Using Temporary Code Names for Documenting Macrofungi

Below is a revised and extended recreation of a few paragraphs I wrote for inclusion in a longer paper - Canan et al. 2024. This post is intended to serves as a reference for the temporary code name system used by many North American mycologists.

Also review our FAQ for Temporary Code Names post.

Temporary code names for species have been widely used by North American mycologists—both amateur and professional—for over a decade on platforms like Mushroom Observer, iNaturalist, and GenBank. The system we use for documening macrofungal biodiversity in North America differs significantly from other numerical-based approaches, such as UNITE. However, a full explanation of temporary codes and justification of their use has never been presented in the scientific literature. An outline of our system follows.

Identification of taxa based solely on ITS barcodes, while sometimes straightforward, is often difficult or impossible due to limitations in available reference data. Just a few examples of the difficulties that can cause issues are type specimens without sequences or specimens, lack of well-validated reference material, misidentifications, and cryptic species, among others (Meiklejohn et al., 2019; Nilsson et al., 2006). This has led Hofstetter et al. to conclude that “prospects for a more reliable sequence-based identification of fungi remain quite dim,” (Hofstetter et al., 2019). One reason for the negative outlook is that a significant number of North American species do not yet have reference data in GenBank, and many have conflicting reference data in public DNA repositories. In these cases, traditional sequence-based identification techniques are much more challenging. Given these limitations, new models for documenting biodiversity are especially important for hyperdiverse groups like fungi, most of which remain undescribed. To accelerate our understanding of biodiversity, especially in underdescribed groups, models that do not rely solely on Latin binomials are essential.

One functional model that worked particularly well for the Amanitaceae has been utilized by Rod Tulloss for decades (Tulloss & Yang, 2024). Based primarily on macro- and micromorphology until the advent of DNA sequencing, this three-stage identification system allows for communication about unpublished species-level units. Having a systematic ‘language’ for this family has enabled the study of its members’ morphology, ecology, geographic range, and levels of diversity, even in cases where species were not formally described. Operating by the Tulloss method, when a novel species is encountered standard practice assigns the species a temporary code name and publishes the known information about this species online at Amanitaceae.org. Temporary codes are often derived from the collection location and a sequential number (e.g., Amanita sp. ‘IN01’), enabling structured reference before formal names exist. As the species is recollected, additional photos and barcodes accumulate. More macroscopic/microscopic analysis is accomplished. All of this data is linked together by DNA barcodes and the temporary code name. As data aggregation continues across time, a clear picture of the species begins to emerge. Only then is a provisional name proposed for publication as the formal Latin binomial, following ICN standards (Turland et al., 2018) and peer review. If a community agreement is reached, this marks the third stage and ultimate goal of the process. The name will then serve as the Latin binomial for the species from that time forward.

The Tulloss model was highly influential when designing our current system. In order to be assigned a temporary code, the species-level unit must 1.) lack reference data in public DNA repositories, 2.) have incomplete reference data, or 3.) have conflicting reference data. This basic model was broadly expanded to macrofungi outside of the Amanitaceae starting in 2016 (Russell, 2022). The benefits of creating provisional codes include streamlining the identification process and gaining the power to link unnamed specimens together for future research, ultimately providing a reliable and consistent sequence-based identification regime for macrofungi. Novel individual species-level sequence clusters can be delimited and assigned a temporary code name as sequences are generated. Our temporary code names are roughly equivalent to the UNITE species hypothesis (Nilsson et al., 2018; Abarenkov et al., 2022), but with some substantive differences. Our system allows for new codes to be immediately generated as novel sequences are encountered, without the need to wait for periodic database updates with a new temporary code name, a process that can take 6 months or more. Further, our code names are not solely sequence-based identifications based on arbitrary similarity values, but take morphology, ecology, geography, and phenology into account when circumscribing a putative species-level delimitation. Finally, our method make sequence similarity scoring adjustments for non-phylogenetically informative regions, common sequencing errors, ambiguous nucleotides, and other elements that are likely to affect sequence similarity assessments final specimens in a cluster. Once species are delimited and a temporary code name is assigned, our method allows rapid sequence-based identification of future collections in real-time and links them efficiently to all related specimens in the dataset.

Assigning a temporary code name does not imply that a species is novel or undescribed. Rather, it flags uncertainty due to missing or conflicting reference data. The temporary code represents the fact that we are unable or unwilling to make a definitive sequenced-based identification due to incomplete reference data in public DNA repositories. A temporary code serves as a flag indicating that more data is needed before a Latin binomial can be assigned with confidence. Other options historically utilized by the mycological community include appending cf. (confer) or aff. (affinis) within a Latin binomial e.g. Amanita aff. canescens. This is problematic when aiming to quantify regional biodiversity, as the same name may be applied to multiple distinct species-level units, obscuring true diversity. In that case, the same name is used for multiple species-level units and species cannot be easily disaggregated to assess total biodiversity. We also do not believe the term OTU (Operational Taxonomic Unit) is synonymous with the temporary code name methodology outlined here. An OTU typically represents a statistical cluster of environmental sequences based on an arbitrary sequence similarity value, such as 97%. Our temporary code names are dynamically clustered based on the intraspecific and interspecific variation present within the available DNA reference data (i.e., a barcode gap). Our temporary codes are then backed up and validated by similarities in ecology, phenology, and morphology typically supported by multiple color images in situ. One goal for temporary code names is for them to be truly temporary. Unlike arbitrary OTU clusters or purely sequence-based hypotheses, our temporary code names are integrative—anchored in physical specimens, field data, and ecological context. They are intentionally designed to be temporary, yet structured to support reproducible science and the systematic documentation of biodiversity. In this way, they quickly deprecate as more type species are sequenced and more novel species are described. A second and proximate goal is to allow better communication as we assess what is currently known about a species. We can continue aggregating new information about the species in a systematic and methodical manner until the species-level unit is assigned an existing name or formally described.

