Package {taxify}

Title:	Offline Taxonomic Name Matching Against Local Darwin Core Snapshots
Version:	0.3.4
Description:	Match taxonomic names against locally stored Darwin Core backbone databases ('WFO', 'COL', 'GBIF', 'ITIS', 'NCBI Taxonomy', 'Open Tree of Life', 'WoRMS', 'Euro+Med', 'Species Fungorum', 'AlgaeBase', 'FishBase', 'SeaLifeBase', 'Reptile Database'). Provides offline fuzzy and exact matching with synonym resolution, hybrid name detection, and a unified output schema across all sources. All heavy computation runs in the 'vectra' C11 columnar engine.
License:	MIT + file LICENSE
URL:	https://gillescolling.com/taxify/, https://github.com/gcol33/taxify
BugReports:	https://github.com/gcol33/taxify/issues
Additional_repositories:	https://gcol33.r-universe.dev
Depends:	R (≥ 4.1.0)
Imports:	curl, jsonlite, rlang, vectra
Suggests:	DBI, GIFT, knitr, openxlsx2, rmarkdown, RSQLite, sf, taxifydb, terra, testthat (≥ 3.0.0), TR8, withr
VignetteBuilder:	knitr
Config/testthat/edition:	3
Encoding:	UTF-8
Config/roxygen2/version:	8.0.0
NeedsCompilation:	no
Packaged:	2026-07-08 23:20:16 UTC; Gilles Colling
Author:	Gilles Colling [aut, cre, cph]
Maintainer:	Gilles Colling <gilles.colling051@gmail.com>
Repository:	CRAN
Date/Publication:	2026-07-09 08:50:02 UTC

taxify: Offline Taxonomic Name Matching Against Local Darwin Core Snapshots

Description

Match taxonomic names against locally stored Darwin Core backbone databases ('WFO', 'COL', 'GBIF', 'ITIS', 'NCBI Taxonomy', 'Open Tree of Life', 'WoRMS', 'Euro+Med', 'Species Fungorum', 'AlgaeBase', 'FishBase', 'SeaLifeBase', 'Reptile Database'). Provides offline fuzzy and exact matching with synonym resolution, hybrid name detection, and a unified output schema across all sources. All heavy computation runs in the 'vectra' C11 columnar engine.

Author(s)

Maintainer: Gilles Colling gilles.colling051@gmail.com (ORCID) [copyright holder]

Authors:

• Gilles Colling gilles.colling051@gmail.com (ORCID) [copyright holder]

See Also

Useful links:

• https://github.com/gcol33/taxify

• Report bugs at https://github.com/gcol33/taxify/issues

Add macroalgal functional traits (AlgaeTraits)

Description

Joins AlgaeTraits (Vranken et al. 2023) macroalgal functional traits to a taxify() result by looking up accepted_name. AlgaeTraits provides morphological, ecological, and life-history traits for European seaweeds.

Usage

add_algae_traits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: AlgaeTraits (Vranken et al. 2023, VLIZ Marine Data Archive, CC BY 4.0). Coverage: ~1,745 European macroalgae species.

Value

The same data.frame with additional columns:

algae_body_size_cm

Maximum body size in centimetres.

algae_growth_form

Growth form / body shape (e.g., filamentous, foliose, crustose).

algae_calcification

Calcification type (e.g., uncalcified, articulated, encrusting).

algae_life_span

Life span category (annual, perennial, etc.).

algae_tidal_zone

Tidal zonation (e.g., supralittoral, eulittoral, sublittoral).

algae_wave_exposure

Wave exposure tolerance (sheltered, moderately exposed, exposed).

algae_environment

Habitat environment (marine, brackish, freshwater).

algae_substrate

Environmental position / substrate type.

References

Vranken S et al. (2023) AlgaeTraits: a trait database for (European) seaweeds. Earth System Science Data 15:2711-2754. doi:10.5194/essd-15-2711-2023

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Fucus vesiculosus", backend = "gbif") |>
  add_algae_traits()

options(old)

Add alien species first record years

Description

Joins alien species first record data to a taxify() result, filtered by country. Data from the Global Alien Species First Record Database (Seebens et al. 2017).

Usage

add_alien_first_records(x, country, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Global Alien Species First Record Database v3.1 (Seebens et al. 2017, Nature Communications 8, 14435). CC BY 4.0. Coverage: ~77k species x country combinations across all taxa.

Value

The same data.frame with additional column(s):

alien_first_record

Year of the first record (integer), or NA if not recorded for that country.

alien_first_record_source

Database that contributed the record (e.g., "GAVIA", "CABI ISC").

alien_first_record_reference

Original citation or reference for the record.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Robinia pseudoacacia") |>
  add_alien_first_records(country = "AT")

taxify(c("Robinia pseudoacacia", "Ailanthus altissima")) |>
  add_alien_first_records(country = c("AT", "DE"))

options(old)

Add amniote life-history traits (Amniote Life History Database)

Description

Joins uniform life-history traits for birds, mammals and reptiles to a taxify() result by looking up accepted_name.

Usage

add_amniote(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Amniote Life History Database (Myhrvold et al. 2015, Ecology, CC0). Coverage: 21,322 species across birds, mammals and reptiles.

Value

The same data.frame with additional columns:

amniote_class

Taxonomic class (Aves/Mammalia/Reptilia).

amniote_adult_body_mass_g

Adult body mass (g).

amniote_no_sex_body_mass_g

Unsexed adult body mass (g).

amniote_female_body_mass_g

Female body mass (g).

amniote_male_body_mass_g

Male body mass (g).

amniote_adult_svl_cm

Adult snout-vent length (cm).

amniote_maximum_longevity_y

Maximum longevity (years).

amniote_litter_clutch_size

Litter or clutch size (count).

amniote_clutches_per_y

Litters or clutches per year (count).

amniote_egg_mass_g

Egg mass (g).

amniote_incubation_d

Incubation period (days).

amniote_female_maturity_d

Age at female maturity (days).

amniote_gestation_d

Gestation length (days).

amniote_weaning_d

Weaning age (days).

amniote_birth_hatching_wt_g

Birth or hatching weight (g).

References

Myhrvold NP et al. (2015) An amniote life-history database to perform comparative analyses with birds, mammals, and reptiles. Ecology 96:3109. doi:10.1890/15-0846R.1

Examples

taxify("Accipiter badius", backend = "gbif") |>
  add_amniote()

Add amphibian life-history traits (AmphiBIO)

Description

Joins AmphiBIO amphibian life-history and ecological traits to a taxify() result by looking up accepted_name.

Usage

add_amphibio(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: AmphiBIO (Oliveira et al. 2017, CC BY 4.0). Coverage: ~6,800 amphibian species. Amphibians only.

Value

The same data.frame with additional columns:

body_size_mm

Maximum body size in mm (snout-vent length).

age_maturity_y

Age at maturity in years.

longevity_yr

Maximum longevity in years.

litter_size

Clutch/litter size.

reproductive_output

Reproductive output per year.

offspring_size_mm

Offspring size in mm.

direct_development

Direct development (0/1).

larval

Has larval stage (0/1).

aquatic

Aquatic habitat (0/1).

fossorial

Fossorial habitat (0/1).

arboreal

Arboreal habitat (0/1).

diurnal

Diurnal activity (0/1).

nocturnal_amphibio

Nocturnal activity (0/1). Named nocturnal_amphibio to avoid collision with EltonTraits' nocturnal column.

References

Oliveira BF, Sao-Pedro VA, Santos-Barrera G, Penone C, Costa GC (2017) AmphiBIO, a global database for amphibian ecological traits. Scientific Data 4:170123.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Bufo bufo", backend = "gbif") |>
  add_amphibio()

options(old)

Add longevity and life-history traits (AnAge)

Description

Joins AnAge (Animal Ageing and Longevity Database) traits to a taxify() result by looking up accepted_name.

Usage

add_anage(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: AnAge (de Magalhaes & Costa 2009, CC BY). Coverage: ~4.7k vertebrate species (mammals, birds, reptiles, amphibians, fish).

Value

The same data.frame with additional columns:

max_longevity_yr

Maximum longevity in years.

anage_body_mass_g

Adult body mass in grams.

metabolic_rate_w

Basal metabolic rate in watts.

female_maturity_d

Female age at sexual maturity in days.

male_maturity_d

Male age at sexual maturity in days.

gestation_incubation_d

Gestation or incubation length in days.

anage_litter_size

Litter or clutch size.

birth_mass_g

Mass at birth in grams.

growth_rate

Growth rate (1/days).

temperature_k

Body temperature in Kelvin.

References

de Magalhaes JP, Costa J (2009) A database of vertebrate longevity records and their relation to other life-history traits. Journal of Evolutionary Biology 22:1770-1774.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Vulpes vulpes", backend = "gbif") |>
  add_anage()

options(old)

Add cross-taxon body mass and metabolic rate (AnimalTraits)

Description

Joins AnimalTraits body mass and metabolic rate data to a taxify() result by looking up accepted_name.

Usage

add_animaltraits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: AnimalTraits (Hebert et al. 2022, CC0). Coverage: ~2k species across arthropods, vertebrates, molluscs, and annelids. Individual-level observations aggregated to species medians.

Value

The same data.frame with additional columns:

animaltraits_body_mass_kg

Median body mass in kg.

animaltraits_metabolic_rate_w

Median metabolic rate in watts.

References

Hebert K et al. (2022) AnimalTraits – a curated animal trait database for body mass, metabolic rate and brain size. Scientific Data 9:265.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Drosophila melanogaster", backend = "gbif") |>
  add_animaltraits()

options(old)

Add Arctic marine benthos traits

Description

Joins Arctic Traits Database functional traits to a taxify() result by accepted_name. Each fuzzy-coded trait is reduced to its dominant category.

Usage

add_arctic_traits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Arctic Traits Database (Degen & Faulwetter 2019, University of Vienna PHAIDRA, CC-BY 4.0).

Value

The same data.frame with categorical arctic_traits_ columns: feeding_habit, skeleton, reproduction, larval_development, size, living_habit, body_form, mobility, bioturbation, depth_range, trophic_level, fragility, sociability, longevity.

References

Degen R, Faulwetter S (2019) The Arctic Traits Database. University of Vienna. doi:10.25365/phaidra.49

Examples

taxify("Astarte borealis", backend = "gbif") |>
  add_arctic_traits()

Add arthropod life-history traits (NW European Arthropods)

Description

Joins the Northwestern European Arthropod Life Histories dataset to a taxify() result by looking up accepted_name.

Usage

add_arthropod_traits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Logghe et al. (2025, CC BY-NC). Coverage: ~4.9k arthropod species from NW Europe across 10 orders (Coleoptera, Hemiptera, Orthoptera, Araneae, Diptera, Hymenoptera, Lepidoptera, etc.).

Value

The same data.frame with additional columns:

arthropod_body_size_mm

Body size in mm.

arthropod_dispersal

Dispersal ability (0–1 ratio within order).

arthropod_voltinism

Mean number of generations per year.

arthropod_fecundity

Fecundity (number of eggs/offspring).

arthropod_development_d

Development time in days.

arthropod_lifespan_d

Adult lifespan in days.

arthropod_thermal_mean

Mean thermal niche (degrees C).

arthropod_diurnality

Activity period (diurnal/nocturnal/both).

arthropod_feeding_guild

Feeding guild of adult.

arthropod_trophic_range

Trophic range of adult (specialist/generalist).

References

Logghe A et al. (2025) An in-depth dataset of northwestern European arthropod life histories and ecological traits. Biodiversity Data Journal 13:e146785.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Abax parallelepipedus", backend = "gbif") |>
  add_arthropod_traits()

options(old)

Add Australian plant traits (AusTraits)

Description

Joins species-level plant functional traits to a taxify() result by looking up accepted_name. Values are aggregated from the long-format AusTraits database (numeric traits by median, categorical traits by mode).

Usage

add_austraits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: AusTraits (Falster et al. 2021, Scientific Data, CC BY 4.0). Coverage: ~33k Australian plant taxa.

Value

The same data.frame with additional columns:

austraits_plant_growth_form

Plant growth form.

austraits_life_history

Life history (annual/perennial/...).

austraits_woodiness

Woodiness.

austraits_photosynthetic_pathway

Photosynthetic pathway (C3/C4/CAM).

austraits_dispersal_syndrome

Dispersal syndrome.

austraits_resprouting_capacity

Resprouting capacity (fire response).

austraits_flowering_time

Flowering time.

austraits_plant_height_m

Plant height (m).

austraits_leaf_length_mm

Leaf length (mm).

austraits_leaf_width_mm

Leaf width (mm).

austraits_leaf_area_mm2

Leaf area (mm2).

austraits_leaf_mass_per_area

Leaf mass per area (g/m2; SLA is its reciprocal).

austraits_leaf_n_per_dry_mass

Leaf nitrogen per dry mass (mg/g).

austraits_leaf_p_per_dry_mass

Leaf phosphorus per dry mass (mg/g).

austraits_seed_dry_mass_mg

Seed dry mass (mg).

austraits_wood_density_g_cm3

Wood density (g/cm3).

References

Falster D et al. (2021) AusTraits, a curated plant trait database for the Australian flora. Scientific Data 8:254. doi:10.1038/s41597-021-01006-6

Examples

taxify("Eucalyptus globulus", backend = "gbif") |>
  add_austraits()

Add bird morphology and migration (AVONET)

Description

Joins AVONET species-level averages for bird morphology, ecology, and migration to a taxify() result by looking up accepted_name.

Usage

add_avonet(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: AVONET (Tobias et al. 2022, Figshare, CC BY 4.0). Coverage: ~11k bird species. Birds only.

Value

The same data.frame with additional columns:

beak_length

Beak length in mm (culmen, species mean).

beak_depth

Beak depth in mm (species mean).

wing_length

Wing length in mm (species mean).

tail_length

Tail length in mm (species mean).

tarsus_length

Tarsus length in mm (species mean).

avonet_body_mass_g

Body mass in grams (species mean).

hand_wing_index

Hand-wing index (pointedness, species mean).

habitat

Primary habitat classification.

trophic_level

Trophic level classification.

trophic_niche

Trophic niche classification.

migration

Migration strategy: "sedentary", "partial", or "full".

References

Tobias JA et al. (2022) AVONET: morphological, ecological and geographical data for all birds. Ecology Letters 25:581-597.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Parus major", backend = "gbif") |>
  add_avonet()

options(old)

Add bacterial and archaeal strain phenotypes (BacDive)

Description

Joins per-species microbial phenotype and growth-condition traits from BacDive, the Bacterial Diversity Metadatabase (DSMZ), to a taxify() result by looking up accepted_name. Strain-level records are aggregated to one row per species (categorical traits by mode, numeric by median); temperature and pH prefer the optimum measurement, falling back to the growth measurement.

Usage

add_bacdive(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: BacDive (Reimer et al.), DSMZ, CC BY 4.0. ~18.6k bacterial and archaeal species with at least one phenotypic trait.

Value

The same data.frame with additional columns:

gram_stain

Gram reaction (positive / negative / variable).

cell_shape

Cell morphology (rod, coccus, ...).

motility

motile / non-motile.

oxygen_metabolism

Oxygen tolerance (aerobe, anaerobe, facultative anaerobe, microaerophile, ...).

cell_length_um, cell_width_um

Cell dimensions in micrometres.

optimal_growth_temp_c

Optimal (or reported growth) temperature, C.

optimal_growth_ph

Optimal (or reported growth) pH.

References

Reimer LC et al. (2022) BacDive in 2022: the knowledge base for standardized bacterial and archaeal data. Nucleic Acids Research 50:D741-D746. doi:10.1093/nar/gkab961

Examples

taxify("Escherichia coli", backend = "gbif") |>
  add_bacdive()

Add plant traits from Baseflor (Catminat / Julve)

Description

Joins Baseflor (Julve, Programme Catminat) plant traits to a taxify() result by looking up accepted_name. Baseflor covers the vascular flora of France and neighbouring regions, providing flowering phenology, pollination and breeding biology, dispersal mode, and floral and fruit morphology.

Usage

add_baseflor(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Baseflor, Programme Catminat (Julve 1998 ff.). Coverage: ~7,000 vascular plant taxa of France and neighbouring regions. Data are released under ODbL 1.0 / CC BY-SA 2.0.

For ecological indicator values on the light, temperature, moisture, reaction, and nutrient axes, see add_eive() (European calibration). For Raunkiaer life form and seed, leaf, and clonality traits of the Northwest European flora, see add_leda().

