Skip to main content
NCBI home page
Applications in Plant Sciences logoLink to Applications in Plant Sciences
. 2026 Aug 20:e70077. Online ahead of print. doi: 10.1002/aps3.70077

BarnebyLives: An R package to create herbarium specimen labels and clean spreadsheets

Reed Clark Benkendorf 1,2,✉, Jeremie B Fant 1,2
PMCID: PMC13490981  PMID: 42625866

Abstract

Premise

Accessioning herbarium specimens is labor intensive, yet remains vital for research in ecology, evolution, and conservation. As institutional support for herbaria declines, efficient tools are needed to streamline this process. The R package BarnebyLives was developed to assist collectors by supplementing collection notes, verifying taxonomic data, conducting quality checks, generating labels, and submitting digital records.

Methods and Results

BarnebyLives integrates geospatial data from U.S. government sources to provide jurisdictional and site information and checks taxonomic names using in‐house spell checkers, International Plant Names Index (IPNI) author standards, and Kew's Plants of the World Online. Optional features include generating Google Maps driving directions. The tool outputs data in tabular and spatial formats for review before producing LaTeX‐based labels and shipping manifests.

Conclusions

BarnebyLives improves data accuracy, ensures up‐to‐date taxonomy, and significantly reduces the time and effort required to accession herbarium specimens in the United States.

Keywords: automation, herbarium, quality control, software

Nearly 400 million specimens are housed worldwide in herbaria (Thiers, 2021). However, the rate of accessioning new collections to herbaria diminished in the 20th century as priorities in biology shifted away from describing and documenting Earth's biodiversity and towards understanding the cellular and molecular processes underpinning life (Prather et al., 2004; Pyke and Ehrlich, 2010; Daru et al., 2018). This shift, among other factors, has led to a decline in the funding allocated to collection‐based research, the number of staff maintaining and accessing new collections, and educating students in these practices (Funk, 2014). Historically, specimens have been used to describe the taxonomic diversity of plants and document global floristic diversity (Greve et al., 2016; James et al., 2018; Brewer et al., 2019; Rønsted et al., 2020). However, renewed interest in herbarium collections utilizing “big data approaches,” such as museomics, has brought herbaria back to the forefront of the natural sciences and greatly expanded their roles in science (Marsico et al., 2020; Rønsted et al., 2020).

Innovations in specimen digitization, data sharing, computing, DNA sequencing, and statistics have perhaps brought about greater use of herbarium specimens than ever before (Greve et al., 2016; James et al., 2018; Brewer et al., 2019; Rønsted et al., 2020). The current use of specimens and their ancillary data extends well beyond their traditional roles in systematics and floristics, and studies utilizing collections are regularly carried out to better understand the ecological niches, phenological processes, and interactions of plants (Rønsted et al., 2020; Davis, 2023). We suspect that collections are yet to realize their full potential, and as currently novel approaches, such as electronic and remote sensing and meta‐barcoding, become more accessible the use of collections will increase (Tosa et al., 2021). While image‐based or purely observational (rather than collection‐based) community science approaches (e.g., iNaturalist, BudBurst) have recently dovetailed with herbarium specimens to meet many current research needs, specimens contain rich data that are not accessible via images. Of the two, specimens alone can provide samples of DNA, secondary metabolites or proteins, material for measuring (micro‐)morphological attributes (Borges et al., 2020), and seeds or pollen. These factors will ensure that herbarium specimens remain the premier botanical data source in perpetuity.

However, despite renewed recognition of the utility of collections, efforts to increase them appear slow (Prather et al., 2004). We conjecture that this is partly because collecting and depositing specimens is a fundamentally slower process, especially for novice collectors, relative to taking photographs via commercially developed apps on smartphones (Daru et al., 2018; Mishler et al., 2020; Manzano and Julier, 2021). While many novice botanists are capable of using dichotomous keys and other resources to reliably identify and collect satisfactory material, we observe that they face difficulties navigating several aspects of data acquisition, processing, and preparation of labels for submission to herbaria. Some of the apparent problems include the lack of dedicated time at the end of a field season to process specimens; a general lack of education on cartography and orienteering, natural history (e.g., geology, geomorphology), and nomenclature; familiarity with various computer programs (e.g., Microsoft Office suite); and foundational knowledge of plant systematics and phylogenetics (Woodland, 2007; Barrows et al., 2016; Nanglu et al., 2023).

