Advanced search and citation of occurrences

Hannah L. Owens

Cory Merow

Brian Maitner

Jamie M. Kass

Vijay Barve

Robert Guralnick

2026-09-01

Advanced features

This vignette demonstrates more advanced features and customization available in occCite. We recommend you read vignette("Simple.Rmd", package = "occCite") first, if you have not already done so.

Loading data from previous GBIF searches

Querying GBIF can take quite a bit of time, especially for multiple species and/or well-known species. In this case, you may wish to access previously-downloaded data sets from your computer by specifying the general location of your downloaded .zip files. occQuery will crawl through your specified GBIFDownloadDirectory to collect all the .zip files contained in that folder and its subfolders. It will then import the most recent downloads that match your taxon list. These GBIF data will be appended to a BIEN search the same as if you do the simple real-time search (if you chose BIEN as well as GBIF), as was shown above. checkPreviousGBIFDownload is TRUE by default, but if loadLocalGBIFDownload is TRUE, occQuery will ignore checkPreviousDownload. It is also worth noting that occCite does not currently support mixed data download sources. That is, you cannot do GBIF queries for some taxa, download previously-prepared data sets for others, and load the rest from local data sets on your computer.

# Simple search
myOldOccCiteObject <- occQuery(x = "Protea cynaroides",
                                  datasources = c("gbif", "bien"),
                                  GBIFLogin = GBIFLogin, 
                                  GBIFDownloadDirectory = 
                                    system.file('extdata/', package='occCite'),
                                  checkPreviousGBIFDownload = T)

Here is the result. Look familiar?

#GBIF search results
head(myOldOccCiteObject@occResults$`Protea cynaroides`$GBIF$OccurrenceTable);
##                name longitude  latitude coordinateUncertaintyInMeters day month
## 1 Protea cynaroides  18.43928 -33.95440                             8  17     2
## 2 Protea cynaroides  22.12754 -33.91561                             4  11     2
## 3 Protea cynaroides  18.43927 -33.95429                             8  17     2
## 4 Protea cynaroides  18.43254 -34.29275                            31   6     2
## 5 Protea cynaroides  18.42429 -34.02934                          2167  10     2
## 6 Protea cynaroides  18.43529 -34.10545                             2   8     2
##   year                           datasetKey dataService
## 1 2022 50c9509d-22c7-4a22-a47d-8c48425ef4a7        GBIF
## 2 2022 50c9509d-22c7-4a22-a47d-8c48425ef4a7        GBIF
## 3 2022 50c9509d-22c7-4a22-a47d-8c48425ef4a7        GBIF
## 4 2022 50c9509d-22c7-4a22-a47d-8c48425ef4a7        GBIF
## 5 2022 50c9509d-22c7-4a22-a47d-8c48425ef4a7        GBIF
## 6 2022 50c9509d-22c7-4a22-a47d-8c48425ef4a7        GBIF
##                               datasetName
## 1 iNaturalist Research-grade Observations
## 2 iNaturalist Research-grade Observations
## 3 iNaturalist Research-grade Observations
## 4 iNaturalist Research-grade Observations
## 5 iNaturalist Research-grade Observations
## 6 iNaturalist Research-grade Observations
#The full summary
summary(myOldOccCiteObject)
##  
##  OccCite query occurred on: 20 June, 2024
##  
##  User query type: User-supplied list of taxa.
##  
##  Sources for taxonomic rectification: GBIF Backbone Taxonomy
##      
##  
##  Taxonomic cleaning results:     
## 
##          Input Name                Best Match Taxonomic Databases w/ Matches
## 1 Protea cynaroides Protea cynaroides (L.) L.         GBIF Backbone Taxonomy
##  
##  Sources for occurrence data: gbif, bien
##      
##                     Species Occurrences Sources
## 1 Protea cynaroides (L.) L.        2334      17
##  
##  GBIF dataset DOIs:  
## 
##                     Species GBIF Access Date           GBIF DOI
## 1 Protea cynaroides (L.) L.       2022-03-02 10.15468/dl.ztbx8c

Getting citation data works the exact same way with previously-downloaded data as it does from a fresh data set.