Value

The same data.frame with additional columns:

flower_begin_month

First month of flowering (1-12).

flower_end_month

Last month of flowering (1-12). A value smaller than flower_begin_month denotes a flowering period that wraps across the new year (e.g. begin 10, end 6).

pollination_vector

Pollination vector(s): insect, wind, water, self, apogamy. Comma-separated when more than one applies.

dispersal_mode

Diaspore dispersal mode(s): anemochory, barochory, epizoochory, endozoochory, myrmecochory, hydrochory, autochory, dyszoochory. Comma-separated when more than one applies.

breeding_system

Sexual system: hermaphroditic, monoecious, dioecious, gynodioecious, androdioecious, gynomonoecious, polygamous.

flower_colour

Flower colour(s): white, yellow, pink, green, blue, brown, black. Comma-separated when more than one applies.

fruit_type

Fruit type: achene, capsule, caryopsis, drupe, legume, silique, berry, follicle, cone, samara, pyxid.

woody_growth_form

Woody growth form for woody taxa: tree, small tree, large tree, shrub, bush, subshrub, liana, parasite. NA for non-woody (herbaceous) taxa.

continentality

Ellenberg-style continentality indicator value (1-9), the axis absent from EIVE.

salinity

Ellenberg-style salinity indicator value (0-9), the axis absent from EIVE.

References

Julve, Ph. (1998 ff.) baseflor. Index botanique, ecologique et chorologique de la Flore de France. Programme Catminat.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Bellis perennis") |>
  add_baseflor()

options(old)

Add bee morphometrics (Ostwald)

Description

Joins global bee morphological traits to a taxify() result by accepted_name. Long-format measurements are reduced to species medians.

Usage

add_bee_ostwald(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Ostwald et al. global bee morphology (Zenodo, CC-BY 4.0).

Value

The same data.frame with numeric columns bee_ostwald_itd_mm (intertegular distance), bee_ostwald_forewing_length_mm, bee_ostwald_tongue_length_mm, bee_ostwald_tongue_width_mm, bee_ostwald_body_length_mm, bee_ostwald_thorax_length_mm, bee_ostwald_hair_length_mm, bee_ostwald_hair_coverage_pct.

References

Ostwald MM et al. (2024) A global database of bee morphological traits. Zenodo. doi:10.5281/zenodo.13366989

Examples

taxify("Apis mellifera", backend = "gbif") |>
  add_bee_ostwald()

Add bryophyte traits (Bryophytes of Europe Traits)

Description

Joins species-level bryophyte traits to a taxify() result by looking up accepted_name.

Usage

add_bet(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Bryophytes of Europe Traits (van Zuijlen et al. 2023, EnviDat, CC BY-SA 4.0). Coverage: ~1.8k bryophyte species.

Value

The same data.frame with additional columns:

bet_growth_form

Growth form (acrocarpous/pleurocarpous/thalloid/...).

bet_life_form

Life form (cushion/mat/turf/weft/...).

bet_life_strategy

Life strategy (During).

bet_sexual_condition

Sexual condition (monoicous/dioicous).

bet_shoot_size_mm

Mean shoot size (mm).

bet_generation_length_y

Generation length (years).

bet_spore_diameter_um

Mean spore diameter (micrometres).

bet_ind_light

Ellenberg light indicator value.

bet_ind_temperature

Ellenberg temperature indicator value.

bet_ind_moisture

Ellenberg moisture indicator value.

bet_ind_reaction_ph

Ellenberg reaction (pH) indicator value.

bet_ind_nitrogen

Ellenberg nitrogen indicator value.

bet_substrate_soil

Occurs on soil (0/1).

bet_substrate_rock

Occurs on rock (0/1).

bet_substrate_bark

Occurs on bark (0/1).

bet_substrate_deadwood

Occurs on deadwood (0/1).

bet_epiphyte

Epiphytic (0/1).

bet_redlist_category

IUCN European Red List category.

References

van Zuijlen K et al. (2023) Bryophytes of Europe Traits (BET): a fundamental dataset for European bryophyte ecology. EnviDat. doi:10.16904/envidat.348

Examples

taxify("Abietinella abietina", backend = "gbif") |>
  add_bet()

Add marine fish traits (Beukhof)

Description

Joins North Atlantic / NE Pacific shelf marine-fish life-history and ecology traits to a taxify() result by accepted_name (species-level summaries).

Usage

add_beukhof(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Beukhof et al. (2019) marine fish trait collection (PANGAEA, CC-BY 4.0).

Value

The same data.frame with beukhof_ columns: numeric trophic_level, aspect_ratio, offspring_size, age_maturity, fecundity, length_infinity_cm, growth_coefficient, length_max_cm; categorical habitat, feeding_mode, body_shape, fin_shape, spawning_type.

References

Beukhof E et al. (2019) A trait collection of marine fish species from North Atlantic and Northeast Pacific continental shelf seas. PANGAEA. doi:10.1594/PANGAEA.900866

Examples

taxify("Gadus morhua", backend = "gbif") |>
  add_beukhof()

Add plant traits (BIEN)

Description

Joins BIEN plant functional traits to a taxify() result by looking up accepted_name. Values are species-level aggregates of public-access BIEN records (numeric by median, categorical by mode).

Usage

add_bien(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: BIEN (Botanical Information and Ecology Network; Maitner et al. 2018, Methods Ecol Evol, CC BY). Coverage: tens of thousands of vascular plant species.

Value

The same data.frame with additional columns:

bien_plant_height_m

Whole-plant height (m).

bien_max_plant_height_m

Maximum whole-plant height (m).

bien_dbh_cm

Diameter at breast height (cm).

bien_sla_mm2_mg

Leaf area per leaf dry mass (SLA).

bien_leaf_area_mm2

Leaf area.

bien_leaf_dry_mass_mg

Leaf dry mass.

bien_leaf_n_per_dry_mass

Leaf nitrogen per dry mass.

bien_leaf_p_per_dry_mass

Leaf phosphorus per dry mass.

bien_leaf_thickness_mm

Leaf thickness.

bien_seed_mass_mg

Seed mass.

bien_wood_density_g_cm3

Stem wood density (g/cm3).

bien_leaf_lifespan

Leaf life span.

bien_growth_form

Whole-plant growth form.

bien_woodiness

Whole-plant woodiness.

bien_dispersal_syndrome

Whole-plant dispersal syndrome.

bien_flower_color

Flower colour.

References

Maitner BS et al. (2018) The BIEN R package: A tool to access the Botanical Information and Ecology Network (BIEN) database. Methods in Ecology and Evolution 9:373-379. doi:10.1111/2041-210X.12861

Examples

taxify("Quercus alba", backend = "gbif") |>
  add_bien()

Add bird traits (BIRDBASE)

Description

Joins BIRDBASE biogeography, conservation and life-history traits to a taxify() result by looking up accepted_name. Traits redundant with add_avonet() morphology are not carried.

Usage

add_birdbase(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: BIRDBASE (Sekercioglu et al. 2025, figshare, CC BY 4.0). Coverage: ~11.6k bird species.

Value

The same data.frame with additional columns:

birdbase_iucn_status

IUCN Red List category.

birdbase_realm

Biogeographic realm.

birdbase_latitudinal_zone

Latitudinal zone (1 tropical to 5).

birdbase_island_endemic

Island-restricted breeding (0/1).

birdbase_restricted_range

Restricted-range species (0/1).

birdbase_elevation_min_m

Lower elevation limit (m).

birdbase_elevation_max_m

Upper elevation limit (m).

birdbase_elevation_range_m

Elevational breadth (m).

birdbase_primary_habitat

Primary habitat.

birdbase_habitat_breadth

Habitat breadth (number of habitats).

birdbase_primary_diet

Primary diet.

birdbase_diet_breadth

Diet breadth (number of food types).

birdbase_specialization_esi

Ecological specialization index.

birdbase_clutch_min

Minimum clutch size (eggs).

birdbase_clutch_max

Maximum clutch size (eggs).

birdbase_nest_type

Nest architecture.

birdbase_flightlessness

Volancy (yes/no/partial).

References

Sekercioglu CH et al. (2025) BIRDBASE: a global database of bird ecological and life-history traits. Scientific Data. doi:10.1038/s41597-025-05615-3

Examples

taxify("Struthio camelus", backend = "gbif") |>
  add_birdbase()

Add ant genus defensive traits (Blanchard & Moreau)

Description

Joins genus-level ant defensive and ecological traits to a taxify() result by genus.

Usage

add_blanchard(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Blanchard & Moreau (2017) ant defensive traits (Dryad, CC0). Joins on genus because the database is genus-resolved.

Value

The same data.frame with blanchard_ columns: categorical subfamily, spines, sting, diet, nesting, foraging; numeric colony_size_workers (joined on genus).

References

Blanchard BD, Moreau CS (2017) Defensive traits in the ant genera database. Dryad. doi:10.5061/dryad.st6sc

Examples

taxify("Camponotus pennsylvanicus", backend = "gbif") |>
  add_blanchard()

Add Mediterranean plant traits (BROT 2.0)

Description

Joins Mediterranean-Basin plant fire-response, regeneration and functional traits to a taxify() result by accepted_name.

Usage

add_brot(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: BROT 2.0 (Tavsanoglu & Pausas 2018, Scientific Data, CC-BY 4.0).

Value

The same data.frame with brot_ columns: numeric seed_mass_mg, sla_mm2_mg, height_m, leaf_area_mm2; categorical resp_fire, growth_form, disp_mode, fruit_type, soil_seed_bank, seedling_emergence.

References

Tavsanoglu C, Pausas JG (2018) A functional trait database for Mediterranean Basin plants (BROT 2.0). Scientific Data 5:180135. doi:10.6084/m9.figshare.c.3843841

Examples

taxify("Quercus coccifera", backend = "gbif") |>
  add_brot()

Add turtle traits (CheloniansTraits)

Description

Joins species-level turtle and tortoise traits to a taxify() result by looking up accepted_name.

Usage

add_chelonians(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: CheloniansTraits (Wang et al. 2025, figshare, CC BY 4.0). Coverage: 358 turtle and tortoise species. Numeric values reported as "min-max" ranges in the source are reduced to their midpoint.

Value

The same data.frame with additional columns:

chelonian_carapace_length_mm

Maximum straight-line carapace length (mm).

chelonian_max_mass_g

Maximum body mass (g).

chelonian_clutch_size_mean

Mean clutch size (count).

chelonian_clutch_size_max

Maximum clutch size (count).

chelonian_clutches_per_year

Clutches per year (count).

chelonian_incubation_d

Incubation period (days).

chelonian_age_maturity_y

Age at sexual maturity (years).

chelonian_max_lifespan_y

Maximum lifespan (years).

chelonian_range_size_km2

Range size (km2).

chelonian_diet

Diet (herbivorous/carnivorous/omnivorous).

chelonian_activity_time

Activity time.

chelonian_microhabitat

Microhabitat (aquatic/terrestrial/...).

chelonian_habitat_type

Habitat type.

chelonian_shell_type

Shell type (hardshell/softshell).

References

Wang Y et al. (2025) CheloniansTraits: a comprehensive trait database of global turtles and tortoises. figshare. doi:10.6084/m9.figshare.28828241

Examples

taxify("Chelonia mydas", backend = "gbif") |>
  add_chelonians()

Add the full higher classification to a taxify result

Description

Attaches the Linnaean ranks above family (kingdom, phylum, class, order) to a taxify() result by joining each matched row back to its backbone. The core taxify() output already carries family and genus; this fills the ranks above them, for whichever ranks the matched backbone stores. Rows matched by different backends are each joined against their own backbone.

Usage

add_classification(
  x,
  ranks = c("kingdom", "phylum", "class", "order"),
  verbose = TRUE
)

Arguments

Value

x with the requested rank columns added. A rank a backbone does not store is left NA (WFO, for example, carries no ranks above family).

See Also

add_col_info(), add_gbif_info() for backend-specific extras.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Naja naja", backend = "reptiledb") |>
  add_classification()

options(old)

Add COL-specific columns

Description

Joins extra Catalogue of Life columns to a taxify() result by looking up taxon_id in the COL backbone. Only enriches rows where backend == "col".

Usage

add_col_info(x)

Arguments

Value

The same data.frame with additional columns:

notho

Hybrid type from COL: "generic", "specific", "infrageneric", or "infraspecific".

nomenclaturalCode

Nomenclatural code ("ICN", "ICZN", etc.).

nomenclaturalStatus

Nomenclatural status.

namePublishedIn

Original publication reference.

kingdom

Kingdom classification.

phylum

Phylum classification.

col_class

Class classification (renamed to avoid conflict with R's class function).

order

Order classification.

infraspecificEpithet

Infraspecific epithet.

is_extinct

Logical. Whether the species is extinct (from SpeciesProfile, if available).

is_marine

Logical. Whether the species is marine.

is_freshwater

Logical. Whether the species is freshwater.

is_terrestrial

Logical. Whether the species is terrestrial.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Quercus robur", backend = "col") |>
  add_col_info()

options(old)

Add mammal traits (COMBINE)

Description

Joins COMBINE mammal traits to a taxify() result by looking up accepted_name. COMBINE is a separate, coalesced mammal trait source; it is offered alongside add_pantheria(), not as a replacement. Reported (not phylogenetically imputed) values are used.

Usage

add_combine(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: COMBINE (Soria et al. 2021, Ecology, CC0). Coverage: ~6.2k mammal species. Keyed on the IUCN 2020 binomial.

Value

The same data.frame with additional columns:

combine_adult_mass_g

Adult body mass (g).

combine_adult_body_length_mm

Adult head-body length (mm).

combine_litter_size_n

Litter size (count).

combine_litters_per_year_n

Litters per year (count).

combine_max_longevity_d

Maximum longevity (days).

combine_gestation_length_d

Gestation length (days).

combine_weaning_age_d

Weaning age (days).

combine_generation_length_d

Generation length (days).

combine_dispersal_km

Natal dispersal distance (km).

combine_habitat_breadth_n

Number of IUCN habitats (count).

combine_diet_breadth_n

Number of diet categories (count).

combine_trophic_level

Trophic level (1 herbivore, 2 omnivore, 3 carnivore).

combine_activity_cycle

Activity cycle (1 nocturnal, 2 cathemeral, 3 diurnal).

combine_foraging_stratum

Foraging stratum (G/Ar/A/S/M).

combine_biogeographical_realm

Biogeographical realm(s).

References

Soria CD et al. (2021) COMBINE: a coalesced mammal database of intrinsic and extrinsic traits. Ecology 102:e03344. doi:10.1002/ecy.3344

Examples

taxify("Vulpes vulpes", backend = "gbif") |>
  add_combine()

Add common (vernacular) names

Description

Joins vernacular names to a taxify() result by looking up accepted_name, filtered by language.

Usage

add_common_names(x, lang = "en", cols = NULL, verbose = TRUE)

Arguments

Details

Common names are merged from three sources:

• GBIF backbone vernacular names (CC0) — multi-language via ISO 639-1 codes.

• NCBI Taxonomy common names (public domain) — no language tag (lang = NA).

• Open Tree of Life common names (CC0) — no language tag (lang = NA).

When multiple common names exist for a species in the requested language, the first (most commonly used) is returned.

Value

The same data.frame with an additional column:

common_name

The vernacular name in the requested language, or NA if none is available.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Quercus robur") |>
  add_common_names()

taxify("Quercus robur") |>
  add_common_names(lang = "de")

options(old)

Add scleractinian coral traits (Coral Trait Database)

Description

Joins species-level coral functional traits to a taxify() result by looking up accepted_name. Values are aggregated from the long-format Coral Trait Database (numeric traits by median, categorical traits by mode).

Usage

add_coral_traits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Coral Trait Database (Madin et al. 2016, Scientific Data, CC BY 4.0). Coverage: ~1.5k coral species.

Value

The same data.frame with additional columns:

coral_symbiotic_state

Zooxanthellate / azooxanthellate.

coral_growth_form

Typical growth form (massive/branching/...).

coral_coloniality

Colonial / solitary.

coral_substrate_attachment

Attached / unattached.

coral_sexual_system

Hermaphrodite / gonochore.

coral_larval_development_mode

Spawner / brooder.

coral_symbiont_clade

Symbiodinium clade.

coral_corallite_width_max_mm

Maximum corallite width (mm).

coral_colony_max_diameter_cm

Maximum colony diameter (cm).

coral_growth_rate_mm_yr

Linear extension rate (mm/year).

coral_depth_lower_m

Lower depth limit (m).

coral_depth_upper_m

Upper depth limit (m).

coral_skeletal_density_g_cm3

Skeletal density (g/cm3).

