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Record W4280577124 · doi:10.1111/acv.12788

‘Lost’ taxa and their conservation implications

2022· article· en· W4280577124 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

VenueAnimal Conservation · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIUCN Red ListExtinction (optical mineralogy)TaxonData deficientEcologyBiologyBiodiversityEndangered speciesThreatened speciesConservation statusTaxonomic rankGlobal biodiversityGeographyHabitat

Abstract

fetched live from OpenAlex

Abstract While biological extinctions are predicted to rise sharply during the Anthropocene, extinction declarations are rare, partly due to inherent uncertainties in knowing when the last individual of a species has died. This has led to the growth of a group of ‘lost’ species that have not been observed in decades or even centuries, yet are not declared extinct, and as such possess an uncertain conservation status. The existence of such species may prove increasingly problematic as the extinction crisis worsens, given that their presence may create uncertainty with respect to conservation prioritization efforts and to our understanding of extinction rates. We provide the first assessment of the extent of lost taxa, defined as species that have not been reliably observed in >50 years yet are not declared extinct, for terrestrial vertebrates (amphibians, reptiles, birds and mammals). We reviewed information from IUCN Red List accounts within these Classes using a hybrid code‐based search/manual assessment approach, supplemented with consultation of recent literature. In total, we identify a total of 562 lost species (137 amphibians, 257 reptiles, 38 birds and 130 mammals). Of these, 13% (75 species) are listed as ‘Possibly Extinct’ by the IUCN. Lost species outnumber extinct species for all studied Classes except birds. They were mainly confined to the tropics (92.5%), with distributions being particularly concentrated in ‘mega‐diverse’ countries, as expected. Indonesia (69 species), Mexico (33 species) and Brazil (29 species) possessed the most lost species overall. Our results highlight the prevalence of lost taxa among terrestrial vertebrates and identify ‘hotspots’ for these species where future survey efforts should be prioritized. We suggest minor adjustments to IUCN Red List accounts to allow lost species to be better tracked, including more consistent use of the ‘Possibly Extinct’ marker and wider application of the ‘last seen date’ field.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.972

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)0.0290.000

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 head0.043
GPT teacher head0.245
Teacher spread0.202 · 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