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Record W4310707157 · doi:10.1111/ele.14152

Scale of population synchrony confirms macroecological estimates of minimum viable range size

2022· letter· en· W4310707157 on OpenAlexaff
Juan D. Carvajal‐Quintero, Lise Comte, Xingli Giam, Julian D. Olden, Ulrich Brose, Tibor Erős, Ana Filipa Filipe, Marie‐Josée Fortin, Katie Irving, Claire Jacquet, Stefano Larsen, Albert Ruhí, Sapna Sharma, Fabricio Villalobos, Pablo A. Tedesco

Bibliographic record

VenueEcology Letters · 2022
Typeletter
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsYork UniversityUniversity of Toronto
FundersConsejo Nacional de Ciencia y TecnologíaAgence Nationale de la RechercheDeutsche ForschungsgemeinschaftLaboratoire d'Excellence TULIPASCRS Research Foundation
KeywordsRange (aeronautics)MacroecologyEcologyExtinction (optical mineralogy)Population sizeEcosystemBiologyBiodiversityAbundance (ecology)TaxonScale (ratio)PopulationGeography

Abstract

fetched live from OpenAlex

Global ecosystems are facing a deepening biodiversity crisis, necessitating robust approaches to quantifying species extinction risk. The lower limit of the macroecological relationship between species range and body size has long been hypothesized as an estimate of the relationship between the minimum viable range size (MVRS) needed for species persistence and the organismal traits that affect space and resource requirements. Here, we perform the first explicit test of this assumption by confronting the MVRS predicted by the range-body size relationship with an independent estimate based on the scale of synchrony in abundance among spatially separated populations of riverine fish. We provide clear evidence of a positive relationship between the scale of synchrony and species body size, and strong support for the MVRS set by the lower limit of the range-body size macroecological relationship. This MVRS may help prioritize first evaluations for unassessed or data-deficient taxa in global conservation assessments.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.009
GPT teacher head0.230
Teacher spread0.220 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2022
Admission routes1
Has abstractyes

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