The generation of a herbarium specimen involves many steps that are easy to take for granted (Forman and Bridson, 1989). For example, while acquiring appropriate political information for a collection site appears simple, novice collectors rarely have adequate cartographic resources (printed topographic maps or geographic information system [GIS] software) at their disposal. In topographically complex areas, where administrative borders are often associated with hydrological basins and the ridges defining them, collectors are liable to misinterpret their true geographic position and report administrative details in error. Even finding appropriate site names can rarely be resolved without a printed map, as many navigation‐related software now consider most features that would serve as site names to be extraneous. Similarly, the rate at which taxonomic innovations occur, the volume of the literature, and the reluctance of some regional curators to embrace a phylogenetic approach to plant classification have made it difficult to find more recently applied scientific names, even when these names are unanimously accepted by taxonomic specialists in the group and other regional curators (Hitchcock and Cronquist, 2018). Furthermore, formatting a label correctly (e.g., author abbreviations, italicization) is a time‐consuming process with many opportunities to introduce errors in formatting that reduce the apparent credibility of a collector. Anecdotally, many mail merge templates offered by herbaria still require collectors to modify many variables by hand (e.g., applying italicization). Even if a collector successfully navigates all these hurdles, the time allocated to each step is quite large and may discourage them from further collecting.

To address these concerns, we have developed an R package, BarnebyLives, that aims both to increase the quality of data rendered to labels and recorded in databases and to speed up the generation of labels. BarnebyLives rapidly provides political and administrative boundary information for a collection site using data from the U.S. Census Bureau (Walker, 2024), the Public Land Survey System (PLSS), and ownership details of public lands via the Protected Areas Database of the U.S. (PAD‐US) (U.S. Geological Survey [USGS] Gap Analysis Project [GAP], 2024). Site names are suggested by finding the closest unambiguously named place feature in the Geographic Names Information System (GNIS) and the precise calculation of distance and azimuth from this feature to the collection site (U.S. Geological Survey, 2026). Using the Global Mountain Biodiversity Assessment (GMBA) Mountain Inventory v2, a standardized named mountain dataset with global coverage, allows for a relevant descriptor of the general region with less ambiguity (Snethlage et al., 2022). Spell checks on all scientific names (including associated species) are performed using a copy of the World Checklist of Vascular Plants, and the resolved species may be searched via Kew's Plants of the World Online for relevant synonyms (Govaerts et al., 2021; POWO, 2024). Author abbreviations are verified using the International Plant Names Index (IPNI) Standard Author Abbreviation Checklist and also returned by Kew's Plants of the World Online to ensure proper abbreviations of authorities (POWO, 2024; IPNI, 2026). Checks to search for and flag common issues associated with spreadsheet software or data transcription, such as the autofilling of coordinate and date columns, are also performed. After a final review of the data flagged or generated by the package, users have the option to export spreadsheets that are suitable for mass uploading of data to multiple common herbarium databases as well as to generate herbarium labels.

Label generation functionality is only provided by two programs, PLabel and Symbiota, and by the Microsoft Word tool Mail Merge (Gries et al., 2014; Perkins, 2020). The Microsoft Office suite is costly and can be difficult to set up according to our experience; furthermore, its functionality ends with label creation. PLabel is a standalone program that has greatly enhanced functionality relative to Mail Merge, allowing users to specify the layout and formatting of label components using an intuitive and local graphical user interface (GUI) functionality. However, beyond verifying the country of collection, it does not include data cleaning functionalities. The increasingly popular Symbiota biodiversity data management software not only provides label generation capabilities but also provides data cleaning functionality in an attractive GUI web portal, allowing for live management of collections and bypassing the need for a local installation, so that it can be accessed on all operating systems. Symbiota offers functionality similar to the first four of the five stages of our taxonomic module, and also verifies the political boundaries (as performed in the Political Boundaries module in BarnebyLives). However, not all herbaria use Symbiota, and many have original database systems that they maintain (e.g., Harvard University Herbarium: https://kiki.huh.harvard.edu/databases/specimen_index.html, Missouri Botanical Garden: https://tropicos.org/specimen/Search, and The Consortium of Pacific Northwest Herbaria: https://www.pnwherbaria.org/). Most importantly, however, many collectors prefer to generate their own labels, especially as they are likely to send different sets of collections to different institutions. Accordingly, the data ingestion and processing steps offered by Symbiota should exist alongside alternative systems. In scenarios where users want to keep rendering labels in either of the three existing alternatives, they can easily export data in the appropriate formats after utilizing the data cleaning utilities available in BarnebyLives.

