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Record W4288767099 · doi:10.1111/conl.12881

The disproportionately high value of small patches for biodiversity conservation

2022· article· en· W4288767099 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueConservation Letters · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsCarleton UniversityEspace pour la vie
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiodiversityExtinction (optical mineralogy)HabitatExtinction debtGeographyEcologyHabitat destructionConservation biologyBiology

Abstract

fetched live from OpenAlex

Abstract Small habitat patches have been historically neglected in conservation, primarily because extinction risk is higher in small patches. Nevertheless, sets of small patches usually harbor more species than one or a few larger patches of equal total area. Resolving this inconsistency is key to policy and practice in biodiversity conservation. Our analysis of 32 datasets (603 patches and 2290 taxa) provides two novel lines of evidence confirming that small patches have disproportionately high value for biodiversity. First, sets of small patches harbor more species than large patches even when considering only species of conservation concern. Second, sets of small patches harbor more species than large patches even when the small patches are very small compared to the large patches. Therefore, higher extinction risk in small than large patches does not decrease the cumulative value of small patches for biodiversity. We contend that acknowledging the conservation value of small patches, even very small patches, will be a necessary step for stemming biodiversity loss in the Anthropocene.

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 score0.066
Threshold uncertainty score0.920

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 studies0.0010.000
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 head0.016
GPT teacher head0.203
Teacher spread0.187 · 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