References

Madin JS et al. (2016) The Coral Trait Database, a curated database of trait information for coral species from the global oceans. Scientific Data 3:160017. doi:10.1038/sdata.2016.17

Examples

taxify("Acropora millepora", backend = "gbif") |>
  add_coral_traits()

Add custom data by taxonomic matching

Description

Joins an external data source (CSV file or data.frame) to a taxify() result. Species names in the external data are matched through the same backbone(s) used in the original taxify() call, and the join is performed on accepted_id — so synonyms in either dataset resolve to the same key.

Usage

add_data(
  x,
  data,
  species_col = NULL,
  table = NULL,
  sheet = NULL,
  start_row = NULL,
  cols = NULL,
  group_col = NULL,
  groups = "all",
  fuzzy = TRUE,
  fuzzy_threshold = 0.2,
  verbose = TRUE
)

Arguments

Details

The workflow:

1. Read data (CSV or data.frame).

2. Identify the species column (explicit or auto-detected).

3. Match species names through the same backbone(s) as the original taxify() call, obtaining accepted_id for each row.

4. Check for conflicting duplicates: if multiple rows in data resolve to the same accepted_id with different values, an error is raised (unless group_col is set). Exact duplicates produce a warning and are deduplicated.

5. Left-join on accepted_id.

Grouped data

When your data has multiple rows per species (e.g., one row per species per country), set group_col to produce wide output with suffixed columns. This is the same format as the built-in grouped enrichments.

Auto-detection

When species_col is not specified, add_data() takes the first 10 rows of each character column and runs them through taxify(). The column with the highest match rate is selected. If no column achieves at least 50% matches, an error is raised asking the user to specify species_col explicitly.

Value

The input data.frame with additional columns from data, joined via backbone-resolved accepted_id. Columns from data that collide with existing columns in x are prefixed with "data_".

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

result <- taxify(c("Quercus robur", "Pinus sylvestris"))
traits <- data.frame(species = c("Quercus robur", "Pinus sylvestris"),
                     height = c(30, 25))
result |> add_data(traits, species_col = "species")

options(old)

Add seed mass and plant height (Diaz et al. 2022)

Description

Joins species-level mean seed mass and plant height from Diaz et al. (2022) to a taxify() result by looking up accepted_name.

Usage

add_diaz_traits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Diaz et al. 2022, TRY File Archive (CC BY 3.0). Coverage: ~46k plant species. Plants only.

Value

The same data.frame with additional columns:

seed_mass_mg

Seed mass in milligrams (species-level mean).

plant_height_m

Plant height in metres (species-level mean).

References

Diaz S et al. (2022) The global spectrum of plant form and function: enhanced species-level trait data. TRY File Archive.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Quercus robur") |>
  add_diaz_traits()

options(old)

Add aquatic-invertebrate dispersal traits (DISPERSE)

Description

Joins genus-level dispersal-related traits for European aquatic macroinvertebrates to a taxify() result by genus. Each fuzzy-coded trait is reduced to its dominant modality (with the database's own labels).

Usage

add_disperse(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: DISPERSE (Sarremejane et al. 2020, Scientific Data, CC-BY 4.0). Joins on genus because the database is genus-resolved.

Value

The same data.frame with categorical disperse_body_size_cm, disperse_life_cycle, disperse_repro_cycles, disperse_dispersal, disperse_adult_lifespan, disperse_female_wing_mm, disperse_wing_type, disperse_fecundity, disperse_drift, and the numeric bin-midpoint columns disperse_body_size_cm_mid, disperse_female_wing_mm_mid, disperse_fecundity_mid (all joined on genus).

References

Sarremejane R et al. (2020) DISPERSE, a trait database to assess the dispersal potential of European aquatic macroinvertebrates. Scientific Data 7:386. doi:10.6084/m9.figshare.c.5000633

Examples

taxify("Baetis rhodani", backend = "gbif") |>
  add_disperse()

Add British plant traits from Ecoflora

Description

Joins traits from the Ecological Flora of the British Isles (Fitter & Peat 1994) to a taxify() result by looking up accepted_name. Ecoflora covers the vascular flora of the British Isles, providing canopy height, leaf traits, life form, flowering phenology, pollination and reproduction, seed weight, and British-calibrated Ellenberg indicator values. Every column carries a ⁠_uk⁠ suffix to mark the British-flora calibration and to avoid collisions when chained with other plant-trait enrichments (e.g. add_baseflor() for France, add_floraweb() for Germany).

Usage

add_ecoflora(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Ecoflora (Ecological Flora of the British Isles). Ecoflora has no bulk download or API; the bundled dataset was collected one species at a time and is redistributed under the source licence (CC BY-NC-SA 4.0). The .vtr is downloaded from the taxify release on first use and cached.

For French-flora traits see add_baseflor(); for German-flora traits see add_floraweb(); for European-calibration indicator values see add_eive().

Value

The same data.frame with additional ⁠_uk⁠ columns:

height_max_mm_uk, height_min_mm_uk

Canopy height range (mm).

leaf_area_uk

Leaf area class.

leaf_longevity_uk

Leaf longevity (e.g. evergreen, deciduous).

root_system_uk

Root system type.

photosynthetic_pathway_uk

Photosynthetic pathway (C3/C4/CAM).

life_form_uk

Raunkiaer life form.

reproduction_uk

Reproduction method.

flower_begin_month_uk, flower_end_month_uk

Flowering months (1-12).

pollination_vector_uk

Pollen vector(s).

seed_weight_mg_uk

Seed weight (mg).

propagule_uk

Propagule / dispersule type.

ell_light_uk, ell_moisture_uk, ell_reaction_uk, ell_nitrogen_uk, ell_salt_uk

Ellenberg indicator values calibrated for the British flora (light, moisture, reaction, nitrogen, salt).

References

Fitter AH, Peat HJ (1994) The Ecological Flora Database. Journal of Ecology 82:415-425.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Bellis perennis") |>
  add_ecoflora()

options(old)

Add phytoplankton nutrient-uptake traits (Edwards et al.)

Description

Joins species-level phytoplankton nutrient physiology (Droop/Monod uptake and growth parameters for ammonium, nitrate and phosphorus, plus cell size and carbon content) to a taxify() result by looking up accepted_name.

Usage

add_edwards_phyto(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Edwards et al. (2015, Ecology, CC BY 4.0), a compilation of phytoplankton nutrient-utilization traits for ~130 species. Single-source physiological data with no cross-source analogue, so it is surfaced through this door rather than the cross-source add_trait() verb.

Value

The same data.frame with additional columns. The curated set:

edwards_taxon_group

Coarse phytoplankton group (diatom, green, ...).

edwards_habitat_system

Habitat (marine/freshwater).

edwards_cell_volume

Cell volume (micron^3).

edwards_carbon_per_cell

Carbon content per cell (pg C).

edwards_mu_inf_nit

Maximum growth rate on nitrate (per day).

edwards_k_nit

Half-saturation constant for growth on nitrate.

edwards_qmin_nit

Minimum cell nitrogen quota.

edwards_mu_inf_p

Maximum growth rate on phosphorus (per day).

edwards_k_p

Half-saturation constant for growth on phosphorus.

edwards_qmin_p

Minimum cell phosphorus quota.

With cols = "all" the full set of ammonium/nitrate/phosphorus uptake and quota parameters (vmax_amm, mu_nit, vmax_p, qmax_p, ...) is attached under their source names. All uptake/quota traits are joined on accepted_name.

References

Edwards KF, Thomas MK, Klausmeier CA, Litchman E (2015) Phytoplankton growth and the interaction of light and temperature: A synthesis at the species and community level. Ecology 96(9):2554-2564. doi:10.1890/14-2252.1

Examples

taxify("Thalassiosira pseudonana", backend = "gbif") |>
  add_edwards_phyto()

Add EIVE ecological indicator values

Description

Joins EIVE 1.0 (Dengler et al. 2023) ecological indicator values to a taxify() result by looking up accepted_name. EIVE provides continuous indicator values for European vascular plants, superseding the original ordinal Ellenberg values.

Usage

add_eive(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: EIVE 1.0 (Dengler et al. 2023, Zenodo, CC BY 4.0). Coverage: ~14.5k European vascular plant species.

Value

The same data.frame with additional columns:

eive_light

Light indicator value (continuous).

eive_temperature

Temperature indicator value (continuous).

eive_moisture

Moisture indicator value (continuous).

eive_reaction

Soil reaction (pH) indicator value (continuous).

eive_nutrients

Nutrient indicator value (continuous).

References

Dengler J et al. (2023) EIVE 1.0 – a standardized set of Ecological Indicator Values for Europe. Vegetation Classification and Survey 4:7-29. doi:10.3897/VCS.98324

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Arrhenatherum elatius") |>
  add_eive()

options(old)

Add diet, foraging, and body mass (EltonTraits 1.0)

Description

Joins EltonTraits 1.0 diet composition, foraging strata, body mass, and activity data to a taxify() result by looking up accepted_name.

Usage

add_elton_traits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: EltonTraits 1.0 (Wilman et al. 2014, Figshare, CC0). Coverage: ~15.4k species. Birds and mammals only.

Value

The same data.frame with additional columns:

diet_inv

Percentage of diet: invertebrates.

diet_vend

Percentage of diet: endothermic vertebrates.

diet_vect

Percentage of diet: ectothermic vertebrates.

diet_vfish

Percentage of diet: fish.

diet_vunk

Percentage of diet: unknown vertebrates.

diet_scav

Percentage of diet: scavenging.

diet_fruit

Percentage of diet: fruit.

diet_nect

Percentage of diet: nectar.

diet_seed

Percentage of diet: seeds and nuts.

diet_plantother

Percentage of diet: other plant material.

foraging_water

Percentage of foraging: below water surface.

foraging_ground

Percentage of foraging: on ground.

foraging_understory

Percentage of foraging: in understory.

foraging_midhigh

Percentage of foraging: in mid to high strata.

foraging_canopy

Percentage of foraging: in canopy.

foraging_aerial

Percentage of foraging: aerial.

elton_body_mass_g

Body mass in grams.

nocturnal

Nocturnal activity (0 = diurnal, 1 = nocturnal).

diet_guild

Dominant diet guild derived from the ten diet-fraction columns (fractions summed within guild, the guild reaching 50 percent wins, otherwise omnivore): carnivore, herbivore, omnivore, invertivore, frugivore, granivore, nectarivore, scavenger. Also reachable across sources via add_trait(x, "diet_guild").

References

Wilman H et al. (2014) EltonTraits 1.0: Species-level foraging attributes of the world's birds and mammals. Ecology 95:2027.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Parus major", backend = "gbif") |>
  add_elton_traits()

options(old)

Add European pollinator traits (EuPollTrait)

Description

Joins European bee and hoverfly morphological, biogeographic and ecological traits to a taxify() result by accepted_name.

Usage

add_eupolltrait(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: EuPollTrait (Milicic et al. 2025, Zenodo, CC-BY 4.0).

Value

The same data.frame with eupolltrait_ columns: numeric itd_mm, tongue_length_mm, species_temperature_index, species_continentality_index, area_of_occupancy, extent_of_occurrence; categorical sociality, nest, larval_nutrition, body_length_category.

References

Milicic M et al. (2025) EuPollTrait: a trait database for European bees and hoverflies. Zenodo. doi:10.5281/zenodo.18032357

Examples

taxify("Bombus terrestris", backend = "gbif") |>
  add_eupolltrait()

Add European bat traits (EuroBaTrait)

Description

Joins species-level traits of European bats (morphology, life history, diet, foraging habitat, roost type) to a taxify() result by looking up accepted_name.

Usage

add_eurobat(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Froidevaux et al. (2023, Scientific Data, CC BY 4.0), EuroBaTrait 1.0. Thematic measurement-or-fact tables are reduced to species-level values (numeric by median, categorical by mode).

Value

The same data.frame with additional columns. The curated set:

eurobat_forearm_length_mm

Forearm length (mm).

eurobat_body_mass_g

Body mass (g).

eurobat_max_longevity_yr

Maximum recorded longevity (years).

eurobat_litter_size

Litter size.

eurobat_diet_type

Diet type (insectivorous, frugivorous, ...).

eurobat_first_main_prey

First main prey item.

With cols = "all" the full trait set (digit lengths, wing indices, habitat affinity scores, critical feeding areas, roost dependence, phenology, ...) is attached under their source names.

References

Froidevaux JSP et al. (2023) EuroBaTrait 1.0: a species-level trait dataset of bats in Europe and beyond. Scientific Data. figshare doi:10.6084/m9.figshare.21777161

Examples

taxify("Myotis myotis", backend = "gbif") |>
  add_eurobat()

Add fish traits (FishBase)

Description

Joins FishBase morphological and ecological traits to a taxify() result by looking up accepted_name.

Usage

add_fishbase(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: FishBase via rfishbase (Froese & Pauly, CC BY-NC 4.0). Coverage: ~35k fish species. Fishes only.

The build-from-source fallback requires the rfishbase package (available on CRAN). Pre-built .vtr files do not require rfishbase.

Value

The same data.frame with additional columns:

fb_body_length_cm

Maximum body length in centimetres.

fb_body_mass_g

Body mass in grams (estimated from length-weight relationships where available).

fb_trophic_level

Trophic level.

fb_depth_min_m

Minimum depth in metres.

fb_depth_max_m

Maximum depth in metres.

fb_vulnerability

Vulnerability index (0–100).

fb_habitat

Habitat type (e.g. demersal, pelagic).

fb_importance

Commercial importance category.

References

Froese R, Pauly D (eds.) (2024) FishBase. World Wide Web electronic publication, https://www.fishbase.org.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Gadus morhua", backend = "gbif") |>
  add_fishbase()

options(old)

Add freshwater fish morphological traits (FISHMORPH)

Description

Joins FISHMORPH morphological trait data to a taxify() result by looking up accepted_name. This is the source-named door for FISHMORPH; for the fish reference database FishBase see add_fishbase().

Usage

add_fishmorph(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: FISHMORPH (Brosse et al. 2021, Figshare, CC BY 4.0). Coverage: ~8.3k freshwater fish species.

Value

The same data.frame with additional columns:

fish_max_body_length

Maximum body length (cm).

fish_body_elongation

Body elongation (body length / body depth).

fish_vertical_eye_position

Vertical eye position (eye position / head depth).

fish_relative_eye_size

Relative eye size (eye diameter / head length).

fish_oral_gape_position

Oral gape position (mouth position: 0 = inferior, 0.5 = terminal, 1 = superior).

fish_relative_maxillary_length

Relative maxillary length (maxillary length / head length).

fish_body_lateral_shape

Body lateral shape (body depth / caudal peduncle depth).

fish_pectoral_fin_position

Pectoral fin vertical position (fin insertion depth / body depth).

fish_pectoral_fin_size

Pectoral fin size (fin length / body length).

fish_caudal_peduncle_throttling

Caudal peduncle throttling (caudal peduncle depth / caudal fin depth).

References

Brosse S, Charpin N, Su G, Toussaint A, Herrera-R GA, Tedesco PA, Villegé r S (2021) FISHMORPH: A global database on morphological traits of freshwater fishes. Global Ecology and Biogeography 30:2330-2336. doi:10.1111/geb.13395

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Salmo trutta", backend = "gbif") |>
  add_fishmorph()

options(old)

Add German plant traits from FloraWeb

Description

Joins traits from FloraWeb (Bundesamt fuer Naturschutz) to a taxify() result by looking up accepted_name. FloraWeb is the live national portal carrying the BiolFlor trait data (Klotz, Kuehn & Durka 2002) together with Rothmaler morphology and Ellenberg indicator values. This enrichment covers the full per-species trait profile scraped from the four FloraWeb trait pages: morphology, reproductive biology, the nine Ellenberg indicator values, ploidy and chromosome number, and chorological distribution. Every column carries a ⁠_de⁠ suffix to mark the German-flora calibration and to avoid collisions when chained with other plant-trait enrichments (e.g. add_ecoflora() for Britain, add_baseflor() for France).

