Accuracy in the identification of orchids of the genus Angraecum by taxonomists and non-taxonomists

Mackay-Smith, Thomas H.; Roberts, David L.

doi:10.1007/s12225-019-9813-6

Cited by 6 publications

(5 citation statements)

References 18 publications

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“…Identification errors may have affected our results (Mackay‐Smith & Roberts, 2019), but are unlikely to have had the same influence as spatial inconsistencies (Maldonado et al, 2015) such as sampling and specimen collection biases (e.g., along roadsides) (Oliveira et al, 2016). There is yet to be an automated method to detect identification errors within occurrence data due to the complex science of plant names (Thomson et al, 2018) therefore manual checks are still required.…”

Section: Discussionmentioning

confidence: 97%

To clean or not to clean: Cleaning open‐source data improves extinction risk assessments for threatened plant species

Panter

Clegg

Moat

et al. 2020

Conservat Sci and Prac

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Plants are under-represented in conservation efforts, with only 9% of described species published on the IUCN Red List. Biodiversity aggregators including the Global Biodiversity Information Facility (GBIF) and the more recent Botanical Information and Ecology Network (BIEN) contain a wealth of potentially useful occurrence data. We investigate the influence of these data in accelerating plant extinction risk assessments for 225 endemic, near-endemic, and socioeconomic Bolivian plant species. Geo-referenced herbarium voucher specimens verified by taxonomic experts comprised our control data set. Open-source data for 77 species was subjected to a two-stage cleaning protocol (using an automated R package followed by a manual clean) and threat categories were computed based on extent of occurrence thresholds. Accuracy was the highest using cleaned GBIF data (76%) and uncleaned BIEN data (79%). Sensitivity was the highest for cleaned GBIF (73%) and BIEN (80%) data suggesting our cleaning protocol was essential to maximize sensitivity rates. Comparisons between the control, GBIF and BIEN data sets revealed a paucity of occurrence data for 148 species (66%), 72% of which qualified for a threatened category. Balancing data quantity and accuracy must be considered when using opensource data. Filling data gaps for threatened species is a conservation priority to improve the coverage of threatened species within biodiversity aggregators.

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Section: Discussionmentioning

confidence: 97%

To clean or not to clean: Cleaning open‐source data improves extinction risk assessments for threatened plant species

Panter

Clegg

Moat

et al. 2020

Conservat Sci and Prac

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show abstract

“…As currently estimated, 350,510 described plant species names are accepted in the world (WFO, 2021). Species identification mainly depends on taxonomists and their work, yet even for specialists, species identification is not always straightforward (Mackay‐Smith & Roberts, 2019). Even worse, experts in species identification are dwindling rapidly, with training pipelines shrinking due to a variety of structural reasons broadly referred to as the “taxonomic impediment” (Engel et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…plastid genome, super-barcodes, recently diverged, Schima, standard barcodes straightforward (Mackay-Smith & Roberts, 2019). Even worse, experts in species identification are dwindling rapidly, with training pipelines shrinking due to a variety of structural reasons broadly referred to as the "taxonomic impediment" (Engel et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Species discrimination in Schima (Theaceae): Next‐generation super‐barcodes meet evolutionary complexity

Jiang

Folk

et al. 2022

Molecular Ecology Resources

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Plastid genome and nuclear ribosomal DNA (nrDNA) arrays, proposed recently as “super‐barcodes,” might provide additional discriminatory power and overcome the limitations of traditional barcoding loci, yet super‐barcodes need to be tested for their effectiveness in more plant groups. Morphological homoplasy among Schima species makes the genus a model for testing the efficacy of super‐barcodes. In this study, we generated multiple data sets comprising standard DNA barcodes (matK, rbcL, trnH‐psbA, nrITS) and super‐barcodes (plastid genome, nrDNA arrays) across 58 individuals from 12 out of 13 species of Schima from China. No samples were correctly assigned to species using standard DNA barcodes and nrDNA arrays, while only 27.27% of species with multiple accessions were distinguished using the plastid genome and its partitioned data sets—the lowest estimated rate of super‐barcode success in the literature so far. For Schima and other taxa with similarly recently divergence and low levels of genetic variation, incomplete lineage sorting, hybridization or taxonomic oversplitting are all possible causes of the failure. Taken together, our study suggests that by no means are super‐barcodes immune to the challenges imposed by evolutionary complexity. We therefore call for developing multilocus nuclear markers for species discrimination in plant groups.

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“…Indeed, our dataset and subsequent analysis incorporated some herbarium specimen identification as they were originally recorded. Based on our expertise (but also Mackay-Smith and Roberts (2019) ), it is important to note that such identifications can carry a substantial margin of error, with higher discrepancies observed for more intricate genera (e.g. Liparis Rich.…”

Section: Discussionmentioning

confidence: 99%

Diversity and distribution of Orchidaceae in one of the world's most threatened plant hotspots (Madagascar)

Droissart,

Verlynde,

Ramandimbisoa

et al. 2023

BDJ

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Introduction. In recent decades, Madagascar has become one of the most important plant hotspots in the world. The country's remaining forests and vegetation are disappearing at an alarming rate, while dozens of new species are discovered each year. Amongst the plant families that have long been studied, Orchidaceae appear as one of the most charismatic, diverse and of high conservation concern. Based on a reviewed, comprehensive herbarium dataset, we have compiled a curated checklist of all orchid species occurring in Madagascar. Based on this complete dataset, we then compiled sampling effort, species diversity distribution and some general statistics on their ecology and IUCN conservation status. Methods. We compiled and standardised a global dataset using five public databases as the main data sources, supplemented by the most recent publications. The database contains ~ 10,000 geolocated records collected between 1816 and 2021. We used GIS software and rarefaction methods to examine sampling and diversity patterns. Results. According to our dataset, there are currently 913 orchid species collected in Madagascar, of which 759 orchid species (83.1%) are endemic. Doubling the sampling effort could lead to the discovery of around 100 more species, bringing the total estimated number of orchid species in Madagascar to between 986 and 1048. About one-third (297 species) of all orchid species are known only by type specimens (189 species) or have not been collected in Madagascar for more than 50 years (214 species). Although the raw data show that the Andasibe-Moramanga area would have the highest orchid species concentration, our analysis of the data, adjusted for bias, shows that the centres of orchid diversity in Madagascar are in the Tsaratanàna Strict Nature Reserve and the Ranomafana National Park. Life-form statistics show that 55.0% of orchid species are strict epiphytes. The main flowering period of orchids in Madagascar is between November and March. To date, 84% of the 226 Malagasy orchid species listed in the IUCN Red List are threatened with extinction (CR, EN or VU). Conclusion. Despite geographically uneven coverage, the biodiversity of Malagasy orchids appears to be already well documented. We provide maps corrected for sampling bias that indicate priority areas for future surveys. Upcoming efforts should also focus on rediscovery and conservation of rare and/or threatened species and ensure that the protected area network is well aligned with the distribution of priority species for conservation. Finally, the conservation status of 75% of the orchid species found in Madagascar is not yet known and the inclusion of these species must be a top priority in the coming years.

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Accuracy in the identification of orchids of the genus Angraecum by taxonomists and non-taxonomists

Abstract: The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

Cited by 6 publications

References 18 publications

To clean or not to clean: Cleaning open‐source data improves extinction risk assessments for threatened plant species

To clean or not to clean: Cleaning open‐source data improves extinction risk assessments for threatened plant species

Species discrimination in Schima (Theaceae): Next‐generation super‐barcodes meet evolutionary complexity

Diversity and distribution of Orchidaceae in one of the world's most threatened plant hotspots (Madagascar)

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