#Get citations
myOldOccCitations <- occCitation(myOldOccCiteObject)
print(myOldOccCitations)
## Writing 5 Bibtex entries ... OK
## Results written to file 'temp.bib'
## AFFOUARD A, JOLY A, LOMBARDO J, CHAMP J, GOEAU H, CHOUET M, GRESSE H, BONNET P (2025). Pl@ntNet observations. Version 1.9. Pl@ntNet. https://doi.org/10.15468/gtebaa. Accessed via GBIF on 2022-03-02.
## AFFOUARD A, JOLY A, LOMBARDO J, CHAMP J, GOEAU H, CHOUET M, GRESSE H, BOTELLA C, BONNET P (2023). Pl@ntNet automatically identified occurrences. Version 1.8. Pl@ntNet. https://doi.org/10.15468/mma2ec. Accessed via GBIF on 2022-03-02.
## Chamberlain, S., Barve, V., Mcglinn, D., Oldoni, D., Desmet, P., Geffert, L., Ram, K. (2026). rgbif: Interface to the Global Biodiversity Information Facility API. R package version 3.8.5.13. https://CRAN.R-project.org/package = rgbif.
## Chamberlain, S., Boettiger, C. (2017). R Python, and Ruby clients for GBIF species occurrence data. PeerJ PrePrints.
## Fatima Parker-Allie, Ranwashe F (2018). PRECIS. South African National Biodiversity Institute. https://doi.org/10.15468/rckmn2. Accessed via GBIF on 2022-03-02.
## MNHN, Chagnoux S (2025). The vascular plants collection (P) at the Herbarium of the Muséum national d'Histoire Naturelle (MNHN - Paris). Version 69.422. MNHN - Museum national d'Histoire naturelle. https://doi.org/10.15468/nc6rxy. Accessed via GBIF on 2022-03-02.
## MNHN. Accessed via BIEN on NA.
## Maitner, B. (2026). . R package version 1.2.8. https://CRAN.R-project.org/package = BIEN.
## Missouri Botanical Garden,Herbarium. Accessed via BIEN on NA.
## Observation.org (2026). Observation.org, Nature data from around the World. https://doi.org/10.15468/5nilie. Accessed via GBIF on 2022-03-02.
## Owens, H., Merow, C., Maitner, B., Kass, J., Barve, V., Guralnick, R. (2026). occCite: Querying and Managing Large Biodiversity Occurrence Datasets. R package version 0.6.3. https://CRAN.R-project.org/package = occCite.
## Ranwashe F (2026). Botanical Database of Southern Africa (BODATSA): Botanical Collections. Version 1.32. South African National Biodiversity Institute. https://doi.org/10.15468/2aki0q. Accessed via GBIF on 2022-03-02.
## Rob Cubey (2022). Royal Botanic Garden Edinburgh Living Plant Collections (E). Royal Botanic Garden Edinburgh. https://doi.org/10.15468/bkzv1l. Accessed via GBIF on 2022-03-02.
## SANBI. Accessed via BIEN on NA.
## Senckenberg (2020). African Plants - a photo guide. https://doi.org/10.15468/r9azth. Accessed via GBIF on 2022-03-02.
## Taylor S (2019). G. S. Torrey Herbarium at the University of Connecticut (CONN). University of Connecticut. https://doi.org/10.15468/w35jmd. Accessed via GBIF on 2022-03-02.
## Team}, {.C. (2025). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
## Teisher J, Stimmel H (2026). Tropicos MO Specimen Data. Missouri Botanical Garden. https://doi.org/10.15468/hja69f. Accessed via GBIF on 2022-03-02.
## Tela Botanica. Carnet en Ligne. https://doi.org/10.15468/rydcn2. Accessed via GBIF on 2022-03-02.
## UConn. Accessed via BIEN on NA.
## iNaturalist contributors, iNaturalist (2026). iNaturalist Research-grade Observations. iNaturalist.org. https://doi.org/10.15468/ab3s5x. Accessed via GBIF on 2022-03-02.
## naturgucker.de. NABU|naturgucker. https://doi.org/10.15468/uc1apo. Accessed via GBIF on 2022-03-02.