Usage

add_floraweb(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: FloraWeb (https://www.floraweb.de/), Bundesamt fuer Naturschutz, Bonn. FloraWeb has no bulk export or API; the bundled dataset was scraped per species (accessed 2026-06-24) and that access date is the dataset version. The trait data largely derive from BiolFlor, which per the BioFresh metadata statement is publicly available and may be used without restrictions provided it is acknowledged and cited correctly. The .vtr is downloaded from the taxify release on first use and cached.

For British-flora traits see add_ecoflora(); for French-flora traits see add_baseflor(); for European-calibration indicator values see add_eive().

Value

The same data.frame with German trait columns (all suffixed ⁠_de⁠), grouped as:

Morphology

height_de, life_form_de, leaf_shape_de, leaf_anatomy_de, leaf_persistence_de, storage_organs_de, flowering_months_de, flowering_months_biolflor_de, flowering_phase_de, phenological_season_de, description_de.

Reproductive biology

pollination_vector_de, pollinator_de, pollinator_reward_de, flower_type_de, flower_class_de, dispersal_type_de, diaspore_type_de, germinule_type_de, reproduction_type_de, vegetative_spread_de, fertilization_type_de, apomixis_de, dicliny_de, dichogamy_de, self_incompatibility_de, si_mechanism_de, ploidy_de, chromosome_number_de, chromosome_freq_de, chromosomes_de.

Ecology

the nine Ellenberg indicator values ell_light_de, ell_temperature_de, ell_continentality_de, ell_moisture_de, ell_moisture_variability_de, ell_reaction_de, ell_nitrogen_de, ell_salt_de, heavy_metal_resistance_de, plus strategy_type_de (Grime CSR), habitat_site_de, formation_de, plant_community_de, biotope_type_de, forest_binding_de, hemeroby_de, urbanity_de.

Distribution

floristic_zones_de, areal_formula_de, areal_type_de, oceanity_de, range_centre_de, world_range_size_de, world_range_frequency_de, world_range_position_de, world_range_hazard_de, germany_range_share_de, germany_responsibility_de.

Categorical traits with several applicable values are joined with "; ". Trait values are German (as published by FloraWeb / BiolFlor).

References

Klotz S, Kuehn I, Durka W (2002) BIOLFLOR - Eine Datenbank zu biologisch-oekologischen Merkmalen der Gefaesspflanzen in Deutschland. Schriftenreihe fuer Vegetationskunde 38. Bundesamt fuer Naturschutz, Bonn.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Bellis perennis") |>
  add_floraweb()

options(old)

Add freshwater-insect genus traits (Freshwater Insects CONUS)

Description

Joins genus-level ecological and life-history trait modalities of North American freshwater insects to a taxify() result by looking up genus, so any species in a covered genus is annotated. The modalities are the source's own abbreviation codes, kept verbatim.

Usage

add_freshwater_insects_conus(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Twardochleb et al. (2021, Environmental Data Initiative, CC BY 4.0), the Freshwater Insects CONUS genus trait table. Traits are genus-level categorical modalities.

Value

The same data.frame with additional columns. The curated set:

fwinsect_thermal_pref

Thermal preference class.

fwinsect_feed_prim

Primary functional feeding group code.

fwinsect_habit_prim

Primary habit (swimmer, clinger, burrower, ...).

fwinsect_rheophily

Rheophily (current preference) code.

fwinsect_voltinism

Voltinism (generations per year) code.

fwinsect_max_body_size

Maximum body size class.

With cols = "all" the remaining trait groups (emergence, dispersal, respiration, ...) are attached under their source names.

References

Twardochleb LA et al. (2021) Freshwater insect occurrences and traits for the contiguous United States, 2001-2018. Environmental Data Initiative. doi:10.6073/pasta/8238ea9bc15840844b3a023b6b6ed158

Examples

taxify("Baetis", backend = "gbif") |>
  add_freshwater_insects_conus()

Add Neotropical frugivore traits (Frugivoria)

Description

Joins shared bird/mammal frugivore traits to a taxify() result by accepted_name.

Usage

add_frugivoria(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Gerstner et al. (2023) Frugivoria (EDI, CC-BY 4.0).

Value

The same data.frame with frugivoria_ columns: categorical taxon_group, diet_category; numeric diet_breadth, body_mass_g, body_size_mm, longevity, generation_time.

References

Gerstner BE et al. (2023) Frugivoria: a trait database for birds and mammals exhibiting frugivory across contiguous Neotropical moist forests. EDI (edi.1220.5).

Examples

taxify("Ramphastos toco", backend = "gbif") |>
  add_frugivoria()

Add fungal lifestyle and trait data (FungalTraits)

Description

Joins FungalTraits (Polme et al. 2020) genus-level trait data to a taxify() result by looking up genus. Unlike other enrichments that join on species-level accepted_name, FungalTraits is a genus-level database and joins on the genus column already present in taxify output.

Usage

add_fungal_traits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: FungalTraits (Polme et al. 2020, Fungal Diversity, CC BY 4.0). Coverage: ~10k fungal genera. Genus-level only (not species-level).

Value

The same data.frame with additional columns:

primary_lifestyle

Primary ecological role (e.g., saprotroph, mycorrhizal, pathogen, endophyte, lichenized, parasite).

secondary_lifestyle

Secondary ecological role, if any.

growth_form

Morphological growth form (e.g., agaricoid, corticioid, polyporoid, yeast).

fruitbody_type

Fruiting body morphology (e.g., gasteroid, pileate, resupinate).

decay_substrate

Substrate type for saprotrophic genera (e.g., wood, litter, dung, soil).

plant_pathogenic_capacity

Capacity to cause plant disease (e.g., high, medium, low, none).

animal_biotrophic_capacity

Capacity for animal biotrophy.

endophytic_interaction_capability

Capacity for endophytic interactions with plants.

ectomycorrhiza_exploration_type

Exploration type for ectomycorrhizal genera (e.g., contact, short, medium, long).

References

Polme S et al. (2020) FungalTraits: a user-friendly traits database of fungi and fungus-like stramenopiles. Fungal Diversity 105:1-16. doi:10.1007/s13225-020-00466-2

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Amanita muscaria", backend = "gbif") |>
  add_fungal_traits()

options(old)

Add mycorrhizal type from FungalRoot

Description

Joins genus-level mycorrhizal type from the FungalRoot database (Soudzilovskaia et al. 2020) to a taxify() result by looking up genus. Mycorrhizal type is phylogenetically conserved at the genus level, which is the resolution FungalRoot recommends for inference, so this enrichment joins on genus rather than accepted_name.

Usage

add_fungalroot(x, verbose = TRUE)

Arguments

Details

Source: FungalRoot, published on GBIF as a Darwin Core Archive (doi:10.15468/a7ujmj), CC BY-NC 4.0. The per-genus value is a majority consensus computed from the per-observation mycorrhiza type labels, not FungalRoot's own published per-genus assignment. Plant genera only. The .vtr is downloaded from the taxify release on first use and cached.

Value

The same data.frame with three additional columns:

mycorrhizal_type

Genus-level majority-consensus type, one of AM (arbuscular), EcM (ecto), ErM (ericoid), OM (orchid), NM (non-mycorrhizal), the dual types EcM-AM / ErM-EcM / ErM-AM, Other, or uncertain. NA if the genus is not in FungalRoot.

mycorrhizal_status

Coarse status derived from the type: "mycorrhizal", "non-mycorrhizal", or "uncertain".

mycorrhizal_records

Number of FungalRoot observations supporting the genus-level consensus.

References

Soudzilovskaia NA et al. (2020) FungalRoot: global online database of plant mycorrhizal associations. New Phytologist 227:955-966.

Examples

# Joins on genus, so any species in a covered genus is annotated.
taxify(c("Quercus robur", "Trifolium pratense")) |>
  add_fungalroot()

Add fungal functional guild data (FUNGuild)

Description

Joins FUNGuild trophic mode, guild, growth morphology, and confidence data to a taxify() result by looking up accepted_name. Species-level matches take priority; genus-level guild assignments are used as fallback for unmatched species.

Usage

add_funguild(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: FUNGuild (Nguyen et al. 2016, CC BY 4.0). Coverage: ~13k taxa. Fungi only.

The enrichment first attempts species-level matching. For species without a direct match, it falls back to genus-level guild assignments from FUNGuild's genus-rank entries.

Value

The same data.frame with additional columns:

trophic_mode

Trophic mode (e.g., Pathotroph, Saprotroph, Symbiotroph, or hyphenated combinations).

guild

Functional guild (e.g., "Ectomycorrhizal", "Plant Pathogen", "Wood Saprotroph").

funguild_growth_form

Growth morphology (e.g., "Agaricoid", "Microfungus"). Prefixed to avoid collision with FungalTraits.

confidence_ranking

Confidence of the guild assignment (Possible, Probable, Highly Probable).

References

Nguyen NH et al. (2016) FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecology 20:241-248.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Amanita muscaria", backend = "gbif") |>
  add_funguild()

options(old)

Add GBIF-specific columns

Description

Joins extra GBIF backbone columns to a taxify() result by looking up taxon_id in the GBIF backbone. Only enriches rows where backend == "gbif".

Usage

add_gbif_info(x)

Arguments

Value

The same data.frame with additional columns:

notho_type

Hybrid type: "GENERIC", "SPECIFIC", or "INFRASPECIFIC".

nom_status

Nomenclatural status (may contain multiple values).

bracket_authorship

Basionym author in parentheses.

bracket_year

Basionym author year.

gbif_year

Combining author year.

name_published_in

Publication citation.

origin

How the name entered the backbone.

infra_specific_epithet

Infraspecific epithet.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Quercus robur", backend = "gbif") |>
  add_gbif_info()

options(old)

Add plant traits from GIFT

Description

Joins species-level plant traits from GIFT, the Global Inventory of Floras and Traits (Weigelt et al. 2020), to a taxify() result by accepted_name. GIFT aggregates published trait records to one value per species (mean for numeric traits, most frequent entry for categorical ones). You choose which traits to attach with cols; browse the available columns with gift_traits().

Usage

add_gift(x, cols = NULL, verbose = TRUE)

Arguments

Details

The GIFT trait table is bundled as a pre-built .vtr and joined offline, so no internet access is needed once it is present (the first use downloads it, or builds it from source if taxifydb is installed). GIFT's API exposes only the redistributable subset of its data (CC BY 4.0; references whose underlying source is restricted are excluded), and that subset is what is bundled here. Cite GIFT and, where applicable, the underlying references (GIFT::GIFT_references()) when you use the values.

Value

The same data.frame with one added column per requested trait, named ⁠gift_<trait>⁠. Numeric traits (heights, masses, areas) are doubles, the rest character. Rows with no value in GIFT get NA. With the default cols, the added columns are gift_woodiness_1, gift_growth_form_1, gift_lifecycle_1, gift_life_form_1, gift_climber_1, gift_epiphyte_1, gift_parasite_1, gift_aquatic_1, gift_plant_height_max, gift_photosynthetic_pathway, gift_seed_mass_mean, gift_dispersal_syndrome_1, gift_flowering_start, gift_flowering_end, gift_deciduousness_1, and gift_sla_mean.

References

Weigelt P, Konig C, Kreft H (2020) GIFT - A Global Inventory of Floras and Traits for macroecology and biogeography. Journal of Biogeography 47:16-43. doi:10.1111/jbi.13623 Denelle P, Weigelt P, Kreft H (2023) GIFT: an R package to access the Global Inventory of Floras and Traits. Methods in Ecology and Evolution 14:2738-2748. doi:10.1111/2041-210X.14213

See Also

gift_traits() to browse the available columns.

Examples

old <- options(taxify.data_dir = taxify_example_data())

taxify("Abies alba") |>
  add_gift()

options(old)

Add biotic interaction degree (GloBI)

Description

Joins per-species biotic interaction breadth from GloBI (Global Biotic Interactions) to a taxify() result by looking up accepted_name. GloBI's aggregated interaction records are reduced to per-species counts: how many distinct partner taxa a species interacts with (undirected), across how many distinct interaction types, over how many interaction records.

Usage

add_globi(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: GloBI (Poelen et al. 2014), an open index of biotic interactions aggregated from many contributed datasets. Only derived per-species counts are distributed here; the underlying interaction records carry the licenses of their original data contributors, who should be cited in derivative work. Partner counts are resolved to accepted names before counting, so synonymous partners are not double-counted.

Value

The same data.frame with additional columns:

interaction_degree

Number of distinct partner taxa recorded interacting with the species (both directions).

n_interaction_types

Number of distinct interaction types (eats, pollinates, parasitises, ...).

n_interaction_records

Total number of interaction records touching the species.

References

Poelen JH, Simons JD, Mungall CJ (2014) Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics 24:148-159. doi:10.1016/j.ecoinf.2014.08.005

Examples

taxify("Apis mellifera", backend = "gbif") |>
  add_globi()

Add thermal tolerance limits (GlobTherm)

Description

Joins GlobTherm upper and lower thermal tolerance limits to a taxify() result by looking up accepted_name.

Usage

add_globtherm(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: GlobTherm (Bennett et al. 2018, Scientific Data, CC0). Coverage: ~2.1k species across aquatic and terrestrial groups.

Value

The same data.frame with additional columns:

globtherm_thermal_max_c

Upper thermal limit (degrees Celsius).

globtherm_thermal_max_metric

Definition of the upper limit (e.g. ctmax, LT50, UTNZ); the value is ambiguous without it.

globtherm_thermal_min_c

Lower thermal limit (degrees Celsius).

globtherm_thermal_min_metric

Definition of the lower limit (e.g. ctmin, LT50, LTNZ).

globtherm_thermal_max_error

Reported error on the upper limit.

globtherm_thermal_min_error

Reported error on the lower limit.

References

Bennett JM et al. (2018) GlobTherm, a database on the thermal tolerance for aquatic and terrestrial organisms. Scientific Data 5:180022. doi:10.1038/sdata.2018.22

Examples

taxify("Lepomis gibbosus", backend = "gbif") |>
  add_globtherm()

Add naturalized alien flora status (GloNAF)

Description

Joins GloNAF (Global Naturalized Alien Flora) data to a taxify() result, filtered by region.

Usage

add_glonaf(x, region, verbose = TRUE)

Arguments

Details

Source: GloNAF v2.0 (van Kleunen et al. 2019, Davis et al. 2025, CC BY 4.0). Coverage: ~16k alien plant taxa across ~1,300 regions. Plants only.

Value

The same data.frame with additional column(s):

naturalized

Integer 1 if the species is recorded as naturalized in that region, NA otherwise.

References

van Kleunen M et al. (2019) The Global Naturalized Alien Flora (GloNAF) database. Ecology 100:e02542.

Davis K et al. (2025) The updated Global Naturalized Alien Flora (GloNAF 2.0) database. Ecology, e70245.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Robinia pseudoacacia") |>
  add_glonaf(region = "EUR")

taxify("Robinia pseudoacacia") |>
  add_glonaf(region = c("EUR", "NAM"))

options(old)

Add invasive species status (GRIIS)

Description

Joins GRIIS (Global Register of Introduced and Invasive Species) status to a taxify() result, filtered by country. This is the source-named door for GRIIS; GloNAF (add_glonaf()) carries related naturalized-alien status.

Usage

add_griis(x, country, cols = NULL, verbose = TRUE)

Arguments

Details

Source: GRIIS (Zenodo combined CSV, CC BY 4.0, 196 countries). Coverage: ~23k name x country combinations.

Value

The same data.frame with additional column(s):

invasive_status

One of "native", "introduced", "invasive", or NA if not recorded for that country.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Robinia pseudoacacia") |>
  add_griis(country = "AT")

taxify("Robinia pseudoacacia") |>
  add_griis(country = c("AT", "DE"))

options(old)

Add root traits (GRooT)

Description

Joins species-level root traits from the Global Root Traits (GRooT) database to a taxify() result by looking up accepted_name. GRooT aggregates root trait records to per-species means. The .vtr carries the full GRooT trait set (38 root traits); the default attaches the nine best-populated key traits, and cols = "all" attaches every one. Run enrichment_cols("groot") to list them.

Usage

add_groot(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: GRooT database (Guerrero-Ramirez et al. 2021). Vascular plants. GRooT data are publicly available and used here with the data-paper citation requested by the authors.