BarnebyLives was named for plant taxonomist Rupert Charles Barneby (1911–2000), who published over 6500 pages of text, described over 750 taxa, and is notable for balancing his studies at the William and Lynda Steere Herbarium at the New York Botanical Garden with annual collection trips in Western North America from 1937–1970 and sporadically until his death in 2000 (Welsh, 2001). Select accolades of Rupert include the 1989 Asa Gray Award from the American Society of Plant Taxonomists (ASPT), the 1991 Engler Silver Medal from the International Association of Plant Taxonomists (IAPT), as well as being one of eight recipients of the International Botanical Congress's (IBC) Millennium Botany Award (Welsh, 2001). Most germanely, Rupert was remembered as being generous with his time to assist younger botanists with the more arcane aspects of field botany and taxonomy (Holmgren and Holmgren, 1988).

METHODS AND RESULTS

BarnebyLives was iteratively developed based on data submitted by approximately 20 seasonal field botany teams over a two‐year period. Essentially, continual updates were made as the developers became aware of the idiosyncrasies of collection notes and data entry. Several commands in BarnebyLives require output from previous functions, and a workflow that satisfies these requirements is presented in Figure 1.

Figure 1.

Figure 1

Open in a new tab

Recommended workflow. The top two rows show the main data cleaning steps, which should generally be run in the order shown, although taxonomic steps may precede spatial ones. The third row can be interspersed with the first two and includes label creation, which helps detect formatting or other issues not captured by the pipeline or earlier manual review. Additional functions support data export for mass upload at the receiving institution and generation of a shipping manifest and transfer notice.

Usage

All steps of BarnebyLives, except for label generation, are run within the freely available RStudio (Posit Team, 2026). Data may be read from any common spreadsheet management system or database connection such as Excel, from free alternatives such as LibreOffice or OpenOffice, or via the cloud on Google Sheets. The latter two options are documented here and in package vignettes, detailed descriptions of the required and suggested input columns are located on GitHub (https://sagesteppe.github.io/BarnebyLives/), and around 100 real‐world examples are provided on a Google Sheets accessible from that page. BarnebyLives is atypical for R packages in that it requires a considerable amount of data to operate (Figure 2). Virtually all on‐disk memory associated with the package is used to store spatial data, with the amount of spatial data varying according to the domain that the user decides to support (Figure 2). Functions that require on‐disk data require a path to data as an argument. Manually supplying the path argument allows users to determine an appropriate storage location suitable for their needs.

Figure 2.

Figure 2

Open in a new tab

Data sources for the BarnebyLives R package. TRS, Township Section and Range.

We anticipate that for a typical user, BarnebyLives will require less than a couple gigabytes of memory (ours covering all of the conterminous Western United States at 3‐arc second [~90 m] resolution is ~16 GB), while the processing requires relatively little RAM; hence installations can work on hardware as limited as Chromebooks, while having the data stored entirely on thumb drives. Given that the attributes for which the package collects data are tailored to the Western United States region, we do not expect local installs to exceed the size of ours. The final steps of BarnebyLives, generating the labels, require working installations of R Markdown, a LaTeX installation (e.g., pdfTeX, LuaTeX, XeLaTeX), and the open‐source command‐line tools pdfjam and pdftk (Vinyals, 2022; Firth et al., 2026). While these steps are run through a shell‐scripting language such as bash, we have wrapped them in R functions that bypass the need to enter the commands directly into a shell terminal outside of RStudio. However, installation of the utilities on the three supported operating systems (Debian Linux, MacOS, and Windows 10 and 11) will require some minimal use of the command line to install the software required for the label‐generating functionality as detailed on the README page.

Functionality

BarnebyLives consists of five main modules (Figure 1): spatial, taxonomic, formatting, manual review, and data exporting. The core functions are detailed below, and all functions are documented on the package Reference page (https://sagesteppe.github.io/BarnebyLives/reference/index.html).