Note that you can also load multiple species using either a vector of species names or a phylogeny (provided you have previously downloaded data for all of the species of interest), and you can load occurrences from non-GBIF data sources (e.g. BIEN) in the same query.

occCite with a Phylogeny

Here is an example of how such a search is structured, using an unpublished phylogeny of billfishes.

library(ape)
#Get tree
treeFile <- system.file("extdata/Fish_12Tax_time_calibrated.tre", package='occCite')
phylogeny <- ape::read.nexus(treeFile)
tree <- ape::extract.clade(phylogeny, 22)
#Query databases for names
myPhyOccCiteObject <- studyTaxonList(x = tree, 
                                     datasources = "GBIF Backbone Taxonomy")
#Query GBIF for occurrence data
myPhyOccCiteObject <- occQuery(x = myPhyOccCiteObject, 
                            datasources = "gbif",
                            GBIFDownloadDirectory = system.file('extdata/', package='occCite'),
                            loadLocalGBIFDownload = T,
                            checkPreviousGBIFDownload = F)
# What does a multispecies query look like?
summary(myPhyOccCiteObject)
##  
##  OccCite query occurred on: 01 September, 2026
##  
##  User query type: User-supplied phylogeny.
##  
##  Sources for taxonomic rectification: GBIF Backbone Taxonomy
##      
##  
##  Taxonomic cleaning results:     
## 
##                   Input Name                 Best Match
## 1 Tetrapturus_angustirostris Tetrapturus angustirostris
## 2         Tetrapturus_belone         Tetrapturus belone
## 3      Tetrapturus_pfluegeri      Tetrapturus pfluegeri
##   Taxonomic Databases w/ Matches
## 1         GBIF Backbone Taxonomy
## 2         GBIF Backbone Taxonomy
## 3         GBIF Backbone Taxonomy
##  
##  Sources for occurrence data: gbif
##      
##                      Species Occurrences Sources
## 1 Tetrapturus angustirostris         671      26
## 2         Tetrapturus belone          46       7
## 3      Tetrapturus pfluegeri          44      10
##  
##  GBIF dataset DOIs:  
## 
##                      Species GBIF Access Date           GBIF DOI
## 1 Tetrapturus angustirostris       2026-09-01 10.15468/dl.d25nu2
## 2         Tetrapturus belone       2026-09-01 10.15468/dl.fjfux7
## 3      Tetrapturus pfluegeri       2026-09-01 10.15468/dl.6jss78

When you have results for multiple species, as in this case, you can also plot the summary figures either for the whole search…

plot(myPhyOccCiteObject)

or you can plot the results by species!

plot(myPhyOccCiteObject, bySpecies = T, plotTypes = c("yearHistogram", "source"))

And then you can print out the citations, separated by species (or not, but in this example, they’re separate).

#Get citations
myPhyOccCitations <- occCitation(myPhyOccCiteObject)