Value

The same data.frame with additional columns (per-species means). The default set:

root_diameter

Mean root diameter.

specific_root_length

Specific root length.

root_tissue_density

Root tissue density.

root_n_concentration

Root nitrogen concentration.

root_c_concentration

Root carbon concentration.

root_mass_fraction

Root mass fraction.

lateral_spread

Lateral spread.

root_mycorrhizal_colonization

Root mycorrhizal colonization intensity.

rooting_depth

Maximum rooting depth.

cols = "all" additionally attaches root chemistry (P/K/Ca/Mg/Mn concentrations, C:N and N:P ratios), architecture (branching density and ratio, stele diameter and fraction, cortex thickness, vessel diameter and number), turnover (root lifespan, production, turnover rate, litter mass-loss rate), and specific root area, respiration, and dry-matter content, among others. Units follow the GRooT data paper; see the reference below.

References

Guerrero-Ramirez NR et al. (2021) Global root traits (GRooT) database. Global Ecology and Biogeography 30:25-37. doi:10.1111/geb.13179

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Abies alba") |>
  add_groot()

options(old)

Add wood density (Global Wood Density Database v2)

Description

Joins species-level wood density to a taxify() result by looking up accepted_name. Wood density is reported as wood specific gravity (oven-dry mass / green volume), dimensionless and numerically equal to g/cm3.

Usage

add_gwdd(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Global Wood Density Database v2 (Fischer et al. 2026, New Phytologist, CC BY 4.0). Coverage: ~17.3k species. Bark density is not part of the aggregated source and is not included.

Value

The same data.frame with additional columns:

gwdd_wood_density_g_cm3

Species-mean wood density (g/cm3).

gwdd_wood_density_trunk_g_cm3

Trunk wood density (g/cm3).

gwdd_wood_density_branch_g_cm3

Branch wood density (g/cm3).

gwdd_n_measurements

Number of underlying measurements.

References

Fischer FJ et al. (2026) The Global Wood Density Database version 2. New Phytologist. doi:10.1111/nph.70860

Examples

taxify("Quercus robur", backend = "gbif") |>
  add_gwdd()

Add mammal home-range size (HomeRange)

Description

Joins species-median home-range size and body mass to a taxify() result by accepted_name.

Usage

add_homerange(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Broekman et al. (2023) HomeRange database (Dryad, CC0). Per-individual records are reduced to species medians.

Value

The same data.frame with numeric homerange_home_range_km2 and homerange_body_mass_kg.

References

Broekman MJE et al. (2023) HomeRange: a global database of mammalian home ranges. Dryad. doi:10.5061/dryad.d2547d85x

Examples

taxify("Panthera leo", backend = "gbif") |>
  add_homerange()

Add Lepidoptera hostplant breadth (NHM HOSTS)

Description

Joins per-insect hostplant breadth from the Natural History Museum HOSTS database to a taxify() result by looking up accepted_name. Each moth or butterfly species is summarised by how many distinct hostplants and hostplant families it has been recorded feeding on.

Usage

add_hosts(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Robinson et al. (2010) HOSTS, Natural History Museum, London (CC0). Lepidoptera only; ~24k species with at least one recorded hostplant.

Value

The same data.frame with additional columns:

host_plant_count

Number of distinct hostplant species recorded.

host_family_count

Number of distinct hostplant families recorded.

References

Robinson GS, Ackery PR, Kitching IJ, Beccaloni GW, Hernandez LM (2010) HOSTS - a Database of the World's Lepidopteran Hostplants. Natural History Museum, London. doi:10.5519/havt50xw

Examples

taxify("Papilio machaon", backend = "gbif") |>
  add_hosts()

Add amphibian morphometrics (Huang)

Description

Joins species-level amphibian body measurements to a taxify() result by accepted_name. Only measurements comparable across Anura, Caudata and Gymnophiona are carried; per-specimen values are reduced to species medians.

Usage

add_huang_amph(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Huang amphibian morphological dataset (figshare, CC-BY 4.0).

Value

The same data.frame with numeric huang_amph_svl_mm, huang_amph_head_length_mm, huang_amph_head_width_mm, huang_amph_eye_diameter_mm, huang_amph_forelimb_length_mm, huang_amph_hindlimb_length_mm and categorical huang_amph_taxon_order.

References

Huang et al. A global amphibian morphological trait dataset. figshare. doi:10.6084/m9.figshare.21159229

Examples

taxify("Bufo bufo", backend = "gbif") |>
  add_huang_amph()

Add hybrid parent and type information

Description

Parses the input_name column from a taxify() result to extract hybrid parent names and classify the hybrid type.

Usage

add_hybrid_info(x)

Arguments

Value

The same data.frame with additional columns:

hybrid_parent_1

First parent (full binomial), NA if not a hybrid formula.

hybrid_parent_2

Second parent (full binomial, abbreviated genus expanded), NA if not a hybrid formula.

hybrid_type

One of "nothogenus", "nothospecies", "formula", or NA if not a hybrid.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Quercus pyrenaica x Q. petraea") |>
  add_hybrid_info()

options(old)

Add Italian-lichen taxon-page traits (ITALIC)

Description

Joins per-species morphological and ecological descriptors from ITALIC, the Information System on Italian Lichens, to a taxify() result by looking up accepted_name. One row per species, scraped from the ITALIC 8.0 taxon pages.

Usage

add_italic(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: ITALIC 8.0 (Nimis; Univ. of Trieste), taxon-page descriptors, CC BY-SA 4.0. Lichens are otherwise almost absent from the bundled trait databases.

Value

The same data.frame with additional columns:

growth_form

Thallus growth form (crustose, foliose, fruticose, ...).

substrata

Substrata the species grows on.

photobiont

Photosynthetic partner.

reproductive_strategy

Reproductive strategy.

References

Nimis PL. ITALIC - The Information System on Italian Lichens, Version 8.0. University of Trieste, Dept. of Biology (https://italic.units.it), accessed 2026-07. System paper: Martellos S, Conti M, Nimis PL (2023) Aggregation of Italian Lichen Data in ITALIC 7.0. Journal of Fungi 9(5):556. doi:10.3390/jof9050556

Examples

taxify("Xanthoria parietina", backend = "gbif") |>
  add_italic()

Add IUCN Red List conservation status

Description

Joins IUCN Red List conservation status to a taxify() result by looking up accepted_name. This is the source-named door for the IUCN Red List; for conservation status reconciled across sources, use add_trait() once more than one source is registered for it.

Usage

add_iucn(x, cols = NULL, verbose = TRUE)

Arguments

Details

Conservation status values are compiled from publicly available sources including GBIF and the IUCN Red List API. Coverage is global across all taxonomic groups (~166k species).

Value

The same data.frame with an additional column:

conservation_status

IUCN category: "LC" (Least Concern), "NT" (Near Threatened), "VU" (Vulnerable), "EN" (Endangered), "CR" (Critically Endangered), "EW" (Extinct in the Wild), "EX" (Extinct), or NA if not assessed.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Panthera tigris", backend = "gbif") |>
  add_iucn()

options(old)

Add seed traits from the Kew Seed Information Database (SER-SID)

Description

Joins species-level seed traits from the Kew Seed Information Database (SER-SID) to a taxify() result by looking up accepted_name.

Usage

add_kew_sid(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Royal Botanic Gardens Kew, Seed Information Database, served as SER-SID (https://ser-sid.org/), CC BY 2.0. Per-record measurements are reduced to per-species medians (numeric) and modes (categorical); a thousand-seed weight in grams equals the per-seed mass in milligrams.

Value

The same data.frame with additional columns. The curated set:

sid_thousand_seed_weight

Thousand-seed weight (grams per 1000 seeds, median of all records).

sid_storage_behaviour

Seed storage behaviour (Orthodox/Recalcitrant/Intermediate/Uncertain).

sid_oil_content_pct

Seed oil content (percent, median).

sid_protein_content_pct

Seed protein content (percent, median).

sid_lifeform

Raunkiaer life-form code as recorded by SID.

With cols = "all" the seed-weight record count (n_seed_weight_records) and modal fruit_type are also attached under their source names. Joined on accepted_name.

References

Royal Botanic Gardens Kew. Seed Information Database (SID). https://ser-sid.org/

Examples

taxify("Quercus robur", backend = "gbif") |>
  add_kew_sid()

Add plant traits from LEDA Traitbase

Description

Joins LEDA Traitbase (Kleyer et al. 2008) plant functional traits to a taxify() result by looking up accepted_name. LEDA provides species-level trait data for NW European plant species, covering life form, dispersal, seed, leaf, and clonality traits.

Usage

add_leda(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: LEDA Traitbase (Kleyer et al. 2008). Coverage: ~8,000 NW European plant species.

The Raunkiaer life form is a bud-position classification system: phanerophyte = buds >25 cm above soil, chamaephyte = buds near soil surface, hemicryptophyte = buds at soil surface, geophyte (cryptophyte) = buds below soil, therophyte = annual that survives as seed.

Value

The same data.frame with additional columns:

raunkiaer_life_form

Primary Raunkiaer life form classification (phanerophyte, chamaephyte, hemicryptophyte, geophyte, therophyte, helophyte, hydrophyte).

raunkiaer_variable

1 if species assigned to multiple Raunkiaer forms, 0 otherwise.

dispersal_type

Primary dispersal type (anemochory, zoochory, hydrochory, autochory, barochory, dysochory).

terminal_velocity_ms

Seed terminal velocity in m/s (species median).

seed_mass_mg

Seed mass in mg (species median). Prefixed with leda_ in the .vtr to avoid collision with Diaz traits.

canopy_height_m

Canopy height in meters (species median).

leaf_mass_mg

Leaf dry mass in mg (species median).

sla_mm2_mg

Specific leaf area in mm^2/mg (species median).

clonal_growth

Capable of clonal growth (1 = yes, 0 = no).

buoyancy

Seed buoyancy classification.

References

Kleyer M et al. (2008) The LEDA Traitbase: a database of life-history traits of the Northwest European flora. Journal of Ecology 96:1266-1274.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Arrhenatherum elatius") |>
  add_leda()

options(old)

Add butterfly traits (LepTraits)

Description

Joins LepTraits 1.0 butterfly life-history and ecological traits to a taxify() result by looking up accepted_name.

Usage

add_leptraits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: LepTraits 1.0 (Shirey et al. 2022, CC0). Coverage: ~12.4k butterfly species globally (Papilionoidea).

Value

The same data.frame with additional columns:

wingspan_mm

Wingspan in mm (midpoint of lower and upper bounds).

voltinism

Number of generations per year.

diapause_stage

Overwintering/diapause life stage.

canopy_affinity

Canopy association category.

edge_affinity

Edge/gap affinity category.

moisture_affinity

Moisture affinity category.

disturbance_affinity

Disturbance affinity category.

n_hostplant_families

Number of host plant families used.

flight_months

Number of months with adult flight activity.

References

Shirey V et al. (2022) LepTraits 1.0: A globally comprehensive dataset of butterfly traits. Scientific Data 9:398.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Vanessa cardui", backend = "gbif") |>
  add_leptraits()

options(old)

Add bacterial and archaeal traits (Madin et al.)

Description

Joins species-level bacterial and archaeal phenotypic and genome traits to a taxify() result by looking up accepted_name.

Usage

add_madin(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Madin et al. (2020, Scientific Data, CC BY 4.0). Coverage: ~14.9k bacterial and archaeal species.

Value

The same data.frame with additional columns:

madin_gram_stain

Gram stain (positive/negative).

madin_metabolism

Metabolism (aerobic/anaerobic/facultative/...).

madin_cell_shape

Cell shape (bacillus/coccus/spiral/...).

madin_motility

Motility (yes/no/flagella/gliding/...).

madin_sporulation

Sporulation (yes/no).

madin_isolation_source

Isolation source category.

madin_growth_temp_c

Recorded growth temperature (degrees Celsius).

madin_optimum_temp_c

Optimum growth temperature (degrees Celsius).

madin_optimum_ph

Optimum growth pH.

madin_genome_size_bp

Genome size (base pairs).

madin_gc_content_pct

Genomic G+C content (percent).

References

Madin JS et al. (2020) A synthesis of bacterial and archaeal phenotypic trait data. Scientific Data 7:170. doi:10.1038/s41597-020-0497-4

Examples

taxify("Escherichia coli", backend = "gbif") |>
  add_madin()

Add bird nest traits (NestTrait)

Description

Joins bird nest-site, nest-structure and nest-attachment indicators to a taxify() result by accepted_name. Each trait is a 0/1 presence flag; a species may carry several flags within a group.

Usage

add_nesttrait(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: NestTrait v2 (Chia et al. 2023, Scientific Data, CC-BY 4.0).

Value

The same data.frame with three collapsed categorical columns (nesttrait_structure, nesttrait_site, nesttrait_attachment, each a pipe-delimited set of modalities for multi-modal species) plus 20 raw 0/1 indicator columns prefixed nesttrait_: brood_parasite, mound_builder, seven ⁠nestsite_*⁠, seven ⁠neststr_*⁠ and four ⁠nestatt_*⁠ flags.

References

Chia SY et al. (2023) A global database of bird nest traits. Scientific Data. doi:10.1038/s41597-023-02837-1

Examples

taxify("Turdus merula", backend = "gbif") |>
  add_nesttrait()

Add NZ marine benthos traits (NZTD)

Description

Joins New Zealand marine benthic-invertebrate functional traits to a taxify() result by accepted_name. Each fuzzy-coded trait is reduced to its dominant modality.

Usage

add_nztd(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: NZTD (Lam-Gordillo et al. 2023, figshare, CC-BY 4.0).

Value

The same data.frame with categorical nztd_ columns: bioturbation, body_size, degree_of_attachment, feeding_mode, living_habit, mobility, morphology, movement_method, rigidity.

References

Lam-Gordillo O et al. (2023) New Zealand Trait Database (NZTD) for marine benthic invertebrates. figshare. doi:10.6084/m9.figshare.21939647

Examples

taxify("Macomona liliana", backend = "gbif") |>
  add_nztd()

Add octocoral traits (Octocoral Trait Database)

Description

Joins soft-coral (octocoral) colony, polyp, skeleton, symbiosis and feeding traits to a taxify() result by accepted_name. Built from long-format records reduced to one value per species.

Usage

add_octocoral(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Octocoral Trait Database v2.2 (Gomez-Gras et al., CC-BY 4.0).

Value

The same data.frame with octocoral_ columns: numeric colony_height, colony_width, tentacles_per_polyp; categorical growth_form, type_of_growth, type_of_skeleton, polyp_retractability, polyp_dimorphism, zooxanthellate, axis_presence, feeding_mechanism, coloniality, skeletal_rigidity, calcareous_sclerites_presence.

References

Octocoral Trait Database v2.2. Zenodo. doi:10.5281/zenodo.14228404

Examples

taxify("Gorgonia ventalina", backend = "gbif") |>
  add_octocoral()

Add odonate behavioural/ecological traits (OPD)

Description

Joins Odonate Phenotypic Database categorical traits to a taxify() result by accepted_name (modal value per species).

Usage

add_odonata(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Odonate Phenotypic Database (Waller et al., Dryad, CC-BY 4.0).

Value

The same data.frame with categorical odonata_territoriality, odonata_flight_mode, odonata_mate_guarding, odonata_habitat_openness, odonata_has_wing_pigment.

References

Waller JT et al. The Odonate Phenotypic Database. Dryad. doi:10.5061/dryad.15pm5qc

Examples

taxify("Calopteryx splendens", backend = "gbif") |>
  add_odonata()

Add mammal life-history traits (PanTHERIA)

Description

Joins PanTHERIA mammal life-history and ecological traits to a taxify() result by looking up accepted_name.

Usage

add_pantheria(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: PanTHERIA (Jones et al. 2009, Ecological Archives, CC0). Coverage: ~5.4k mammal species. Mammals only.

Value

The same data.frame with additional columns:

pantheria_body_mass_g

Adult body mass in grams.

longevity_mo

Maximum longevity in months.

litter_size

Litter size (mean).

gestation_d

Gestation length in days.

weaning_d

Weaning age in days.

home_range_km2

Home range size in km^2.

diet_breadth

Diet breadth (number of diet categories).

habitat_breadth

Habitat breadth (number of habitat types).

References

Jones KE et al. (2009) PanTHERIA: a species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90:2648.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Vulpes vulpes", backend = "gbif") |>
  add_pantheria()

options(old)

Add reef-fish trophic guild (Parravicini)

Description

Joins the consensus reef-fish trophic-guild assignment to a taxify() result by accepted_name. The guild is the modal expert classification.

Usage

add_parravicini(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Parravicini et al. (2020) reef-fish trophic guilds (PLoS Biology, CC-BY 4.0).