The spatial module has five required functions and two optional functions. The required functions include: (1) autofill_checker searches for patterns in the input latitude and longitude data associated with autofilling from various spreadsheet programs and will emit a warning if they are encountered; (2) coords2sf creates a spatially explicit simple feature (sf) geometry dataset for the input data; (3) political_grabber determines many levels of administrative ownership, including land management and public land survey system sections; (4) physical_grabber provides various geographic data, such as elevation, landform position, and aspect using 90‐m resolution spatial data; and (5) site_writer writes distance and azimuth to the collection site from the nearest official named place from the GNIS database. The optional functions are: (1) directions_grabber writes driving directions from a reasonably sized town to the closest drivable area to the site using the Google Maps API, which will require a valid Google account that is free per month for most personal and smaller academic usages; and (2) dms2dd converts coordinates denoted in the degrees, minutes, and second (DMS) format (e.g., 42°08′39.9″N, 87°47′08.3″W) to decimal degree format (e.g., 42.14439, −87.78569).

It should be noted that the function physical_grabber is the one portion of the package where a decoupling may exist between the collection site and the resolution of the spatial data. While we expect the mismatch to be negligible for all effective purposes relating to elevation, major geology type, and general aspect, estimates of slope at this resolution may be biased—generally to lower angles. To account for this, collectors should always make notes on the environment in which taxa are found, and consider that the notes available through BarnebyLives reflect the greater landscape in which a microfeature may be present. While this mismatch will seldom effect landscape ecologists, it may have implications for other data users.

The taxonomic module has four required functions and one optional function. The required functions are: (1) spell_check performs a spell check on the entered scientific name based on a local copy of Kew's Plants of the World database filtered to the local continents or a user‐specified backbone; (2) spell_check_family performs a spell check on the family entered for each scientific name; (3) author_check ensures that the author names are entered in a valid format (e.g., the correct standard abbreviations are used); and (4) associates_check performs a spell check on all associated species using the local taxonomic database. powo_searcher is an optional function that can be used in tandem with the functions spell_check_family and author_check, but we use it in lieu of them to search the current Plants of the World Online to determine relevant synonyms and alternative higher taxonomy for the focal species. No API key or registration is required to use powo_searcher.

The formatting module has three functions. Two are optional, but they are run locally and so quickly that there is no reason to skip them. date_parser parses an input date into various formats for notating collection and determination dates on labels. associate_dropper silently removes the collected species from the list of associated species; however, it searches for the species to be removed using the scientific name entered initially by the user rather than that returned via spell checks. field_lengths will supply a warning message for any fields suspected to create an “overflow” on the physical label that should be truncated for clarity.

The manual review process has only one function, which is technically optional; however, given the importance of ensuring that coordinates are appropriately located for many of the modules in the software, we suggest all users perform it. This function, geodata_writer, will write out a spatial copy of the dataset to any geospatial format supported by the sf package. The default file format is KML files, which are readily used with Google Earth and can also be opened in several other free GIS software programs such as QGIS (http://www.qgis.org). Notably, many of the flags that BarnebyLives generates will be placed into columns with obviously flagged names and can be manually reviewed by the analyst; many of these issues can be resolved by simply addressing the relevant issues in the original data input spreadsheet.

The data‐exporting module contains three functions that interact with LaTeX templates and require slightly more advanced R user interactivity, such as setting up mapping functions using the purrr package from the tidyverse (Wickham et al., 2019; Wickham, 2026). These functions are: (1) labels_skeleton, an R script that will require modifications to customize for institutions, place data into a user‐specified template, and serve as the interface to LaTeX; (2) label_writer writes from a flat file or spreadsheet to small 4 × 4‐inch herbarium labels (users can modify these dimensions as needed); and (3) format_database_import will write out a spreadsheet of cleaned data in a variety of formats (currently, the Jepson, Symbiota, and Consortium of Pacific Northwest herbaria formats are supported).

Herbarium collections

The testing of the BarnebyLives package was performed using a subset of the first author's collections from 2018–2022 using a home computer as detailed in Appendix S1, while most development was performed on their 2023 and 2024 collections. Only collections identified to the level of species or lower and including transcribed collection dates and coordinates were used for optimal functionality. In total, 980 records were used for testing various functions; these records were from 234 sites located across Western North America (Figure 3). This dataset had a total of 728 species (with 558 distinct sets of authors), with 83 infraspecies (22 authorships) in 74 families.

Figure 3.

