Research Article |
Corresponding author: Michael D. Pirie ( michael.pirie@uib.no ) Academic editor: Jaime Fagúndez
© 2024 E. G. H. Oliver, Nigel Forshaw, Inge M. Oliver, Fritz Volk, A. W. S. Schumann, Laurence J. Dorr, Rendert D. Hoekstra, Seth D. Musker, Nicolai M. Nürk, Michael D. Pirie, Anthony G. Rebelo.
This is an open access article distributed under the terms of the CC0 Public Domain Dedication.
Citation:
Oliver EGH, Forshaw N, Oliver IM, Volk F, Schumann AWS, Dorr LJ, Hoekstra RD, Musker SD, Nürk NM, Pirie MD, Rebelo AG (2024) Genus Erica: An identification aid version 4.00. PhytoKeys 241: 143-154. https://doi.org/10.3897/phytokeys.241.117604
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Species identification is fundamental to all aspects of biology and conservation. The process can be challenging, particularly in groups including many closely related or similar species. The problem is confounded by the absence of an up-to-date taxonomic revision, but even with such a resource all but professional botanists may struggle to recognise key species, presenting a substantial barrier to vital work such as surveys, threat assessments, and seed collection for ex situ conservation. Genus Erica: An Identification Aid is a tool to help both amateurs and professionals identify (using a limited number of accessible characteristics) and find information about the 851 species and many subspecific taxa of the genus Erica. We present an updated version 4.00, with new features including integrating distribution data from GBIF and iNaturalist, links to taxonomic resources through World Flora Online, and a probability function for identifications, that is freely available for PCs. It remains a work in progress: We discuss routes forward for collaboratively improving this resource.
Ericaceae, GBIF, iNaturalist, species identification, World Flora Online
Species are among the most basic units of biology and ecology, as fundamental as particles in physics and molecules in chemistry. The identification of individual organisms to a scientifically correct species name is of central importance, as it supports communication and allows for linking and extrapolating of information (
Whilst the relatively few European species of Erica are well documented (
This was the motivation behind the development of the Erica Identification Aid (
The characters in question are summarised in the main screen of the version 4.00 of the Erica ID aid (Fig.
The main screen of the Erica ID aid in ‘view’ mode. The top ribbon provides access to, from left to right, the different identification and view modes; separate windows for information sources (open below the ribbon); options for presenting data in the aid; and links to the help file, webpage, and version information. The open windows, clockwise from top left are the characters used for narrowing down possible species identifications with options underneath for showing and finding data within the ID aid or through external links (‘map distributions’ opens Google Earth); distribution (a list of QDS map references in which the taxon is found); subspecific taxa; synonyms presented with World Flora Online (WFO) links; and references, including where available a DOI link to the relevant taxonomic treatment.
The authors developed the Erica ID aid using Microsoft Access as a deliberate alternative to dedicated software packages such as DELTA (
In the more than a decade since the release of version 3.00, the Erica ID aid had become increasingly incompatible with current software and in need of updating and further development. Our aim is to present a new version of the Erica ID aid that works on current PCs and continues to reflect the state of knowledge in Erica taxonomy. It should remain a useful tool for non-professionals, whilst incorporating more information from openly available sources such as World Flora Online (WFO; https://wfoplantlist.org/plant-list/) and the Global Biodiversity Information Facility (GBIF; https://www.gbif.org/) in a way that facilitates access to and improvement of the primary data, also for professional botanists.
Versions 1.00–4.00 are all archived on Zenodo (https://zenodo.org/communities/erica?q=&f=subject%253Aspecies%20identification), including the full installation kit plus the raw data of each as plain text (.CSV). Version 4.00 is available here: https://doi.org/10.5281/zenodo.10407033, including alternative installation kits for those that have specific older versions of MS office installed (any should work in the absence of an MS office installation).
