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Record W4386459836 · doi:10.1002/ppp3.10425

Small and in‐country herbaria are vital for accurate plant threat assessments: A case study from Peru

2023· article· en· W4386459836 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePlants People Planet · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant and Fungal Species Descriptions
Canadian institutionsUniversity of Guelph
FundersNational Geographic Society
KeywordsHerbariumIUCN Red ListGeographyConservation statusBiodiversityEndangered speciesCritically endangeredEcologyBiology

Abstract

fetched live from OpenAlex

Societal Impact Statement Herbaria can be considered plant libraries, each holding collections of dried specimens documenting plant diversity in space and time. For many plant species, these are our only evidence of their existence and the only means of assessing their conservation status. Specimens in all herbaria, especially those in small and often under‐resourced herbaria in megadiverse countries, are key to achieving accurate estimates of the conservation status of the world's plant species. They are also part of a country's shared heritage and critical contributions to knowledge of the world's diversity. Summary Internationally agreed targets to assess the conservation status of all plant species rely largely on digitised distribution data from specimens held in herbaria. Using taxonomically curated databases of herbarium specimen data for the mega‐diverse genera Begonia (Begoniaceae) and Solanum (Solanaceae) occurring in Peru, we test the value added from including data from local herbaria and herbaria of different sizes on estimations of threat status using International Union for Conservation of Nature (IUCN) Red List criteria. We find that the Global Biodiversity Information Facility (GBIF) has little data from Peruvian herbaria and adding these data influences the estimated threat status of these species, reducing the numbers of Critically Endangered and Vulnerable species in both genera. Similarly, adding data from small‐ and medium‐sized herbaria, whether in‐country or not, also improves the accuracy of threat assessments. [Correction added on 08 September 2023, after first online publication: In the preceding sentence, “litter” has been corrected to “little” in this version.] A renewed focus on resourcing and recognising the contribution of small and in‐country herbaria is required if we are to meet internationally agreed targets for plant conservation. We discuss our case study in the broader context of democratising and increasing participation in global botanical science.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.276
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it