Figure 3

Open in a new tab

The spatial extent or domain (outlined in burgundy) and herbarium collection sites (marked with orange dots) tested in this study.

BarnebyLives took roughly 4 min (227.5 s) to run all local steps, roughly 10 min (595.3 s) to search Plants of the World Online for preferred synonyms, and 64.9 s to search Google Maps and write directions to sites. Most of the local run time is attributable to the spatial (209.1 s) and taxonomic operations (17.9 s), while formatting data for labels took 0.5 s. The spell check of the scientific names accounted for nearly all of the time (17.7 s) spent performing local taxonomic operations. The generation of labels consumed around 9 min (523.5 s) for the rendering and an additional 61.1 s to combine the 182 sheets into a single PDF. The total label generation run time for processing these 728 collections was 15 min. In total, the 728 collections, which underwent all processing steps, took 25 min to process.

Results

Even on our test dataset, which had been manually cleaned and error‐checked by a human several times, BarnebyLives was able to reduce transcription errors, identify typographical errors, make nomenclature suggestions, and reformat text elements for downstream use. While none of the 74 family names were misspelled, BarnebyLives made 25 suggestions on family‐level nomenclature, identified six instances where the user had entered an unequivocally incorrect family (or taxonomic entity), identified five records where the family name was autofilled, and identified one instance where an outdated circumscription was applied. At the family level, BarnebyLives flagged six records where the author followed an alternative taxonomy and flagged seven records in error. It appears that most of these errors were due to issues in the backbone used by the earlier spell check function.

In the 326 genera analyzed, BarnebyLives identified 74 discrepancies at the genus level between user‐submitted data and processed data. In 42 of these instances, the user supplied an outdated name (21 unique genera), flagged four records where the author followed an alternative taxonomy (two genera total), and flagged two records in error. Of 728 distinct species analyzed, BarnebyLives flagged 62 records and detected 33 instances of misspelled epithets (33 unique species). In 15 of these instances, the user supplied an outdated name (15 unique species). It also flagged two records where the author followed an alternative taxonomy (two unique species) and flagged eight records in error. The final record was an egregious error where the order of the specific epithet and the genus name were swapped.

Five records were appropriately flagged for issues with autofills of the longitude value, and three records were also flagged for autofilling increases in latitude values. All flags were correct, and in several instances additional errors were found in the rows following the flagged values.

Other considerations

While numerous tools have been developed for cleaning existing herbarium and museum records, few tools exist to ensure that the data entered are accurate (Patten et al., 2024). We argue that the original collectors are the most qualified individuals to perform quality control checks and that BarnebyLives allows them to assume this responsibility in a relatively fast and streamlined format. While BarnebyLives may be adopted by herbarium curators, its original use was for natural resource management employees (e.g., U.S. Forest Service, heritage programs, natural history surveys) and graduate students in ecology and conservation (e.g., performing inventory and community ecology work), and we expect it to be most widely used in this realm. Beyond the purpose of using the collected data to create a label for a physical specimen, the utility of BarnebyLives may be extended to providing information for various biotic databases (e.g., heritage program databases) or modeling applications (e.g., modeling in community ecology) as a user sees fit. By utilizing both R and LaTeX and having publicly available source code on GitHub, this program allows users to troubleshoot issues and implement upgrades and modifications in project branches. LaTeX, a software system used for typesetting, was developed to allow users to focus on the content rather than the style of the rendered documents. Indeed, using the default LaTeX settings along with standard templates allows users to produce aesthetically pleasing results (Figure 4, Appendix S2). However, LaTeX also offers a rich suite of customizable parameters that offer users a wide variety of ways to modify labels that are under‐explored in the package. Very good documentation of LaTeX capabilities is offered in multiple areas, for instance via the Overleaf project (Overleaf, 2026). While the templates in BarnebyLives are quite simple, LaTeX also offers the ability to use custom fonts, alter font weights and colors, alter line spacing, include images (e.g., dot maps), and customize labels beyond what the default templates support.

Figure 4.

Figure 4

Open in a new tab

Example label.