Unless specified, features of version 3.00 are maintained in version 4.00. These include View (all data); Identify (strict matching); Compare (selected characters, diagnostics, photos, or illustrations for two or more taxa); Sort (by taxon, by Schumann and/or by ID number, the latter two reflecting subgeneric classifications); Map (of QDS) was projected using ArcExplorer and is now presented with Google Earth (see below), whilst it is also possible to generate lists of taxa per QDS. A detailed help file is maintained with minor updates. It includes helpful descriptions of characters and a detailed description of the origins of the aid and people involved.
Identification:
• A new probability algorithm as an optional alternative to strict matching of characters, with easy switching between the two, to find taxa with consistent characters or minor mismatches.
The probability algorithm works as follows: Given 21 probability “Groups”, corresponding to the characters with different coded states (including geographic distribution – “regions” – and flowering month, as well as morphological attributes, as listed above), the probability of a given identification is the sum of the probabilities for all the Groups that the user employs. The probability for each component in the Group is calculated to be 1 divided by the number of species that have the specific character state. For example, observing a tubular flowered Erica on the Cape Peninsula: there are 359 Ericas which are coded as corolla shape “tube”, so the “Corolla Shape” Group contributes 1/361 = 0.0027700 to the sum of all Group probabilities, and there are 116 Ericas which are coded as present on the Cape Peninsula, so the “Regions” Group contributes 1/115 = 0.0086956. In this case, the sum of probabilities of each Group is 0.0027700 + 0.0086956 for every Erica coded as Tube and Cape Peninsula. The sum of all probabilities is calculated for all Ericas, and these are displayed in descending order of probability, with those of equal overall probability listed alphabetically. The match algorithm treats coding as “OR” within a Group, as opposed to “AND”, thus reflecting the variation that is common within species but unlikely to be represented in a single specimen. If more than one state is selected by the user, this is treated as uncertainty. The probability for that group is divided by a greater number of taxa exhibiting one or other state and therefore correspondingly reduced, as opposed to dividing by the smaller number of taxa that exhibit both. By considering the prevalence of individual character states, those that are rare will impart a greater probability than those that are more common. The probability algorithm will also be less sensitive to missing data - characters that have yet to be coded for particular taxa (see below) - than strict matching.
Taxonomy and nomenclature:
Distributions:
The Erica ID aid runs on any Windows 10 or Windows 11 PC and uses 502 MB of disk space.
Distribution data presented on a Google Earth map. The Quarter Degree Square (QDS) map references listed in the main aid are projected as grid squares with separate individual dots for openly available GBIF data in different colours for different taxa displayed. In this example, on clicking ‘map distributions’ whilst viewing the inclusive species Erica plukenetii, data points representing observations/specimens determined to species only are presented in red, with those determined to the five different subspecies presented in orange (ssp. bredensis), green (ssp. breviflora), dark blue (ssp. lineata), purple (ssp. penicillata), and light blue (ssp. plukenetii) respectively. On clicking on an individual dot, the underlying information is shown, including links where available, such as in this case an iNaturalist observation. Note that the QDS grid data derived from version 3.00 does not cover all the point data, and that there also isn’t point data representing all the QDS. This could indicate errors and/or gaps in the data that are worth further investigation.
Since the original versions of the Erica ID aid, development of platforms such as iNaturalist, the Biodiversity Heritage Library, and GBIF have dramatically increased open access to information on biological diversity, including photos, literature, and even machine learning based species identification. The latter is currently only trained on around 200 species (represented by >100 photos), and it does not resolve subspecific ranks. Online access can reduce the need for resources within any dedicated identification tool such as the Erica ID aid itself. On the other hand, it is increasingly challenging to filter and quality control the sheer volumes of accessible data online.