To support widespread adoption, the process for generating and registering temporary code names has been designed to be simple and accessible. Once a sequenced specimen can be delimited, you can register the name on MycoMap (www.mycomap.com/taxonomy/add/). Two name generation formats are most broadly utilized. The first involves the geographic location of the first collection and a sequential number as mentioned above, e.g. Amanita sp. ‘IN01.’ The second naming convention is used in cases where 1.) the species has a close relative it is likely to be confused for in the field, 2.) it is a known member of a species cluster, or 3.) if the name commonly used for the species is outdated e.g. Hygrocybe sp. ‘conica-IN04.’ Once a candidate name is selected, it can be searched in the “Copy From” field at the link above to see if there have been other names registered. For example, type in ‘Hygrocybe “conica’ and examine the dropdown to see the other names within this cluster that have been previously registered. Selecting one of the names in the “Copy From” dropdown will copy the classification - kingdom, phylum, class, order, family, and genus from that species record and apply it to your new name. Next, select the rank for the name you will be creating, this will almost always be “Species.” Finally enter the name you would like to register into the “Name” field. After submitting, the name is registered to MycoMap and available for use. This system helps ensure that even unnamed biodiversity is tracked and studied with rigor—building the infrastructure necessary for future taxonomic clarity.

As of June 2025, community scientists in North America have now documented nearly 100,000 sequenced specimens with photo-linked data aggregated from iNaturalist, MycoMap, and Mushroom Observer, including 65,000 individually validated barcoded observations to date. In the US alone, over 70,000 DNA-barcoded fungal observations have been recorded on iNaturalist, meaning approximately 1% of all US fungal observations on the platform now have associated DNA barcode data—a testament to these dedicated efforts. The initiative has delimited more than 10,000 putative species and assigned temporary code names, indicating that reliable reference data remains insufficient for definitive polyphasic identifications. This highlights the substantial ongoing need for further research to establish formal scientific names - either from previously published species or as novel descriptions.

References:

Abarenkov, K., Kõljalg, U., & Nilsson, R. H. (2022). UNITE Species Hypotheses Matching Analysis. Biodiversity Information Science and Standards, 6, e93856. https://doi.org/10.3897/biss.6.93856

Canan K., Quark, M., Russell S., Ostuni S., Rockefeller A., Williams J., Culliton S., Geurin Z, Birkebak J. (2024) Introducing the Ohio Mushroom DNA Lab: Early Lessons and Contributions from a New Community-Driven Nanopore Sequencing Laboratory. McIlvainea.

Meiklejohn, K. A., Damaso, N., & Robertson, J. M. (2019). Assessment of BOLD and GenBank – Their accuracy and reliability for the identification of biological materials. PLOS ONE, 14(6), e0217084. https://doi.org/10.1371/journal.pone.0217084

Nilsson, R. H., Larsson, K.-H., Taylor, A. F. S., Bengtsson-Palme, J., Jeppesen, T. S., Schigel, D., Kennedy, P., Picard, K., Glöckner, F. O., Tedersoo, L., Saar, I., Kõljalg, U., & Abarenkov, K. (2018). The UNITE database for molecular identification of fungi: Handling dark taxa and parallel taxonomic classifications. Nucleic Acids Research, 47(D1), D259–D264. https://doi.org/10.1093/nar/gky1022

Russell, S. (2022). Online Forays for Macrofungi: Expediting the Rate of Documenting Biodiversity. bioRxiv, 2022.05.24.493314. https://doi.org/10.1101/2022.05.24.493314

Tulloss, R. (2024). Amanita sp-IN01—Amanitaceae.org—Taxonomy and Morphology of Amanita and Limacella. Amanita Sp-IN01. Retrieved February 3, 2024, from http://www.amanitaceae.org/?Amanita+sp-IN01

Tulloss, R., & Yang, Z. (2024). Family Amanitaceae—Amanitaceae.org—Taxonomy and Morphology of Amanita and Limacella. Amanitaceae Studies. Retrieved February 3, 2024, from http://www.amanitaceae.org/?Family+Amanitaceae

Turland, N. J., Wiersema, J. H., Barrie, F. R., Greuter, W., Hawksworth, D. L., Herendeen, P. S., Knapp, S., Kusber, W.-H., Li, D.-Z., & Marhold, K. (2018). International Code of Nomenclature for algae, fungi, and plants (Shenzhen Code) adopted by the Nineteenth International Botanical Congress Shenzhen, China, July 2017. Koeltz botanical books.