BarnebyLives allows for the use of “domains” (i.e., custom geographic extents) to which analysis is restricted; this allows users to specify any portion of the United States for setting up their instance. However, many of the environmental and geographic variables for which BarnebyLives collects information are tailored to Western North America. Several of the variables that BarnebyLives collects and displays on labels relate to topics that are of interest to more senior Western curators (i.e., the administrative information on Township Section and Range [TRS] or the agency administering public land) but that are considered less valuable—or even unavailable or inapplicable—for other geographic regions. Environmental variables such as slope, aspect, and geology are prominent drivers of plant distributions in semi‐arid environments and warrant inclusion on herbarium labels for specimens from Western environments, but curators may consider them superfluous for other environments. Accordingly, users may consider developing new functionality that either removes or supplements the default variables to better reflect regional needs.

Accessioning often relies on the use of the Microsoft Office suite of programs and may utilize other costly software such as ArcPro or Adobe Acrobat. While BarnebyLives does not have its own GUI, the functionality of commonly used integrated development environments (IDEs), such as RStudio, Positron, and VisualStudio (VS) Code, allows users to readily view and filter datasets using familiar spreadsheet‐like formats, increasing accessibility for many users.

CONCLUSIONS

BarnebyLives is an R package that can be used to rapidly acquire relevant geographic and taxonomic data. It can also perform specialized spell checks and assorted curatorial tasks to produce both digital and analog data. The package relies on no licensed software, such as the Microsoft Office suite, and is suitable for installation on all major operating systems (e.g., Windows, Mac, Linux), requiring only minimal use of the command line, which may be called from RStudio or Positron rather than a traditional terminal. Furthermore, while BarnebyLives is primarily intended to create herbarium labels, its basic functionality to resolve taxonomic names and query environmental attributes may make it useful for various land management agencies, which require these utilities for different research activities.

AUTHOR CONTRIBUTIONS

R.C.B. conceptualized the project, wrote the program, and collected and analyzed the data; R.C.B. and J.B.F. wrote the manuscript; and both authors approved the final version.

Supporting information

Appendix S1: System information for benchmarking.

Appendix S2: Label templates.

APS3-9999-e70077-s001.pdf (809.1KB, pdf)

ACKNOWLEDGMENTS

The Bureau of Land Management is gratefully acknowledged as a provider of funding to R.C.B. for most of his specimen collection activities. We thank the two anonymous peer reviewers who have increased the quality of this manuscript and the functionality of the package. Several prominent associated collectors of specimens used in this study are thanked: Dani Yashinovitz, Hannah Lovell, Dakota Becerra, Caitlin Miller, and Hubert Szczygiel.

DATA AVAILABILITY STATEMENT

The BarnebyLives R package is open source, and the development version is available on GitHub (https://github.com/sagesteppe/BarnebyLives). The package includes seven use‐case vignettes (tutorials) that are available on a GitHub Pages site (https://sagesteppe.github.io/BarnebyLives/). The first vignette, “Preparing to use BarnebyLives!”, shows how to set up an instance for a certain geographic area (domain). The “BarnebyLives! Running pipeline” vignette showcases the core functionality of the package for processing data entered on a spreadsheet. “Printing herbarium labels and exporting a digital copy of data” demonstrates how to export data in both digital and analog formats, while “Rendering a shipping manifest” details how to produce a shipping manifest for gifting or transferring material to a herbarium. The remaining vignettes detail different aspects of label usage, such as including maps and logos (“Labels with graphics”) and customization (e.g., the position of template elements in “Customizing a label template” and fonts in “Customizing label fonts”).

All data used in this manuscript are available at: https://github.com/sagesteppe/Barneby_Lives_dev/tree/main/manuscript.