#Print citations as text with accession dates.
print(myPhyOccCitations, bySpecies = T)
## Writing 6 Bibtex entries ... OK
## Results written to file 'temp.bib'
## Species: Tetrapturus angustirostris 
## 
## Atlas of Living Australia (2025). Redmap. https://doi.org/10.15468/3aks4m. Accessed via GBIF on 2026-09-01.
## Australian Museum (2026). Australian Museum provider for OZCAM. https://doi.org/10.15468/e7susi. Accessed via GBIF on 2026-09-01.
## Barde J (2011). ecoscope_observation_database. IRD - Institute of Research for Development. https://doi.org/10.15468/dz1kk0. Accessed via GBIF on 2026-09-01.
## Bessudo S (2025). Inventario de Peces del Santuario de Fauna y Flora de Malpelo. Version 2.7. Fundación Malpelo y Otros Ecosistemas Marinos. https://doi.org/10.15472/yde8tf. Accessed via GBIF on 2026-09-01.
## Bosman A, Ranwashe F (2018). FBIP: IZIKO Marine Bony Fish (1884-2013). South African National Biodiversity Institute. https://doi.org/10.15468/rnpcwh. Accessed via GBIF on 2026-09-01.
## Bureau of Rural Sciences - National commercial fisheries half-degree data set 2000-2002 https://doi.org/10.15468/0esdv0. Accessed via GBIF on 2026-09-01.
## Cauquil P, Barde J (2011). observe_tuna_bycatch_ecoscope. IRD - Institute of Research for Development. https://doi.org/10.15468/23m361. Accessed via GBIF on 2026-09-01.
## Chamberlain, S., Barve, V., Mcglinn, D., Oldoni, D., Desmet, P., Geffert, L., Ram, K. (2026). rgbif: Interface to the Global Biodiversity Information Facility API. R package version 3.8.5.13. https://CRAN.R-project.org/package = rgbif.
## Chamberlain, S., Boettiger, C. (2017). R Python, and Ruby clients for GBIF species occurrence data. PeerJ PrePrints.
## Chiang W (2014). Taiwan Fisheries Research Institute – Digital archives of coastal and offshore specimens. TELDAP. https://doi.org/10.15468/xvxngy. Accessed via GBIF on 2026-09-01.
## European Bioinformatics Institute (EMBL-EBI), GBIF Helpdesk (2026). INSDC Sequences. Version 1.186. European Nucleotide Archive (EMBL-EBI). https://doi.org/10.15468/sbmztx. Accessed via GBIF on 2026-09-01.
## Fong J (2026). CAS Ichthyology (ICH). Version 150.538. California Academy of Sciences. Occurrence dataset. http://ipt.calacademy.org:8080/resource?r=ich&v=150.538 https://doi.org/10.15468/efh2ib. Accessed via GBIF on 2026-09-01.
## Frable B (2025). SIO Marine Vertebrate Collection. Version 1.9. Scripps Institution of Oceanography. https://doi.org/10.15468/ad1ovc. Accessed via GBIF on 2026-09-01.
## Harvard University M, Morris P J (2026). Museum of Comparative Zoology, Harvard University. Version 162.525. Museum of Comparative Zoology, Harvard University. https://doi.org/10.15468/p5rupv. Accessed via GBIF on 2026-09-01.
## Inventaire National du Patrimoine Naturel (2018). Programme Ecoscope: données d'observations des écosystèmes marins exploités (Réunion). UAR PatriNat (OFB-MNHN-CNRS-IRD), Paris. https://doi.org/10.15468/elttrd. Accessed via GBIF on 2026-09-01.
## Inventaire National du Patrimoine Naturel (2018). Programme Ecoscope: données d'observations des écosystèmes marins exploités. UAR PatriNat (OFB-MNHN-CNRS-IRD), Paris. https://doi.org/10.15468/gdrknh. Accessed via GBIF on 2026-09-01.
## María Monge-Ortiz A, Herrera-Herrera E, Chinchilla-Chinchilla I, Zúñiga-Siles M, Suominen S, Provoost P, Gillard E, Douvere F, Appeltans W (2024). UNESCO eDNA expedition in Cocos Island National Park (Costa Rica): December 2022. OBIS Secretariat. https://doi.org/10.25607/11qhzq. Accessed via GBIF on 2026-09-01.
## McLean, M.W. (2014). Straightforward Bibliography Management in R Using the RefManager Package. NA, NA. https://arxiv.org/abs/1403.2036.
## McLean, M.W. (2017). RefManageR: Import and Manage BibTeX and BibLaTeX References in R. The Journal of Open Source Software.
## Mertz W, Ludt W, Clardy T, Robson S, Camacho N (2026). LACM Vertebrate Collection. Version 18.20. Natural History Museum of Los Angeles County. https://doi.org/10.15468/77rmwd. Accessed via GBIF on 2026-09-01.
## Ministry for Primary Industries (2014). New Zealand research tagging database. Southwestern Pacific OBIS, National Institute of Water and Atmospheric Research (NIWA), Wellington, New Zealand, 411926 records, Online http://nzobisipt.niwa.co.nz/resource.do?r=mpi_tag released on November 5, 2014. https://doi.org/10.15468/i66xdm. Accessed via GBIF on 2026-09-01.