As part of the ongoing development of the Erica ID aid, we set out to improve both accessibility and quality of existing online resources for Erica. We shifted from maintaining a limited names database within the Erica ID aid to improving at source and synchronising with openly available data for Erica names and literature through contributing to the development of the World Flora Online (
We incorporated links to iNaturalist data both for species and via GBIF to individual observations. The latter is through a curated dataset downloaded from GBIF representing data from a wider range of sources, including herbarium records, and has been filtered to reduce noise as a resource particularly for conservation prioritisation (
Many of the photos provided in earlier versions of the ID aid were compromised in resolution due to both the limitations of storage media and quality of images available. Those provided from ‘Ericas of South Africa’ (
In version 3.00 a limitation of the Erica ID aid was clearly stated which remains in this new version: “Due to the limited number of characters in this package, use of the Diagnostics & notes may have to be resorted to in order to come to a final decision, but this aspect is far from complete due to the vast number of species that still need to be dealt with” (
Even the current limited numbers of characters are yet to be completely coded for all the taxa in the ID aid. Some characters and regions are better known than others. Data for flowering period, and for Tropical African and particularly Madagascan taxa are very incomplete (Appendix
IUCN threat status is derived from SANBI’s seminal work (
The current implementation, on Windows PCs only, is obviously not ideal: users might wish to use this tool on different platforms, including on mobile devices. This would be an important future step in development of the Erica ID aid, that will be made easier by our archiving and use of openly accessible data.
Tools for species identification are essential for effective conservation efforts, particularly in species rich genera such as Erica. With this new version, the invaluable Erica Identification Aid is updated and openly available, with new features that improve its functionality and integrate online resources such as WFO, GBIF, and iNaturalist and offer scope for wider contributions to improving that primary data.
In the absence of Ted and Inge Oliver as a single hub for Erica taxonomy, it is our hope that future efforts can be spread among a broad group of collaborators, such as coordinated through the Global Conservation Consortium for Erica (
The authors wish to acknowledge invaluable contributions to the accumulated knowledge represented in the Erica ID aid of the following: David Small (1939–2010), Dr Charles Nelson, Dr Alan Elliot (RBGE Edinburgh, particularly for assistance with WFO integration and for reviewing the ms.). Dr. Kenneth Oberlander and Prof. Bengt Oxelman are also thanked for commenting on the ms. Staff at SANBI (the South African National Biodiversity Institute), particularly at the Research Centre at Kirstenbosch who have been supportive of the project. The IT section at SANBI assisted Fritz Volk, providing initial computer tools, and the Compton Herbarium gave permission for photographs to be taken of the Erica specimens and generously backed the original launch of the CD Version 1 in 2004.
In addition to the authors, many people kindly contributed photos over the years: John Oakes(†), Ross Turner, Mario Martinez-Azorin, David Osborne(†), Berit Gehrke, Adam Harrower, Pieter Bester, Mervyn Lotter, Wickus Leeuner, Thys de Villiers, Adrian Mohl, Georg Miehe, David Small(†), Charles Nelson, Alan Hall, Benny Bytebier, Janos Podani, Ralph Clark, Corinne Merry, Petra Wester, Jenny Potgieter, Stefaan Dondeyne, Gavin Schafer, Wesley Berrington, Doug Euston-Brown, Ashley Harvey, Ann Symonds, Nick Helme.
The authors have declared that no competing interests exist.
No ethical statement was reported.
No funding was reported.
Taxonomy: EGHO, IMO, MDP, SDM, LJD, RDH. Programming: NF. Probability algorithm: NF, TR. Mapping: NF, NMN. Illustrations: IMO, EGHO. Photos: AWSS, EGHO, FF, NF, MDP. Writing: drafting: MDP; editing: NF, NMN, SDM, LJD, RDH, AGR.
Nigel Forshaw https://orcid.org/0009-0000-4782-1875
Laurence J. Dorr https://orcid.org/0000-0001-7157-363X
Rendert D. Hoekstra https://orcid.org/0009-0001-1506-7107
Seth D. Musker https://orcid.org/0000-0002-1456-1373
Nicolai M. Nürk https://orcid.org/0000-0002-0471-644X
Michael D. Pirie https://orcid.org/0000-0000-0000-0000
Anthony G. Rebelo https://orcid.org/0000-0003-0403-4470
All of the data that support the findings of this study are available in the main text.
Overview of completeness of character coding by region. Note that the total number of Ericas includes all 851 recognised species plus many (but not all) subspecific taxa. Threat status has been assessed in South Africa at the lowest taxonomic level only, so the numbers for non-assessed taxa include many inclusive species for which subspecific taxa have been assessed individually.
