level 3 boundaries (downloaded and
cached on first use); region and coords are
unioned. coords also accepts an
sf/sfc object or a terra
SpatVector of points (reprojected automatically). The
point-in- polygon test uses terra or sf when
installed and falls back to a native implementation otherwise; the
engine can be forced with
options(taxify.pip_engine = "terra" | "sf" | "native"). The
filter only narrows genuinely ambiguous fuzzy candidates – a candidate
is dropped only when the same input name has another candidate that is
in-region or has no WCVP range data – so non-plant matches are never
affected and a name whose only candidate is out-of-region is still
returned. The companion range argument selects which WCVP
statuses count as in-region: "present" (default, any
record), "native", or "introduced".taxify_regions() lists the WGSRPD Level 3 botanical
regions (codes and names) used by region and by
add_wcvp(), with an optional search term."fishbase" (FishBase, ~36k
accepted fish species) and "sealifebase" (SeaLifeBase,
~100k accepted non-fish aquatic species). Both resolve synonyms to their
accepted names and carry kingdom / phylum / class / order
classification. Use them like any other backbone, e.g.
taxify("Gadus morhua", backend = "fishbase").add_sealifebase() joins SeaLifeBase morphological and
ecological traits (body length, mass, trophic level, depth range,
vulnerability, habitat, commercial importance) to a
taxify() result. It is the non-fish companion to
add_fishbase().add_groot() joins species-level root traits from the
Global Root Traits (GRooT) database: root diameter, specific root
length, tissue density, N and C concentration, root mass fraction,
lateral spread, mycorrhizal colonization and rooting depth (per-species
means for 6,154 vascular plant species).add_qualifier_info() has been removed.
taxify() now reports the qualifier natively (see New
features), so a separate parsing pass is no longer needed. Replace
taxify(x) |> add_qualifier_info() with
taxify(x). Note the integer qualifier_position
(a character index) is replaced by a two-value "genus" /
"species" placement.taxify() gains an aggregates argument, default
"preserve": an aggregate name ("... agg.",
"... s.l.") matches the backbone’s aggregate taxon where
one exists (for example in Euro+Med and WoRMS), otherwise it falls back
to the binomial species. aggregates = "collapse" keeps the
previous behaviour of stripping the marker and matching the
binomial.taxify() output carries two new columns.
qualifier is the canonical taxonomic qualifier with
spelling variants folded to one token ("aggr.",
"agg" and "sensu lato" map to
"agg." / "s.l.").
qualifier_position is "genus" for a leading
prefix ("Cf. Pinus sylvestris") and "species"
for an inline or trailing qualifier
("Pinus cf. sylvestris",
"Rubus fruticosus agg.")."... aggr."), and an aggregate query reaches
the aggregate-level trait. A single species’ trait is never propagated
up to the aggregate. Set
options(taxify.trait_provenance = TRUE) to add a
<enrichment>_inherited flag marking the inherited
values.normalize_aggregate_name() and
is_aggregate_name() (build-time helpers) so the taxifydb
build pipeline folds every backbone and enrichment aggregate marker
(agg, aggr., -agg,
s.l., sensu lato, coll., and
aggregate ranks such as SPECIES AGGREGATE) to one canonical
aggr. form. The runtime and build sides therefore recognize
aggregates uniformly across all backbones.summary() now counts abbreviated-genus matches
(match_type == "abbrev", e.g. "Q. robur").
Previously these were resolved correctly in the result but omitted from
the matched total and its breakdown, so the digest
under-reported the number of matched names. The matched
line now reads (exact, case-insensitive, fuzzy, abbrev),
and match_tally carries an abbrev count.add_fungalroot()
(genus-level mycorrhizal type), including the genus-keyed join and the
type vocabulary, and stacks it into the European and global
vascular-plant guidance.add_fungalroot() joins genus-level mycorrhizal type
from the FungalRoot database (Soudzilovskaia et al. 2020, GBIF
doi:10.15468/a7ujmj, CC BY-NC 4.0) to a taxify() result.
Because mycorrhizal type is conserved at the genus level, the join is on
genus, so any species in a covered genus is annotated with
mycorrhizal_type (AM, EcM,
ErM, OM, NM, the dual types,
Other, or uncertain),
mycorrhizal_status, and the supporting record count. Plant
genera only.Cf. prefix
(e.g. "Cf. Pinus sylvestris") is now recorded as the
cf. qualifier by clean_names(),
clean_one(), and add_qualifier_info().
Previously the prefix was stripped before matching but the qualifier was
lost, so only inline cf.
(e.g. "Pinus cf. sylvestris") was reported.
add_qualifier_info() now also matches the prefix
case-insensitively and reports qualifier_position = 1.taxify_data_dir() can now be redirected with the
taxify.data_dir option or the TAXIFY_DATA_DIR
environment variable, so the cache location is configurable (shared
caches, scratch directories, the bundled example data).taxify_example_data() returns the path to a small
bundled example database (a handful of species per backbone plus
matching enrichment tables). Setting
options(taxify.data_dir = taxify_example_data()) lets
matching and enrichment run fully offline.\dontrun{}. Only
add_pignatti() (fetched live via TR8) and
list_enrichments() (reads the online manifest) remain in
\donttest{}.add_floraweb() joins German-flora plant traits from
FloraWeb (the live BfN portal carrying the BiolFlor data of Klotz, Kuehn
& Durka 2002, plus Rothmaler morphology and Ellenberg indicator
values). It bundles the full per-species trait profile – morphology,
reproductive biology, the nine Ellenberg indicator values, ploidy and
chromosome number, and chorological distribution (59 _de
columns) – as a pre-built dataset, so it works offline.add_ecoflora() now joins a bundled, pre-built
Ecoflora dataset (18 _uk columns: canopy height, leaf
traits, life form, flowering phenology, pollination, seed weight, and
British-calibrated Ellenberg values) instead of fetching live through
TR8. It works offline and returns the full trait set rather than the
previous five columns.