## Mokhtar A F, Ab Manaf N, Mohd Azmi Ramasamy A (2024). Fish Collection (2009, 2018 & 2019) (Kemaman & LKIM Kuantan) from the South China Sea Repository and Reference Centre (RRC), Institute of Oceanography and Environment (INOS), Universiti Malaysia Terengganu (UMT). Version 1.1. Institute of Oceanography and Environment (INOS). https://doi.org/10.15468/h9f8r6. Accessed via GBIF on 2026-09-01.
## Motomura H (2026). Fish collection of the Kagoshima University Museum. National Museum of Nature and Science, Japan. https://doi.org/10.15468/vcj3j8. Accessed via GBIF on 2026-09-01.
## Naretto J, Contreras V, Munizaga J L, Bujes D, Munizaga J L (2025). Biodiversidad asociada a principales pesquerías de recursos altamente migratorios del Programa Asesoría Integral para la Toma de Decisiones en Pesca y Acuicultura, Subsecretaria de Pesca y Acuicultura. Subsecretaría de Pesca y Acuicultura. Sampling event dataset https://doi.org/10.15468/szt26p. Accessed via GBIF on 2026-09-01.
## Owens, H., Merow, C., Maitner, B., Kass, J., Barve, V., Guralnick, R. (2026). occCite: Querying and Managing Large Biodiversity Occurrence Datasets. R package version 0.6.3. https://CRAN.R-project.org/package = occCite.
## Queensland Museum (2026). Queensland Museum provider for OZCAM. https://doi.org/10.15468/lotsye. Accessed via GBIF on 2026-09-01.
## Raiva R, Santana P (2021). Diversidade e ocorrência de peixes em Inhambane (2009-2017). Version 1.7. National Institute of Fisheries Research (IIP) – Mozambique. https://doi.org/10.15468/4fj2tq. Accessed via GBIF on 2026-09-01.
## Raiva R, Viador R, Santana P (2021). Diversidade e ocorrência de peixes na Zambézia (2003-2016). Version 1.6. National Institute of Fisheries Research (IIP) – Mozambique. https://doi.org/10.15468/mrz36h. Accessed via GBIF on 2026-09-01.
## Robins R (2026). UF FLMNH Ichthyology. Version 117.565. Florida Museum of Natural History. https://doi.org/10.15468/8mjsel. Accessed via GBIF on 2026-09-01.
## South Australian Museum (2025). South Australian Museum Adelaide provider for OZCAM. https://doi.org/10.15468/wz4rrh. Accessed via GBIF on 2026-09-01.
## Team}, {.C. (2025). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
## iNaturalist contributors, iNaturalist (2026). iNaturalist Research-grade Observations. iNaturalist.org. https://doi.org/10.15468/ab3s5x. Accessed via GBIF on 2026-09-01.
## Writing 6 Bibtex entries ... OK
## Results written to file 'temp.bib'
## Species: Tetrapturus belone 
## 
## Chamberlain, S., Barve, V., Mcglinn, D., Oldoni, D., Desmet, P., Geffert, L., Ram, K. (2026). rgbif: Interface to the Global Biodiversity Information Facility API. R package version 3.8.5.13. https://CRAN.R-project.org/package = rgbif.
## Chamberlain, S., Boettiger, C. (2017). R Python, and Ruby clients for GBIF species occurrence data. PeerJ PrePrints.
## Conselleria de Medio Ambiente, Agua, Infraestructuras y Territorio. Generalitat Valenciana (2026). Banco de Datos de la Biodiversidad de la Comunitat Valenciana. Biodiversity data bank of Generalitat Valenciana. https://doi.org/10.15468/b4yqdy. Accessed via GBIF on 2026-09-01.
## Deudero Company S (2025). Marine biodiversity atlas of the Balearic Sea. Version 1.0. Flanders Marine Institute. https://doi.org/10.15468/3g2c3d. Accessed via GBIF on 2026-09-01.
## Harvard University M, Morris P J (2026). Museum of Comparative Zoology, Harvard University. Version 162.525. Museum of Comparative Zoology, Harvard University. https://doi.org/10.15468/p5rupv. Accessed via GBIF on 2026-09-01.
## McLean, M.W. (2014). Straightforward Bibliography Management in R Using the RefManager Package. NA, NA. https://arxiv.org/abs/1403.2036.
## McLean, M.W. (2017). RefManageR: Import and Manage BibTeX and BibLaTeX References in R. The Journal of Open Source Software.
## Owens, H., Merow, C., Maitner, B., Kass, J., Barve, V., Guralnick, R. (2026). occCite: Querying and Managing Large Biodiversity Occurrence Datasets. R package version 0.6.3. https://CRAN.R-project.org/package = occCite.