Value

The same data.frame with categorical parravicini_trophic_guild.

References

Parravicini V et al. (2020) Delineating reef fish trophic guilds with global gut content data synthesis and phylogeny. PLoS Biology 18:e3000702. doi:10.1371/journal.pbio.3000702

Examples

taxify("Zebrasoma scopas", backend = "gbif") |>
  add_parravicini()

Add pelagic species traits

Description

Joins pelagic fish/cephalopod/gelatinous traits to a taxify() result by accepted_name.

Usage

add_pelagic(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Gleiber et al. (2024) Pelagic Species Trait Database (Borealis, CC-BY 4.0).

Value

The same data.frame with pelagic_ columns: numeric depth_min_m, depth_max_m, temp_min_c, temp_max_c, temp_mean_c, length_min_tl_cm, length_max_tl_cm, trophic_level; categorical vert_habitat, horz_habitat, body_shape, phys_defense, gregarious.

References

Gleiber MR et al. (2024) A trait database for pelagic species. Scientific Data. doi:10.5683/SP3/0YFJED

Examples

taxify("Thunnus albacares", backend = "gbif") |>
  add_pelagic()

Add mammal traits including extinct species (PHYLACINE)

Description

Joins PHYLACINE mammal traits to a taxify() result by looking up accepted_name. PHYLACINE covers extant plus recently and prehistorically extinct mammals; it is offered alongside add_pantheria() and add_combine(), not as a replacement.

Usage

add_phylacine(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: PHYLACINE v1.2 (Faurby et al. 2018, Ecology, CC0). Coverage: ~5.8k mammal species including extinct taxa.

Value

The same data.frame with additional columns:

phylacine_mass_g

Body mass (g).

phylacine_diet_plant_pct

Percent of diet that is plant.

phylacine_diet_vertebrate_pct

Percent of diet that is vertebrate.

phylacine_diet_invertebrate_pct

Percent of diet that is invertebrate.

phylacine_terrestrial

Terrestrial habit (0/1).

phylacine_marine

Marine habit (0/1).

phylacine_freshwater

Freshwater habit (0/1).

phylacine_aerial

Aerial habit (0/1).

phylacine_island_endemicity

Island endemicity class.

phylacine_iucn_status

IUCN status (includes EP = extinct in prehistory, EX, EW).

References

Faurby S et al. (2018) PHYLACINE 1.2: The Phylogenetic Atlas of Mammal Macroecology. Ecology 99:2626. doi:10.1002/ecy.2443

Examples

taxify("Mammuthus primigenius", backend = "gbif") |>
  add_phylacine()

Add Italian plant traits from Pignatti (on demand, via TR8)

Description

Fetches Italian Ellenberg-type indicator values, life form, and chorotype from Pignatti's Flora d'Italia (Pignatti, Menegoni & Pietrosanti 2005) for the species in a taxify() result, using the TR8 package, and joins them by accepted_name. TR8 ships these values bundled, so this works offline.

Usage

add_pignatti(x, verbose = TRUE)

Arguments

Details

These values originate in a copyrighted publication, so taxify does not redistribute them. This function reads the copy bundled in the suggested package TR8 (which redistributes it under TR8's GPL, with attribution); taxify ships none of it and no internet access is required. For European-calibration indicator values see add_eive().

Value

The same data.frame with additional columns:

light_it, temperature_it, continentality_it, moisture_it, reaction_it, nutrients_it, salinity_it

Ellenberg-type indicator values calibrated for the Italian flora (codes; X = indifferent, 0 = not applicable).

life_form_it

Life form for the Italian flora.

chorotype_it

Chorological type (distribution).

References

Pignatti S, Menegoni P, Pietrosanti S (2005) Bioindicazione attraverso le piante vascolari. Braun-Blanquetia 39. Bocci G (2015) TR8: an R package for easily retrieving plant species traits. Methods in Ecology and Evolution 6:347-350.

Examples

old <- options(taxify.data_dir = taxify_example_data())


# add_pignatti() fetches Italian trait data on demand via the TR8 package.
taxify("Abies alba") |>
  add_pignatti()


options(old)

Add amphibian heat tolerance (Pottier)

Description

Joins amphibian upper thermal-limit and body-size summaries to a taxify() result by accepted_name. Per-measurement records are reduced to species medians; heat tolerance pools across metrics and acclimation conditions, so it is an approximate species-level upper thermal limit.

Usage

add_pottier(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Pottier et al. (2022) amphibian heat tolerance database (Scientific Data, CC-BY 4.0).

Value

The same data.frame with numeric columns pottier_heat_tolerance_c, pottier_acclimation_temp_c, pottier_svl_mm, pottier_body_mass_g.

References

Pottier P et al. (2022) A comprehensive database of amphibian heat tolerance. Scientific Data 9:600. doi:10.1038/s41597-022-01704-9

Examples

taxify("Rana temporaria", backend = "gbif") |>
  add_pottier()

Add reef-fish traits (Quimbayo)

Description

Joins Atlantic and Eastern-Pacific reef-fish life-history, ecology and behaviour traits to a taxify() result by accepted_name.

Usage

add_quimbayo(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Quimbayo et al. (2021) reef-fish trait database (ESA data paper; Zenodo, open).

Value

The same data.frame with quimbayo_ columns: numeric body_size_max_cm, aspect_ratio, trophic_level, depth_min_m, depth_max_m, temp_occurrence_mean_c; categorical home_range, diel_activity, water_level, body_shape, mouth_position, diet, spawning, size_group.

References

Quimbayo JP et al. (2021) Life-history traits, geographical range, and conservation aspects of reef fishes. Ecology. doi:10.5281/zenodo.4455016

Examples

taxify("Thalassoma bifasciatum", backend = "gbif") |>
  add_quimbayo()

Add marine protist functional traits (Ramond et al.)

Description

Joins genus-level morphological, behavioural and ecological traits of marine protists to a taxify() result by looking up genus, so any species in a covered genus is annotated.

Usage

add_ramond(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Ramond et al. (SEANOE, CC BY 4.0), functional traits of marine protists. Traits are genus-level; numeric cell size is aggregated by median, categorical traits by mode.

Value

The same data.frame with additional columns. The curated set:

ramond_shape

Cell shape (round, elongated, amoeboid, ...).

ramond_motility

Motility mode (swimmer, floater, gliding, ...).

ramond_ingestion

Ingestion / trophic mode (phagotrophic, ...).

ramond_chloroplast

Chloroplast presence (1 = present).

ramond_symbiontic

Symbiotic relationship (parasite, mutualist, ...).

ramond_colony

Colony form.

ramond_salinity

Salinity preference.

ramond_size_min_um

Minimum cell size (micrometres).

ramond_size_max_um

Maximum cell size (micrometres).

With cols = "all" the full set of behavioural, ecological and symbiosis descriptors is attached under their source names.

References

Ramond P, Siano R, Sourisseau M (2018) Functional traits of marine protists. SEANOE. doi:10.17882/51662

Examples

taxify("Alexandrium", backend = "gbif") |>
  add_ramond()

Add reptile ecological traits and distribution (ReptTraits)

Description

Joins species-level reptile traits from ReptTraits (Oskyrko et al. 2024) to a taxify() result by looking up accepted_name. ReptTraits is built on the Reptile Database taxonomy, so it joins cleanly against the reptiledb backbone (and any backbone that resolves to Reptile Database accepted names).

Usage

add_repttraits(x, cols = NULL, verbose = TRUE)

Arguments

Details

The layer carries a per-species distribution signal – biogeographic realm, elevation range and mean climate – alongside body-size and life-history traits, across all reptiles (snakes, lizards, amphisbaenians, turtles, crocodiles and the tuatara), not lizards only.

Source: ReptTraits v1.2 (Oskyrko et al. 2024, Scientific Data, CC BY 4.0). Coverage: 12,060 reptile species. The biogeographic realm and climate fields give a coarse, realm-level range signal; they are not a fine-grained (TDWG-level) range like the plant ranges used by the region constraint.

Value

The same data.frame with additional columns:

biogeographic_realm

Main biogeographic realm (e.g. Neotropic, Palearctic, Afrotropic, Australo-Pacific, Marine).

microhabitat

Microhabitat (e.g. Terrestrial, Saxicolous, Arboreal).

habitat_type

Habitat type(s) (e.g. Forest, Desert, Wetlands).

elevation_min_m

Minimum recorded elevation in metres.

elevation_max_m

Maximum recorded elevation in metres.

mean_annual_temp_c

Mean annual temperature across the range (degrees Celsius).

insular_endemic

Whether the species is insular/endemic ("Yes"/"No").

body_mass_g

Maximum body mass in grams.

svl_mm

Maximum snout-vent length (straight carapace length for turtles) in mm.

total_length_mm

Maximum total length in mm.

longevity_yr

Maximum longevity in years.

diet

Diet category (e.g. Carnivorous, Herbivorous, Omnivorous).

reproductive_mode

Reproductive mode (oviparous/viviparous/...).

clutch_size

Mean clutch or litter size.

active_time

Activity time (Diurnal/Nocturnal/Cathemeral).

foraging_mode

Foraging mode (ACT active / AMB ambush / Mixed).

References

Oskyrko O, Mi C, Meiri S, Du W (2024) ReptTraits: a comprehensive dataset of ecological traits in reptiles. Scientific Data 11:243. doi:10.1038/s41597-024-03079-5

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Pogona vitticeps", backend = "reptiledb") |>
  add_repttraits()

options(old)

Add phytoplankton cell metrics (Rimet & Druart)

Description

Joins cell-level morphometrics for temperate-lake phytoplankton to a taxify() result by accepted_name.

Usage

add_rimet_phyto(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Rimet & Druart (2018) phytoplankton metrics database (Zenodo, CC-BY 4.0).

Value

The same data.frame with numeric columns rimet_phyto_cell_length_um, rimet_phyto_cell_width_um, rimet_phyto_cell_thickness_um, rimet_phyto_cell_surface_area_um2, rimet_phyto_cell_biovolume_um3.

References

Rimet F, Druart JC (2018) A trait database for phytoplankton of temperate lakes. Zenodo. doi:10.5281/zenodo.1164834

Examples

taxify("Asterionella formosa", backend = "gbif") |>
  add_rimet_phyto()

Add saproxylic beetle morphology (Hagge)

Description

Joins European deadwood-beetle body and appendage morphometrics to a taxify() result by accepted_name.

Usage

add_saproxylic(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Hagge et al. (2021) saproxylic beetle morphology (Dryad, CC0).

Value

The same data.frame with numeric saproxylic_ columns: body_length_mm, body_width_mm, body_height_mm, mass_mg, colour_lightness, head_length_mm, pronotum_length_mm, elytra_length_mm, wing_length_mm, wing_aspect, antenna_length_mm, eye_length_mm.

References

Hagge J et al. (2021) Morphological trait database of European saproxylic beetles. Dryad. doi:10.5061/dryad.2fqz612p3

Examples

taxify("Rhysodes sulcatus", backend = "gbif") |>
  add_saproxylic()

Add aquatic-life traits (SeaLifeBase)

Description

Joins SeaLifeBase morphological and ecological traits to a taxify() result by looking up accepted_name. SeaLifeBase is the non-fish companion to FishBase: molluscs, crustaceans, echinoderms, marine mammals, reptiles and other aquatic organisms. For fishes, use add_fishbase().

Usage

add_sealifebase(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: SeaLifeBase via rfishbase (Palomares & Pauly, CC BY-NC 4.0). Non-fish aquatic life only.

The build-from-source fallback requires the rfishbase package (available on CRAN). Pre-built .vtr files do not require rfishbase.

Value

The same data.frame with additional columns:

sb_body_length_cm

Maximum body length in centimetres.

sb_body_mass_g

Body mass in grams where available.

sb_trophic_level

Trophic level.

sb_depth_min_m

Minimum depth in metres.

sb_depth_max_m

Maximum depth in metres.

sb_vulnerability

Vulnerability index (0–100).

sb_habitat

Habitat type (e.g. benthic, pelagic).

sb_importance

Commercial importance category.

References

Palomares MLD, Pauly D (eds.) (2024) SeaLifeBase. World Wide Web electronic publication, https://www.sealifebase.org.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Octopus vulgaris", backend = "gbif") |>
  add_sealifebase()

options(old)

Add elasmobranch life-history traits (Sharkipedia)

Description

Joins Sharkipedia shark and ray life-history traits to a taxify() result by accepted_name. Long-format observations are reduced to one value per species (numeric traits by median) at build time.

Usage

add_sharkipedia(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Sharkipedia (Mull et al. 2022, Scientific Data, CC-BY 4.0).

Value

The same data.frame with additional columns:

sharkipedia_lmax_cm

Maximum observed length (cm).

sharkipedia_vbgf_linf_cm

von Bertalanffy asymptotic length Linf (cm).

sharkipedia_vbgf_k

von Bertalanffy growth coefficient k (per year).

sharkipedia_vbgf_t0

von Bertalanffy t0 (years).

sharkipedia_length_first_maturity_cm

Length at first maturity (cm).

sharkipedia_length_birth_cm

Length at birth (cm).

sharkipedia_amax_observed_yr

Maximum observed age (years).

sharkipedia_age_first_maturity_yr

Age at first maturity (years).

sharkipedia_uterine_fecundity

Uterine fecundity.

sharkipedia_gestation_length

Gestation length.

sharkipedia_natural_mortality

Natural mortality M.

References

Mull CG et al. (2022) Sharkipedia: a curated open access database of shark and ray life history traits and abundance time-series. Scientific Data 9:559. doi:10.1038/s41597-022-01655-1

Examples

taxify("Carcharodon carcharias", backend = "gbif") |>
  add_sharkipedia()

Add freshwater mussel traits (SHELD)

Description

Joins US freshwater-mussel life-history and host traits to a taxify() result by accepted_name.

Usage

add_sheld(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: SHELD (Hopper et al. 2023, Scientific Data, CC-BY 4.0).

Value

The same data.frame with sheld_ columns: numeric mean_length_mm, max_length_mm, mature_age, max_age, growth_rate, fecundity, n_host_species, n_host_family; categorical brood, marsupial_gills, hermaphrodite, shell_sculpture.

References

Hopper GW et al. (2023) A trait dataset for freshwater mussels of the United States of America. Scientific Data 10:745. doi:10.1038/s41597-023-02635-9

Examples

taxify("Lampsilis cardium", backend = "gbif") |>
  add_sheld()

Add spider traits (World Spider Trait Database)

Description

Joins species-level spider morphometric and ecological traits to a taxify() result by looking up accepted_name. Values are aggregated from the World Spider Trait Database (numeric traits by median, categorical traits by mode); access-restricted source records are excluded.

Usage

add_spider_traits(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: World Spider Trait Database (Pekar et al. 2021, Database, CC BY 4.0). Coverage: ~7.3k spider species. Morphometry is sexually dimorphic in spiders; the value here is the across-record median and is not split by sex.

Value

The same data.frame with additional columns:

spider_body_length_mm

Body length (mm).

spider_prosoma_length_mm

Cephalothorax (prosoma) length (mm).

spider_prosoma_width_mm

Cephalothorax (prosoma) width (mm).

spider_abdomen_length_mm

Abdomen (opisthosoma) length (mm).

spider_leg1_length_mm

Leg I length (mm).

spider_ballooning

Ballooning (aerial dispersal): yes/no.

spider_web_building

Web building: yes/no.

spider_hunting_guild

Hunting guild.

spider_web_type

Web type.

spider_circadian_activity

Circadian activity (diurnal/nocturnal).

spider_stratum

Vertical stratum (habitat layer).

References

Pekar S et al. (2021) The World Spider Trait database: a centralized global open repository for curated data on spider traits. Database 2021:baab064. doi:10.1093/database/baab064

Examples

taxify("Araneus diadematus", backend = "gbif") |>
  add_spider_traits()

Add population density (TetraDENSITY)

Description

Joins species-median terrestrial-vertebrate population density to a taxify() result by accepted_name. Only ind/km2 records are used.

Usage

add_tetradensity(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Santini et al. TetraDENSITY (figshare, CC-BY 4.0). Records in other density units are excluded to avoid mixing.

Value

The same data.frame with numeric tetradensity_density_ind_km2.

References

Santini L et al. TetraDENSITY: a database of population density estimates in terrestrial vertebrates. figshare. doi:10.6084/m9.figshare.5371633

Examples

taxify("Capreolus capreolus", backend = "gbif") |>
  add_tetradensity()

Add freshwater thermal-tolerance traits (ThermoFresh)

Description

Joins species-level critical thermal limits for freshwater fish, invertebrates and amphibians to a taxify() result by looking up accepted_name. All values are in degrees Celsius.