add_pignatti() remains an on-demand TR8 source: its
values are from a copyrighted publication and cannot be
redistributed.
add_ecoflora(), add_biolflor(), and
add_pignatti() join plant traits that taxify does not ship
as a pre-built dataset, accessing them on demand through the suggested
TR8 package on your own machine; taxify redistributes nothing. The
reasons differ by source: add_ecoflora() adds British
flowering months, pollen vector, life form, and leaf longevity (CC
BY-NC-SA, which would allow redistribution, but ecoflora.org.uk has no
bulk download, so it is fetched live per species);
add_biolflor() adds Grime CSR strategy type, breeding
system, pollen vector, life form, life span, and apomixis (usable with
acknowledgement + citation per the BioFresh metadata statement, but no
bulk copy is obtainable while the UFZ site is offline, so fetched live);
add_pignatti() adds Italian Ellenberg-type indicator
values, life form, and chorotype (copyrighted; read from the copy
bundled in TR8, which TR8 redistributes, not taxify; works offline).
Columns are region-suffixed
(_uk/_de/_it) so they never
collide with add_baseflor(). TR8 is a Suggests dependency.
If a live source (Ecoflora, BiolFlor) is unreachable the call errors
rather than attaching silent NA.add_baseflor() joins plant traits from Baseflor
(Programme Catminat, Julve 1998 ff.; ODbL 1.0 / CC BY-SA 2.0) to a
taxify() result. It covers ~7,000 vascular plant taxa of
France and neighbouring regions and adds flowering phenology
(flower_begin_month, flower_end_month),
pollination vector, dispersal mode, breeding system, flower colour,
fruit type, woody growth form, and the continentality and salinity
indicator-value axes absent from EIVE. The enrichment is registered in
the manifest (list_enrichments()) with a pre-built
.vtr; light/temperature/moisture/reaction/nutrient axes are
left to add_eive() and Raunkiaer life form to
add_leda().tests/e2e/test-e2e-enrichment.R) for the enrichment join
fixed in 0.2.5 (#1). It checks that
add_conservation_status(), add_common_names(),
and add_woodiness() attach each value to the row’s own
accepted taxon, stay invariant to batch composition and order, and land
documented values on the correct species."Q. robur" now resolve.
A matching pass restricts the backbone to rows whose genus starts with
the given initial and whose specific epithet matches, resolving only
when that is unique. When two or more genera sharing the initial also
share the epithet the abbreviation is ambiguous: the row is left
unmatched with is_ambiguous = TRUE and the conflicting
accepted IDs in ambiguous_targets, rather than guessing a
genus. A genus spelled out in full elsewhere in the same input takes
precedence (the convention of abbreviating after first mention).
Resolved rows carry match_type = "abbrev".accepted_authorship output column: the authorship
of the resolved accepted name. For a synonym match,
authorship holds the synonym’s own author while
accepted_authorship holds the accepted name’s author, so
accepted_name and accepted_authorship together
form the accepted taxon’s full citation. Backbones that carry authorship
populate it; sources without authorship (NCBI, OTT) return
NA.taxify() no longer errors with “replacement has length
zero” for backbones whose .meta sidecar records the build
date as build_date (the current taxifydb build format)
rather than download_date. Backbone metadata now reads both
layouts and version formatting tolerates a missing date. This previously
broke matching against the WoRMS and Open Tree of Life backbones.Additional_repositories (https://gcol33.r-universe.dev), so
its location is discoverable as required for a Suggests dependency
outside the mainstream repositories.taxify() no longer errors with “incorrect number of
dimensions” when the genus register is present but the backend-coverage
file is not (the state on a clean install before any coverage download,
and during package checks). An early return() evaluated
inside a tryCatch() expression returned NULL
from the pre-filter, which $<- then turned into a list;
the out-of-scope pre-filter now resolves missing coverage to a no-op and
preserves the result data frame.
Replaced non-ASCII characters in roxygen documentation with ASCII equivalents so the PDF reference manual builds under LaTeX.
Ambiguous homonym synonyms now resolve to the epithet-preserving
accepted name (the homotypic basionym) instead of an arbitrary lowest-id
candidate. taxify("Pinus abies") resolves to Picea
abies (not Picea polita), and the spurious
is_ambiguous flag is cleared when one candidate keeps the
specific epithet (#2). Genuinely ambiguous names (no candidate, or
several, preserving the epithet) are still flagged.
Silenced tidyselect deprecation warnings emitted during fuzzy matching.
score_candidates() is exported (kept internal in the
reference index) so the companion taxifydb build pipeline
can collapse each backbone key to the single accepted name
taxify() resolves it to. This corrects enrichment joins
that previously landed trait/status values on within-genus neighbours
(#1); the fix reaches users through rebuilt enrichment data.