Criteria | Total | South Africa | Agulhas Plain Region | Cape Peninsula | Eastern Cape | Karoo Moun-tain Region | KWA-Zulu Natal | Langeberg Region | North West Region | North South Africa | South East Region | South West Region | Tropical Africa | Mada-gascar | Europe |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Total number of Ericas | 961 | 848 | 103 | 115 | 26 | 119 | 37 | 140 | 167 | 17 | 120 | 467 | 41 | 45 | 28 |
Missing corolla size | 63 | 15 | 2 | 0 | 2 | 1 | 1 | 1 | 0 | 0 | 3 | 5 | 7 | 35 | 6 |
Missing corolla shape | 69 | 14 | 1 | 0 | 1 | 2 | 1 | 1 | 0 | 0 | 3 | 4 | 14 | 35 | 6 |
Missing sepal/corolla length ratio | 53 | 15 | 0 | 0 | 2 | 0 | 2 | 1 | 1 | 1 | 0 | 6 | 18 | 11 | 9 |
Missing stem hairiness | 68 | 20 | 2 | 0 | 2 | 1 | 1 | 1 | 0 | 0 | 2 | 9 | 5 | 36 | 7 |
Missing leaf hairiness | 66 | 20 | 2 | 0 | 2 | 1 | 1 | 1 | 1 | 0 | 1 | 10 | 7 | 35 | 4 |
Missing pedicel hairiness | 70 | 20 | 2 | 0 | 2 | 1 | 1 | 1 | 0 | 0 | 2 | 9 | 9 | 33 | 8 |
Missing sepal hairiness | 74 | 21 | 2 | 0 | 2 | 1 | 1 | 1 | 0 | 0 | 2 | 10 | 11 | 34 | 8 |
Missing corolla hairiness | 66 | 16 | 2 | 0 | 2 | 1 | 1 | 1 | 0 | 0 | 1 | 7 | 11 | 35 | 4 |
Missing ovary hairiness | 70 | 21 | 4 | 2 | 2 | 0 | 1 | 1 | 2 | 0 | 3 | 10 | 7 | 36 | 6 |
Missing style exsertion/inclusion | 76 | 20 | 1 | 0 | 2 | 1 | 1 | 1 | 0 | 0 | 4 | 7 | 11 | 34 | 11 |
Missing anthers exsertion/inclusion | 72 | 17 | 1 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 3 | 7 | 14 | 36 | 5 |
Missing appendage presence/absence | 73 | 20 | 1 | 0 | 2 | 2 | 1 | 1 | 0 | 0 | 3 | 8 | 14 | 34 | 5 |
Missing number of stamens | 63 | 15 | 1 | 0 | 2 | 0 | 1 | 0 | 1 | 0 | 1 | 7 | 10 | 34 | 4 |
Missing number of sepals | 63 | 15 | 1 | 0 | 2 | 1 | 1 | 0 | 1 | 0 | 2 | 6 | 7 | 37 | 4 |
Missing number of corolla lobes | 62 | 16 | 2 | 0 | 2 | 1 | 1 | 0 | 1 | 0 | 2 | 7 | 7 | 36 | 3 |
Missing -nate leaves | 67 | 22 | 2 | 1 | 2 | 1 | 1 | 0 | 0 | 0 | 4 | 11 | 6 | 35 | 4 |
Missing number of bracts | 62 | 15 | 1 | 0 | 2 | 1 | 1 | 0 | 1 | 0 | 2 | 6 | 10 | 33 | 4 |
Missing fire survival strategy | 6 | 6 | 0 | 0 | 3 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 |
Missing flowering month | 102 | 29 | 2 | 0 | 2 | 2 | 2 | 0 | 1 | 1 | 4 | 14 | 22 | 42 | 9 |
Missing IUCN Red List category | 242 | 145 | 15 | 25 | 14 | 19 | 25 | 23 | 30 | 9 | 26 | 69 | 31 | 45 | 21 |