Usage

add_thermofresh(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: the Freshwater thermal-tolerance database (Helena Bayat and contributors, Zenodo, CC BY 4.0). Each source record is one tolerance test; values are reduced to species-level medians per metric.

Value

The same data.frame with additional columns:

thermofresh_ctmax

Critical thermal maximum (degrees C).

thermofresh_ctmin

Critical thermal minimum (degrees C).

thermofresh_lt50

Median lethal temperature (degrees C).

thermofresh_ltmax

Lethal thermal maximum (degrees C).

thermofresh_ltmin

Lethal thermal minimum (degrees C).

References

Freshwater thermal-tolerance database. Zenodo. doi:10.5281/zenodo.14056760

Examples

taxify("Salmo trutta", backend = "gbif") |>
  add_thermofresh()

Add a trait from every source that carries it

Description

Attaches a single harmonized trait (e.g. woodiness, plant height) to a taxify() result, pulling from every enrichment source that provides it and reconciling their differing vocabularies and units. Where the per-source ⁠add_*()⁠ doors each join one dataset, add_trait() is the cross-source verb: you name the trait, it gathers the sources.

Usage

add_trait(
  x,
  trait,
  sources = "all",
  mode = c("coalesce", "wide"),
  combine = NULL,
  priority = NULL,
  verbose = TRUE
)

Arguments

Details

Each source keeps its provenance. The default "coalesce" mode reduces the sources to one value per row plus the columns that document it – its unit, the sources that contributed, how many, and a caution when the sources measure the trait by different methods. The opt-in "wide" mode instead gives every source its own column (⁠<trait>_<source>⁠), so per-source agreement and conflict stay fully visible.

Harmonization is per source: a categorical source is mapped to the trait's shared vocabulary, and a numeric source is converted to the trait's canonical unit. For example, GIFT seed mass (grams) and Diaz et al. seed mass (milligrams) both arrive as milligrams. The mappings and units for a trait are listed by trait_info().

Some sources report the same trait in the right unit but under a different definition (for example AusTraits root diameter is a maximum including coarse roots, while GRooT is fine-root only). Such a source carries a caution in the registry. In mode = "coalesce" with the default combine, a trait whose sources disagree in method is not blended: the most complete source is reported and ⁠<trait>_caution⁠ records the difference. trait_info() lists each source's harmonization note and caution.

A source enrichment that is not installed and cannot be downloaded or built is skipped with a warning, and the trait is assembled from the sources that are available.

Value

The same data.frame with added columns.

mode = "coalesce"

⁠<trait>⁠ (the reduced value); ⁠<trait>_unit⁠ (the canonical unit, numeric traits only); ⁠<trait>_sources⁠ (the source it came from, or the comma-separated contributing sources with an aggregating combine); ⁠<trait>_n⁠ (how many sources backed the value); and, only when a source measured the trait differently, ⁠<trait>_caution⁠ explaining the method difference. To inspect every source, use mode = "wide".

mode = "wide"

One column per source, ⁠<trait>_<source>⁠, each harmonized to the trait's shared vocabulary (categorical) or unit (numeric); ⁠<trait>_unit⁠; and ⁠<trait>_caution⁠ on rows where a cautioned source supplied a value.

Numeric traits are returned in the trait's canonical unit (see trait_info()); rows absent from a source get NA.

See Also

list_traits() to see available traits, trait_info() for a trait's sources and units. The per-source doors (add_zanne(), add_gift(), add_diaz_traits(), add_leda()) join one dataset each.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

# One coalesced value plus its provenance (unit, sources, count):
taxify("Abies alba") |>
  add_trait("seed_mass")

# One column per source, to inspect agreement and conflict:
taxify("Abies alba") |>
  add_trait("woodiness", mode = "wide")

options(old)

Add sex-determination traits (Tree of Sex)

Description

Joins sexual-system and sex-determination traits to a taxify() result by looking up accepted_name. Covers plants, vertebrates and invertebrates; some traits are group-specific (selfing for plants, environmental sex determination for vertebrates, haplodiploidy for invertebrates).

Usage

add_tree_of_sex(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Tree of Sex (Tree of Sex Consortium 2014, Scientific Data, CC0). Coverage: ~37.5k species across plants, vertebrates and invertebrates.

Value

The same data.frame with additional columns:

tos_taxon_group

Source group (plants/vertebrates/invertebrates).

tos_sexual_system

Sexual system (vocabulary differs by group).

tos_karyotype

Sex-chromosome system (XY/ZW/XO/homomorphic/...).

tos_genotypic

Heterogamety (male/female heterogametic/GSD/...).

tos_molecular_basis

Molecular basis (Y dominant/W dominant/dosage).

tos_selfing

Selfing (plants; self compatible/incompatible).

tos_environmental_sd

Environmental sex determination (vertebrates; TSD/...).

tos_haplodiploidy

Haplodiploidy (invertebrates).

References

The Tree of Sex Consortium (2014) Tree of Sex: a database of sexual systems. Scientific Data 1:140015. doi:10.1038/sdata.2014.15

Examples

taxify("Silene latifolia", backend = "gbif") |>
  add_tree_of_sex()

Add fungal host breadth (USDA Fungus-Host Dataset)

Description

Joins per-fungus host breadth from the USDA National Fungus Collections Fungus-Host Dataset to a taxify() result by looking up accepted_name. Each fungus species is summarised by how many distinct host plants and host plant genera it has been recorded on.

Usage

add_usda_fungus_host(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Farr, Rossman & Castlebury (2021) United States National Fungus Collections Fungus-Host Dataset, Ag Data Commons (U.S. Public Domain). Fungi only; ~99k species with at least one recorded host.

Value

The same data.frame with additional columns:

fungus_host_count

Number of distinct host plant species recorded.

fungus_host_genus_count

Number of distinct host plant genera recorded.

References

Farr DF, Rossman AY, Castlebury LA (2021) United States National Fungus Collections Fungus-Host Dataset. Ag Data Commons. doi:10.15482/USDA.ADC/1524414

Examples

taxify("Puccinia graminis", backend = "gbif") |>
  add_usda_fungus_host()

Add human-use categories (World Checklist of Useful Plant Species)

Description

Joins plant human-use categories to a taxify() result by looking up accepted_name. Each of the ten Level-1 use categories is a 0/1 flag, plus a crop-wild-relative flag.

Usage

add_useful_plants(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: World Checklist of Useful Plant Species (Diazgranados et al. 2020, KNB, CC BY 4.0). Coverage: ~39k plant species.

Value

The same data.frame with additional columns:

useful_animal_food

Animal food (0/1).

useful_environmental_uses

Environmental uses (0/1).

useful_fuels

Fuels (0/1).

useful_gene_sources

Gene sources (0/1).

useful_human_food

Human food (0/1).

useful_invertebrate_food

Invertebrate food (0/1).

useful_materials

Materials (0/1).

useful_medicines

Medicines (0/1).

useful_poisons

Poisons (0/1).

useful_social_uses

Social uses (0/1).

useful_crop_wild_relative

Crop wild relative (0/1).

References

Diazgranados M et al. (2020) World Checklist of Useful Plant Species. Knowledge Network for Biocomplexity. doi:10.5063/F1CV4G34

Examples

taxify("Acorus calamus", backend = "gbif") |>
  add_useful_plants()

Add WCVP native range status

Description

Joins WCVP (World Checklist of Vascular Plants, Kew) native range data to a taxify() result, filtered by TDWG botanical region.

Usage

add_wcvp(x, region, cols = NULL, verbose = TRUE)

Arguments

Details

Source: WCVP (Kew, CC BY). Coverage: ~340k plant species. Plants only.

Value

The same data.frame with additional column(s):

native_status

One of "native", "introduced", "extinct", or NA if not recorded for that region.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Quercus robur") |>
  add_wcvp(region = "EUR")

taxify("Quercus robur") |>
  add_wcvp(region = c("EUR", "NAM"))

options(old)

Add WFO-specific columns

Description

Joins extra World Flora Online columns to a taxify() result by looking up taxon_id in the WFO backbone.

Usage

add_wfo_info(x)

Arguments

Value

The same data.frame with additional columns:

scientificNameID

WFO scientificNameID.

parentNameUsageID

WFO parentNameUsageID.

namePublishedIn

Publication reference.

higherClassification

Higher classification string.

taxonRemarks

Taxonomic remarks.

infraspecificEpithet

Infraspecific epithet (for subspecies, varieties, forms).

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Quercus robur") |>
  add_wfo_info()

options(old)

Add woodiness (Zanne et al. 2014)

Description

Joins the woody / herbaceous classification of Zanne et al. (2014) to a taxify() result by looking up accepted_name. This is the source-named door for the Zanne Global Woodiness Database; for woodiness reconciled across every source that carries it (Zanne, GIFT), use add_trait() with "woodiness".

Usage

add_zanne(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Zanne et al. 2014, Nature (Dryad, CC0). Coverage: ~50k plant species. Plants only.

Value

The same data.frame with an additional column:

woodiness

One of "woody", "herbaceous", "variable", or NA if not in the dataset.

References

Zanne AE et al. (2014) Three keys to the radiation of angiosperms into freezing environments. Nature 506:89-92.

See Also

add_trait() for woodiness harmonized across sources.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

taxify("Quercus robur") |>
  add_zanne()

options(old)

Add marine zooplankton traits

Description

Joins global marine-zooplankton traits to a taxify() result by accepted_name (species-level summaries).

Usage

add_zooplankton(x, cols = NULL, verbose = TRUE)

Arguments

Details

Source: Pata & Hunt global marine zooplankton trait database (Zenodo, CC-BY-SA 4.0).

Value

The same data.frame with zooplankton_ columns: numeric body_length_max_mm, carbon_weight_mg, nitrogen_pdw_pct; categorical vertical_distribution, reproduction_mode, trophic_group, feeding_mode, myelination, habitat_association, diel_vertical_migration, bioluminescence.

References

Pata PR, Hunt BPV (2025) A global trait database for marine zooplankton. Zenodo. doi:10.5281/zenodo.8102913

Examples

taxify("Calanus finmarchicus", backend = "gbif") |>
  add_zooplankton()

List the accepted taxa within a genus or family

Description

Returns the accepted taxa a backbone places inside a genus or family, so you can build a checklist from the backbone rather than only validating one. The parent is auto-detected: a genus is tried first, then a family.

Usage

children(taxon, backend = "wfo", rank = "species", verbose = TRUE)

Arguments

Value

A data.frame of accepted taxa, columns: name, authorship, rank, family, genus, taxon_id, parent_rank ("genus" or "family"), backend. Empty if the parent is not found.

See Also

synonyms(), taxify().

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

children("Quercus")

options(old)

Cite data sources used in a taxify result

Description

Prints formatted citations for the taxonomic backbone(s), enrichment layers, and the taxify package itself. Optionally writes a BibTeX file.

Usage

cite(x, file = NULL)

Arguments

Value

x, invisibly (pipe-friendly).

Examples

result <- taxify("Quercus robur", backend = "wfo")
result |> cite()
result |> cite(file = tempfile(fileext = ".bib"))

Embed accepted taxon info at build time (synonym self-join)

Description

Used by the taxifydb build pipeline and by taxify's own test fixtures. For every synonym row, resolves the accepted taxon and embeds its name, family, genus, and (when authorship_col is supplied) authorship directly. Handles synonym chains by iterating until stable (max 10 hops).

Usage

embed_accepted(
  df,
  id_col,
  acc_id_col,
  name_col,
  family_col,
  genus_col,
  status_col,
  synonym_pattern = "SYNONYM",
  authorship_col = NULL
)

Arguments

Value

The data.frame with added columns: accepted_name, accepted_family, accepted_genus, accepted_taxon_id, accepted_authorship, is_synonym.

Browse the trait columns an enrichment door can attach

Description

Lists the columns available from an enrichment's pre-built .vtr, so you can choose which to attach through the doors that accept a cols argument (such as add_gift() and add_floraweb()). Read offline from the local .vtr; the first call may trigger the one-time download.

Usage

enrichment_cols(source)

Arguments

Value

A data.frame with one row per column: column (the name) and type ("numeric" or "character").

See Also

add_gift(), add_floraweb(), list_enrichments()

Examples

old <- options(taxify.data_dir = taxify_example_data())
enrichment_cols("gift")
options(old)

Export a taxify result to file

Description

Writes a taxify() result (with any enrichments) to disk in one of several formats. The default .vtr format preserves column types and is fast to re-read with add_data().

Usage

export_data(x, path, overwrite = FALSE)

Arguments

Value

Invisibly returns path.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

result <- taxify(c("Quercus robur", "Pinus sylvestris"))
result |> export_data(tempfile(fileext = ".vtr"))
result |> export_data(tempfile(fileext = ".csv"))
result |> export_data(tempfile(fileext = ".tsv"))

options(old)

Browse the bundled GIFT trait columns

Description

Returns the species-level trait columns available from the bundled GIFT enrichment, so you can pick which to attach in add_gift(). Read offline from the local .vtr (downloaded or built once); the first call may trigger that one-time download.

Usage

gift_traits()

Value

A data.frame with one row per trait column:

column

The ⁠gift_<trait>⁠ column name.

type

"numeric" or "character".

See Also

add_gift(), enrichment_cols() for the same listing on any enrichment.

Examples

old <- options(taxify.data_dir = taxify_example_data())
gift_traits()
options(old)

Inspect a name list for probable typos and other anomalies

Description

A quality-control pass over a name list. By default inspect() does not match names against backbones: on a plain character vector it runs the checks that need no matching – the genus register and the rest of the batch – and is fast and offline. To also surface the match-based anomalies (typo, synonym, ambiguous, geographic), either set backbones = TRUE (matches against every installed backbone, listed in the report) or match yourself first and inspect the result (taxify(x) |> inspect()). Either way it returns only the rows that look anomalous, each labelled with what stands out and, where known, the name to use instead.

Usage

inspect(
  x,
  backbones = FALSE,
  region = NULL,
  coords = NULL,
  range = c("present", "native", "introduced"),
  min_tier = c("note", "review", "unresolved"),
  verbose = TRUE
)

Arguments

Details

Checks that need no matching (run on a character vector or a result):

unknown

The genus is not in the genus register – the union of all 13 backbones' genera – so no backbone recognises it. The strong "probably not a real name" signal.

near_duplicate

A near-twin of a more frequent name in the same list (small edit distance), so probably a misspelling of it. Computed from the list alone, so it catches typos in names no backbone contains.

outlier_group

The name's kingdom group (from the register) is a tiny minority of an otherwise group-coherent list – the lone animal or fungus among plants, typically a cross-kingdom homonym typo.

Checks read from a taxify() result (only present when you inspect one):

typo

Resolved only after fuzzy correction (match_type = "fuzzy"): the input most likely contains a spelling error; suggestion is the name.

ambiguous

A homonym resolving to more than one accepted taxon.

geographic

The matched species is real but has no WCVP record in the declared region / coords (vascular plants only).

out_of_range

No region declared, yet the matched species' range falls outside the list's main TDWG continents (skipped for globally spread lists).

case

Resolved only after ignoring case (match_type = "exact_ci").

synonym

The input is an outdated synonym; suggestion is the current accepted name.

Rows with no anomaly are dropped.

Each row gets a tier describing what it needs, not how bad it is: unresolved (no usable name – act on it), review (a name is there but its identity is uncertain – verify it), or note (correct, optional cleanup). unknown is unresolved; the identity-uncertain labels are review; case and synonym are note. An anomaly may be intended, so the tier is a triage hint, not a verdict.

The list-context labels (near_duplicate, out_of_range, outlier_group) judge a name against the rest of the batch, so they cannot apply to a single name: inspect() on one name warns and reports only the per-name labels. The register checks (unknown, and the register-derived outlier_group) need the genus register installed; without it they are skipped (with a message at verbose).

Value

A taxify_inspection data.frame (one row per anomalous name, ordered most-notable first) with columns input_name, suggestion (the name to use instead, or NA), anomalies (|-joined labels), tier (ordered factor note < review < unresolved), reason, fuzzy_dist, and backend. Zero rows means nothing stood out.