REFERENCES

  1. Barrows, C. W. , Murphy‐Mariscal M. L., and Hernandez R. R.. 2016. At a crossroads: The nature of natural history in the twenty‐first century. BioScience 66: 592–599. [Google Scholar]
  2. Borges, L. M. , Reis V. C., and Izbicki R.. 2020. Schrodinger's phenotypes: Herbarium specimens show two‐dimensional images are both good and (not so) bad sources of morphological data. Methods in Ecology and Evolution 11: 1296–1308. [Google Scholar]
  3. Brewer, G. E. , Clarkson J. J., Maurin O., Zuntini A. R., Barber V., Bellot S., Biggs N., et al. 2019. Factors affecting targeted sequencing of 353 nuclear genes from herbarium specimens spanning the diversity of angiosperms. Frontiers in Plant Science 10: e1102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Daru, B. H. , Park D. S., Primack R. B., Willis C. G., Barrington D. S., Whitfeld T. J., Seidler T. G., et al. 2018. Widespread sampling biases in herbaria revealed from large‐scale digitization. New Phytologist 217: 939–955. [DOI] [PubMed] [Google Scholar]
  5. Davis, C. C. 2023. The herbarium of the future. Trends in Ecology and Evolution 38: 412–423. [DOI] [PubMed] [Google Scholar]
  6. Firth, D. , Thomas R., and Kurtz M.. 2026. pdfjam: The pdfjam package for manipulating PDF files. Version 4.3.1. Website https://github.com/pdfjam/pdfjam [accessed 3 August 2026].
  7. Forman, L. , and Bridson D.. 1989. The herbarium handbook. Royal Botanic Gardens Kew, Richmond, United Kingdom. [Google Scholar]
  8. Funk, V. A. 2014. The erosion of collections‐based science: Alarming trend or coincidence. The Plant Press 17: 1–13. [Google Scholar]
  9. Govaerts, R. , Nic Lughadha E., Black N., Turner R., and Paton A.. 2021. The world checklist of vascular plants, a continuously updated resource for exploring global plant diversity. Scientific Data 8: e215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Greve, M. , Lykke A. M., Fagg C. W., Gereau R. E., Lewis G. P., Marchant R., Marshall A. R., et al. 2016. Realising the potential of herbarium records for conservation biology. South African Journal of Botany 105: 317–323. [Google Scholar]
  11. Gries, C. , Gilbert M. E. E., and Franz N. M.. 2014. Symbiota: A virtual platform for creating voucher‐based biodiversity information communities. Biodiversity Data Journal 2: e1114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Hitchcock, C. L. , and Cronquist A.. 2018. Flora of the Pacific Northwest: An illustrated manual. University of Washington Press, Seattle, Washington, USA. [Google Scholar]
  13. Holmgren, N. , and Holmgren P.. 1988. Intermountain flora, vol. 7. The New York Botanical Garden Press, New York, New York, USA.
  14. IPNI . 2026. International Plant Names Index. Website http://www.ipni.org. The Royal Botanic Gardens, Kew, Harvard University Herbaria & Libraries and Australian National Herbarium [accessed 21 July 2026].
  15. James, S. A. , Soltis P. S., Belbin L., Chapman A. D., Nelson G., Paul D. L., and Collins M.. 2018. Herbarium data: Global biodiversity and societal botanical needs for novel research. Applications in Plant Sciences 6: e1024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Manzano, S. , and Julier A. C.. 2021. How FAIR are plant sciences in the twenty‐first century? The pressing need for reproducibility in plant ecology and evolution. Proceedings of the Royal Society B. Biological Sciences 288: e20202597. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Marsico, T. D. , Krimmel E. R., Carter J. R., Gillespie E. L., Lowe P. D., McCauley R., Morris A. B., et al. 2020. Small herbaria contribute unique biogeographic records to county, locality, and temporal scales. American Journal of Botany 107: 1577–1587. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Mishler, B. D. , Guralnick R., Soltis P. S., Smith S. A., Soltis D. E., Barve N., Allen J. M., and Laffan S. W.. 2020. Spatial phylogenetics of the North American flora. Journal of Systematics and Evolution 58: 393–405. [Google Scholar]
  19. Nanglu, K. , de Carle D., Cullen T. M., Anderson E. B., Arif S., Castañeda R. A., Chang L. M., et al. 2023. The nature of science: The fundamental role of natural history in ecology, evolution, conservation, and education. Ecology and Evolution 13: e10621. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Overleaf . 2026. Overleaf: A web‐based collaborative LaTeX editor. Version 6.2.0. Website https://github.com/overleaf/overleaf [accessed 3 August 2026].