## ROBERT S, LEPAREUR F, Inventaire National du Patrimoine Naturel (2022). Données d'occurrences Espèces issues de l'inventaire des ZNIEFF. Version 1.7. UAR PatriNat (OFB-MNHN-CNRS-IRD), Paris. https://doi.org/10.15468/ikshke. Accessed via GBIF on 2026-09-01.
## Robins R (2026). UF FLMNH Ichthyology. Version 117.565. Florida Museum of Natural History. https://doi.org/10.15468/8mjsel. Accessed via GBIF on 2026-09-01.
## Team}, {.C. (2025). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
## University of Kansas Biodiversity Institute: KUBI Ichthyology Collection https://doi.org/10.15468/mgjasg. Accessed via GBIF on 2026-09-01.
## iNaturalist contributors, iNaturalist (2026). iNaturalist Research-grade Observations. iNaturalist.org. https://doi.org/10.15468/ab3s5x. Accessed via GBIF on 2026-09-01.
## Writing 6 Bibtex entries ... OK
## Results written to file 'temp.bib'
## Species: Tetrapturus pfluegeri 
## 
## Boateng M (2021). Fishes of Ghana. Version 1.4. Department of Marine and Fisheries Sciences, University of Ghana. https://doi.org/10.15468/pgesnw. Accessed via GBIF on 2026-09-01.
## Bosman A, Ranwashe F (2018). FBIP: IZIKO Marine Bony Fish (1884-2013). South African National Biodiversity Institute. https://doi.org/10.15468/rnpcwh. Accessed via GBIF on 2026-09-01.
## Cauquil P, Barde J (2011). observe_tuna_bycatch_ecoscope. IRD - Institute of Research for Development. https://doi.org/10.15468/23m361. Accessed via GBIF on 2026-09-01.
## Chamberlain, S., Barve, V., Mcglinn, D., Oldoni, D., Desmet, P., Geffert, L., Ram, K. (2026). rgbif: Interface to the Global Biodiversity Information Facility API. R package version 3.8.5.13. https://CRAN.R-project.org/package = rgbif.
## Chamberlain, S., Boettiger, C. (2017). R Python, and Ruby clients for GBIF species occurrence data. PeerJ PrePrints.
## European Bioinformatics Institute (EMBL-EBI), GBIF Helpdesk (2026). INSDC Sequences. Version 1.186. European Nucleotide Archive (EMBL-EBI). https://doi.org/10.15468/sbmztx. Accessed via GBIF on 2026-09-01.
## Inventaire National du Patrimoine Naturel (2018). Programme Ecoscope: données d'observations des écosystèmes marins exploités (Réunion). UAR PatriNat (OFB-MNHN-CNRS-IRD), Paris. https://doi.org/10.15468/elttrd. Accessed via GBIF on 2026-09-01.
## Inventaire National du Patrimoine Naturel (2018). Programme Ecoscope: données d'observations des écosystèmes marins exploités. UAR PatriNat (OFB-MNHN-CNRS-IRD), Paris. https://doi.org/10.15468/gdrknh. Accessed via GBIF on 2026-09-01.
## McLean, M.W. (2014). Straightforward Bibliography Management in R Using the RefManager Package. NA, NA. https://arxiv.org/abs/1403.2036.
## McLean, M.W. (2017). RefManageR: Import and Manage BibTeX and BibLaTeX References in R. The Journal of Open Source Software.
## Orrell T, Informatics and Data Science Center - Digital Stewardship (2026). NMNH Extant Specimen Records (USNM, US). Version 1.111. National Museum of Natural History, Smithsonian Institution. https://doi.org/10.15468/hnhrg3. Accessed via GBIF on 2026-09-01.
## Owens, H., Merow, C., Maitner, B., Kass, J., Barve, V., Guralnick, R. (2026). occCite: Querying and Managing Large Biodiversity Occurrence Datasets. R package version 0.6.3. https://CRAN.R-project.org/package = occCite.
## Robins R (2026). UF FLMNH Ichthyology. Version 117.565. Florida Museum of Natural History. https://doi.org/10.15468/8mjsel. Accessed via GBIF on 2026-09-01.
## Rodriguez Jimenez A, Rueda M, Escobar Toledo F, Correa Daza J L, Salas Castro S T, Viloria Maestre E, Mejía Mercado B, Viaña Tous J, Ojeda K, Montoya-Cadavid E, Bohórquez Naranjo J C, Ojeda Ochoa K A (2023). Composición de pesca de prospección para grandes pelágicos del Caribe colombiano, recolectados en el marco del Programa de Investigación Pesquera en Aguas Marinas Jurisdiccionales de Colombia INVEMAR – AUNAP (2013-2018). Version 1.1. Instituto de Investigaciones Marinas y Costeras - Invemar. Sampling event dataset https://doi.org/10.15472/jlg8ij. Accessed via GBIF on 2026-09-01.
## Team}, {.C. (2025). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
## iNaturalist contributors, iNaturalist (2026). iNaturalist Research-grade Observations. iNaturalist.org. https://doi.org/10.15468/ab3s5x. Accessed via GBIF on 2026-09-01.