See Also

taxify(), taxify_regions()

Examples

old <- options(taxify.data_dir = taxify_example_data())

# On raw names: register + list checks (no matching)
inspect(c("Quercus robur", "Bogusus fakus", "Carexus mysteriosa",
          "Carexus mysteriosa", "Carexus mysteryosa"))

# Opt in to matching to also get typos, synonyms, ambiguity
inspect(c("Quercus robur", "Quercus robus"), backbones = TRUE)

# Or match yourself and inspect the result
taxify(c("Quercus robur", "Quercus robus")) |> inspect()

options(old)

Test whether a canonical name carries an aggregate marker

Description

TRUE for names ending in any aggregate marker spelling (agg., aggr., -agg, s.l., ⁠sensu lato⁠, ⁠coll. sp.⁠). Exported for the taxifydb build pipeline so it can keep aggregate source rows out of cross-backbone name expansion (which would otherwise leak an aggregate trait onto the binomial species key).

Usage

is_aggregate_name(x)

Arguments

Value

Logical vector; FALSE for NA.

List available enrichments

Description

Returns a summary of all enrichment layers available in the taxify manifest, including version, row count, whether the dataset is static, and which trait columns are provided.

Usage

list_enrichments(verbose = TRUE)

Arguments

Value

A data.frame with columns: name, version, nrow, static, trait_cols (comma-separated), and source_url.

Examples

list_enrichments()

List the traits available to add_trait()

Description

Returns the traits that add_trait() can attach across sources, with their kind, canonical unit, and the number and names of contributing sources.

Usage

list_traits()

Value

A data.frame with one row per trait:

trait

The trait name to pass to add_trait().

label

Human-readable label.

kind

"numeric" or "categorical".

unit

Canonical unit for numeric traits, NA for categorical.

n_sources

Number of sources providing the trait.

sources

Comma-separated source names.

See Also

add_trait(), trait_info()

Examples

list_traits()

Look up a genus in the register

Description

Returns the register row for the given genus, or NULL if not found. Auto-loads the register on first call.

Usage

lookup_genus(genus)

Arguments

Value

A one-row data.frame, or NULL if the genus is not in the register.

Normalize aggregate markers on canonical names (build-time)

Description

Folds every aggregate marker a backbone or enrichment source may use to one canonical form, "<binomial> aggr.", so taxify's matching engine and enrichment join recognize aggregates uniformly regardless of source spelling. Two cases are handled:

• a name already carrying a marker (agg., aggr., -agg, s.l., ⁠sensu lato⁠, ⁠coll. sp.⁠) is rewritten to "<binomial> aggr.";

• a name at an aggregate rank (taxon_rank such as "SPECIES AGGREGATE", "AGGR.", "COLL. SP.") that carries no marker gets " aggr." appended.

Exported for the taxifydb build pipeline so the build and runtime sides share one definition.

Usage

normalize_aggregate_name(name, rank = NULL)

Arguments

Value

name with aggregate markers normalized to " aggr.".

Vectorized Latin orthographic normalization

Description

Reduces common Latin spelling alternations to a canonical form so that e.g. hirtaeformis and hirtiformis produce the same normalized key. Applied identically to both query names and backbone names so the keys line up on either side of the join.

Usage

normalize_epithets(names)

Arguments

Details

Pipeline:

1. Lowercase.

2. Strip Latin-1 diacritics and ligatures (e-acute to e, ae-ligature to ae, sharp-s to ss, etc.), applied to genus and epithet.

3. Orthographic alternation on the epithet only: ae/oe -> i, trailing ii -> i, y -> i, ph -> f, rh -> r, th -> t.

Step 2 runs before step 3, so ae-ligature -> ae -> i and oe-ligature -> oe -> i fold into the same key as the de-ligatured forms.

Value

Character vector of normalized forms.

Precompute matching keys at build time

Description

Used by the taxifydb build pipeline and by taxify's own test fixtures. Adds key_ci, key_normalized, key_species, and fuzzy_block columns to the backbone data.frame for direct lookup at query time.

Usage

precompute_keys(df, name_col, genus_col, epithet_col)

Arguments

Value

The data.frame with added key columns.

Print a taxify inspection report

Description

Print a taxify inspection report

Usage

## S3 method for class 'taxify_inspection'
print(x, ...)

Arguments

Value

x, invisibly.

Print a taxify_result

Description

Delegates to the standard data.frame print method.

Usage

## S3 method for class 'taxify_result'
print(x, ...)

Arguments

Value

x, invisibly.

Geographic range constraint for fuzzy matching

Description

These helpers restrict fuzzy match candidates to a user-declared geographic region, using WCVP (World Checklist of Vascular Plants) per-species native status keyed on TDWG Level 3 botanical regions. The fuzzy filter itself is a categorical join on tdwg_code. User-facing inputs are resolved to TDWG Level 3 codes before that join: a code is used directly, a region name ("Belgium", "Europe") is looked up in the bundled WGSRPD crosswalk, and coordinates (c(lon, lat)) are mapped to codes by point-in-polygon against the WGSRPD Level 3 boundaries. Only fuzzy candidates are constrained; exact matches are always trusted.

Score match candidates by resolution priority

Description

Computes the per-row priority scores used to rank backbone candidates for a name (smaller is better): ACCEPTED over SYNONYM (status_score), SPECIES over higher ranks (rank_score), nomenclaturally Valid (valid_score), and epithet-preserving accepted target (epithet_score, the homotypic basionym among same-name homonym synonyms, e.g. ⁠Pinus abies⁠ -> ⁠Picea abies⁠). Used by the matching engine's best-match selection and, in the taxifydb build pipeline, to collapse each backbone key to the single accepted name taxify() resolves it to.

Usage

score_candidates(candidates)

Arguments

Value

A list with integer vectors status_score, rank_score, valid_score, epithet_score, and the character tier signature ("status/rank/valid/epithet") per row, in input order.

Summarise a taxify_result

Description

Prints a compact digest of match quality and life-form scope to the console. Uses cat() so output is captured by capture.output() and rendered correctly in knitr chunks.

Usage

## S3 method for class 'taxify_result'
summary(object, ...)

Arguments

Value

object, invisibly.

List the synonyms of a name

Description

The reverse of the forward resolution taxify() does: each input name is resolved to its accepted taxon, then every synonym that points to that accepted taxon in the backbone is returned. Useful for auditing which historical names collapse onto a current name.

Usage

synonyms(x, backend = "wfo", verbose = TRUE)

Arguments

Value

A data.frame with one row per synonym found, columns:

input_name

The queried name.

accepted_name

The accepted name the query resolved to.

synonym

A synonym of that accepted taxon.

authorship

Authorship of the synonym.

rank

Rank of the synonym.

taxon_id

Backend ID of the synonym.

backend

Backend used.

Names that resolve to an accepted taxon with no synonyms contribute no rows.

See Also

taxify() for the forward direction, children() to list the accepted taxa within a genus or family.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

# Amphibolurus vitticeps is a synonym of Pogona vitticeps
synonyms("Pogona vitticeps", backend = "reptiledb")

options(old)

Match taxonomic names against local backbone databases

Description

Matches a vector of taxonomic names against locally stored Darwin Core backbone databases. Returns a data.frame with one row per input name containing the matched name, accepted name, taxonomic hierarchy, and match quality information.

Usage

taxify(
  x,
  backend = "wfo",
  fuzzy = TRUE,
  fuzzy_threshold = 0.2,
  fuzzy_method = c("dl", "levenshtein", "jw"),
  aggregates = c("preserve", "collapse"),
  region = NULL,
  coords = NULL,
  range = c("present", "native", "introduced"),
  verbose = TRUE
)

Arguments

Details

When multiple backends are specified, names are matched against each backend in order. Names matched by an earlier backend are not re-matched by later ones (fallback chain).

Value

A data.frame with one row per input name and the following columns:

input_name

The original name as provided.

matched_name

Full name in the backbone that matched.

accepted_name

Resolved accepted name (equals matched_name if not a synonym).

taxon_id

Backend-specific ID of the matched name.

accepted_id

ID of the accepted name.

rank

Taxonomic rank (species, subspecies, genus, etc.).

family

Family name.

genus

Genus name.

epithet

Specific epithet.

authorship

Authorship of the matched name.

accepted_authorship

Authorship of the accepted name. For a synonym this is the author of the resolved accepted name, not the synonym's own author, so accepted_name and accepted_authorship together form the accepted name's full citation.

is_synonym

Logical. Was the match a synonym?

is_hybrid

Logical. Was a hybrid marker detected in the input?

qualifier

Canonical taxonomic qualifier found in the input name ("cf.", "aff.", "agg.", "s.l.", "s.str.", "sp.", ...), or NA. Spelling variants are folded to one token ("aggr.", "agg" and "sensu lato" all map to "agg."/"s.l.").

qualifier_position

"genus" when the qualifier leads the name and qualifies the whole name (e.g. "Cf. Pinus sylvestris"), "species" when it qualifies the species (inline cf. or trailing agg.), NA when there is no qualifier.

aggregate_fallback

Logical. For an aggregate query under aggregates = "preserve": FALSE when it resolved to the backbone's dedicated aggregate taxon, TRUE when no such taxon existed and it fell back to the nominal binomial. NA for non-aggregate queries and under aggregates = "collapse", where the collapse is explicit.

match_type

One of "exact", "exact_ci", "fuzzy", "abbrev" (an abbreviated genus such as "Q. robur" resolved via genus initial plus epithet), or "none".

fuzzy_dist

Normalized string distance (0–1), NA if exact.

is_ambiguous

Logical. TRUE when the matched scientificName had multiple synonym rows pointing to different accepted taxa at the same priority tier (homonym ambiguity). Disambiguated via nomenclaturalStatus = "Valid" when that column is in the backbone; for irreducible ambiguity, the scalar columns hold one candidate.

ambiguous_targets

Character. |-joined list of conflicting accepted taxon IDs when is_ambiguous = TRUE; NA otherwise.

backend

Which backend was used (e.g., "wfo", "col", "gbif").

backbone_version

Backend name, version, and download date (e.g., "wfo:2024-12 (2026-04-01)"). Useful for reproducibility.

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

# Match a few names
taxify(c("Quercus robur", "Pinus sylvestris"))

# Disable fuzzy matching
taxify("Quercus robus", fuzzy = FALSE)

# Constrain fuzzy candidates to a geographic region: a TDWG Level 3 code,
# or a region name resolved via the bundled WGSRPD crosswalk
taxify("Quercus robus", region = "EUR")
taxify("Quercus robus", region = "Belgium")

# Constrain by coordinates (downloads WGSRPD boundaries on first use)
## Not run: 
taxify("Quercus robus", coords = c(4.35, 50.85))

## End(Not run)

# Fallback chain: try WFO first, then COL for unmatched
taxify(c("Quercus robur", "Panthera leo"),
       backend = c("wfo", "col"))

options(old)

Expand ambiguous matches into their candidate taxa

Description

Where taxify() meets an irreducible homonym – a name whose synonyms point to several accepted taxa at the same priority tier – it records one candidate in the scalar columns, sets is_ambiguous = TRUE, and lists the conflicting accepted taxon IDs in ambiguous_targets. This verb expands those rows into one row per candidate, resolved to full names against the backbone, so you can choose the right taxon yourself instead of relying on the automatic tiebreak.

Usage

taxify_candidates(x, verbose = TRUE)

Arguments

Value

A data.frame with one row per (ambiguous input, candidate taxon):

input_name

The queried name.

chosen

The accepted name taxify() picked for that row.

candidate

A candidate accepted name.

authorship

Authorship of the candidate.

rank

Rank of the candidate.

family

Family of the candidate.

genus

Genus of the candidate.

taxon_id

Backend ID of the candidate.

backend

Backend used.

Empty when no rows were ambiguous.

See Also

taxify(), synonyms().

Examples

# Runs offline against the bundled example database.
old <- options(taxify.data_dir = taxify_example_data())

# Homonyms are rare; on an unambiguous result this is an empty frame.
taxify("Quercus robur") |>
  taxify_candidates()

options(old)

Clear all cached backbones

Description

Removes all loaded backbone handles from memory. The next call to taxify() will re-load from disk.

Usage

taxify_clear_cache()

Value

No return value, called for side effects.

Get the taxify data directory

Description

Returns the directory where taxify stores downloaded backbone and enrichment .vtr files. By default this is the platform-appropriate per-user cache returned by tools::R_user_dir() (available since R 4.0).

Usage

taxify_data_dir()

Details

The location can be overridden, in order of precedence, by the taxify.data_dir option (getOption("taxify.data_dir")) or the TAXIFY_DATA_DIR environment variable. This is useful to point taxify at a shared cache, or at the small bundled example database returned by taxify_example_data().

Value

Character string. Path to the data directory.

Build a backbone database from source

Description

Builds the backbone .vtr for a backend from its upstream Darwin Core source, delegating to the sibling taxifydb package (which must be installed). This is the from-source path, for rebuilding a backbone locally.

Usage

taxify_download(backend, dest = NULL, verbose = TRUE, ...)

Arguments

Details

For everyday use you do not need this: taxify() auto-downloads the pre-built .vtr on first use, and taxify_download_vtr() fetches a pre-built backbone directly without taxifydb.

Value

The path to the .vtr file (invisibly).

See Also

taxify_download_vtr() to fetch a pre-built backbone, taxify() which downloads on first use.

Download one or more enrichment .vtr files

Description

Downloads pre-built enrichment .vtr files from the taxify manifest.

Usage

taxify_download_enrichment(enrichment, version = "latest", verbose = TRUE)

Arguments

Details

Available enrichments:

iucn

IUCN conservation status (LC/NT/VU/EN/CR/EW/EX)

griis

GRIIS invasive species status by country

zanne

Zanne et al. 2014 woody/herbaceous classification

wcvp

WCVP native range by TDWG botanical region

eive

EIVE 1.0 ecological indicator values (European plants)

diaz_traits

Diaz et al. 2022 seed mass and plant height

elton_traits

EltonTraits 1.0 diet and foraging (birds + mammals)

avonet

AVONET bird morphology and migration

pantheria

PanTHERIA mammal life-history traits

common_names

GBIF vernacular names (multi-language)

amphibio

AmphiBIO amphibian life-history and ecological traits

leda

LEDA Traitbase NW European plant traits (Kleyer et al. 2008)

Value

The path(s) to the downloaded .vtr file(s) (invisibly).

Download a pre-built taxify backbone

Description

Downloads a pre-built .vtr backbone from GitHub Releases using the taxify manifest. This needs no build tools and does not require taxifydb; it is the fast path taxify() uses internally on first use. Call it directly to pre-fetch backbones before an offline session. Progress is always shown; no prompts are shown, so calling this function is consent.

Usage

taxify_download_vtr(backend = "wfo", version = "latest", verbose = TRUE)

Arguments

Value

The path(s) to the downloaded .vtr file(s) (invisibly).

See Also

taxify_download() to build a backbone from source via taxifydb, taxify_download_enrichment() for enrichment layers.

Path to the bundled example database

Description

taxify ships a tiny example database (a handful of species per backbone plus matching enrichment tables) so that examples and quick experiments run offline, without downloading the full multi-million-row backbones.

Usage

taxify_example_data()

Details

Point taxify at it for the current session by setting the taxify.data_dir option:

old <- options(taxify.data_dir = taxify_example_data())
taxify("Quercus robur") |> add_zanne()
options(old)  # restore the real data directory

The example database is read-only and covers only the species used in the package examples; use the full downloaded backbones for real work.

Value

Character string. Path to the bundled example database directory, or "" if it is not installed.

See Also

taxify_data_dir()

Load the unified genus register into memory

Description

Reads genus_register.vtr from disk and caches it as a data.frame in .taxify_env$register. Subsequent calls reuse the cached version unless force = TRUE.

Usage

taxify_load_register(force = FALSE, verbose = TRUE)

Arguments

Details

The register contains one row per genus with columns: genus, kingdom, phylum, class, order, family, life_form.

Value

The register data.frame (invisibly).

Reshape grouped enrichment columns to long format

Description

Converts wide-format columns produced by grouped enrichments (e.g., invasive_status_AT, invasive_status_DE) back to long format with one row per species x group combination.

Usage

taxify_long(x, cols = NULL, group_col = NULL, drop_na = FALSE)

Arguments

Details

When cols and group_col are omitted, taxify_long() reads the reshape metadata attached by grouped enrichment functions (add_griis(), add_alien_first_records(), add_wcvp(), add_common_names()). If multiple grouped enrichments were applied, all are reshaped together (they must share the same group column).