  21. Patten, N. N. , Gaynor M. L., Soltis D. E., and Soltis P. S.. 2024. Geographic and taxonomic occurrence R‐based scrubbing (gatoRs): An R package and workflow for processing biodiversity data. Applications in Plant Sciences 12: e11575. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Perkins, K. 2020. PLabel [Computer software]. University of Florida Herbarium. Website https://www.floridamuseum.ufl.edu/herbarium/methods/plabel/ [accessed 17 July 2026].
  23. Team Posit. 2026. RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, Massachusetts, USA.
  24. POWO . 2024. Plants of the World Online. Facilitated by the Royal Botanic Gardens, Kew. Website https://powo.science.kew.org/ [accessed 17 July 2026].
  25. Prather, L. A. , Alvarez‐Fuentes O., Mayfield M. H., and Ferguson C. J.. 2004. The decline of plant collecting in the United States: A threat to the infrastructure of biodiversity studies. Systematic Botany 29: 15–28. [Google Scholar]
  26. Pyke, G. H. , and Ehrlich P. R.. 2010. Biological collections and ecological/environmental research: A review, some observations and a look to the future. Biological Reviews 85: 247–266. [DOI] [PubMed] [Google Scholar]
  27. Rønsted, N. , Grace O. M., and Carine M. A.. 2020. Integrative and translational uses of herbarium collections across time, space, and species. Frontiers in Plant Science 11: e1319. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Snethlage, M. A. , Geschke J., Ranipeta A., Jetz W., Yoccoz N. G., Körner C., Spehn E. M., et al. 2022. A hierarchical inventory of the world's mountains for global comparative mountain science. Scientific Data 9: e149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Thiers, B. M. 2021. The world's herbaria 2021: A summary report based on data from index herbarium. Available at https://sweetgum.nybg.org/science/wp-content/uploads/2022/02/The_Worlds_Herbaria_Jan_2022.pdf [accessed 17 July 2026].
  30. Tosa, M. I. , Dziedzic E. H., Appel C. L., Urbina J., Massey A., Ruprecht J., Eriksson C. E., et al. 2021. The rapid rise of next‐generation natural history. Frontiers in Ecology and Evolution 9: e698131. [Google Scholar]
  31. U.S. Geological Survey (USGS) Gap Analysis Project (GAP) . 2024. Protected Areas Database of the United States (PAD‐US) 4: U.S. Geological Survey data release. 10.5066/P96WBCHS. [DOI]
  32. U.S. Geological Survey . 2026. Geographic Names Information System (GNIS). Website https://www.usgs.gov/tools/geographic-names-information-system-gnis [accessed 17 July 2026].
  33. Vinyals, M. 2022. pdftk‐java: A port of PDFtk into Java, version 3.3.3. Website https://gitlab.com/pdftk-java/pdftk [accessed 2 August 2026].
  34. Walker, K. 2024. Tigris: Load census TIGER/line shapefiles. R package version 2.2.1. Website https://github.com/walkerke/tigris [accessed 17 July 2026].
  35. Welsh, S. L. 2001. Rupert C. Barneby (1911–2000). Taxon 50: 285–292. [Google Scholar]
  36. Wickham, H. 2026. purrr: Functional programming tools. R package version 1.2.2. Website https://purrr.tidyverse.org/ [accessed 3 August 2026].
  37. Wickham, H. , Averick M., Bryan J., Chang W., McGowan L. D., François R., Grolemund G., et al. 2019. Welcome to the tidyverse. Journal of Open Source Software 4(43): e1686. 10.21105/joss.01686. [DOI] [Google Scholar]
  38. Woodland, D. W. 2007. Are botanists becoming the dinosaurs of biology in the 21st century? South African Journal of Botany 73: 343–346. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix S1: System information for benchmarking.

Appendix S2: Label templates.

APS3-9999-e70077-s001.pdf (809.1KB, pdf)

Data Availability Statement

The BarnebyLives R package is open source, and the development version is available on GitHub (https://github.com/sagesteppe/BarnebyLives). The package includes seven use‐case vignettes (tutorials) that are available on a GitHub Pages site (https://sagesteppe.github.io/BarnebyLives/). The first vignette, “Preparing to use BarnebyLives!”, shows how to set up an instance for a certain geographic area (domain). The “BarnebyLives! Running pipeline” vignette showcases the core functionality of the package for processing data entered on a spreadsheet. “Printing herbarium labels and exporting a digital copy of data” demonstrates how to export data in both digital and analog formats, while “Rendering a shipping manifest” details how to produce a shipping manifest for gifting or transferring material to a herbarium. The remaining vignettes detail different aspects of label usage, such as including maps and logos (“Labels with graphics”) and customization (e.g., the position of template elements in “Customizing a label template” and fonts in “Customizing label fonts”).

All data used in this manuscript are available at: https://github.com/sagesteppe/Barneby_Lives_dev/tree/main/manuscript.

Articles from Applications in Plant Sciences are provided here courtesy of Wiley

RESOURCES