MétaCan
Menu
Back to cohort
Record W4281477943 · doi:10.1111/ele.14026

Temporal correlations among demographic parameters are ubiquitous but highly variable across species

2022· letter· en· W4281477943 on OpenAlexaff
Rémi Fay, Sandra Hamel, Martijn van de Pol, Jean‐Michel Gaillard, Nigel G. Yoccoz, Paul Acker, Matthieu Authier, Benjamin Larue, Christie Le Cœur, Kaitlin R. Macdonald, Alex Nicol‐Harper, Christophe Barbraud, Christophe Bonenfant, Dirk H. Van Vuren, Emmanuelle Cam, Karine Delord, Marlène Gamelon, María Moirón, Fanie Pelletier, Jay J. Rotella, Céline Teplitsky, Marcel E. Visser, Caitlin P. Wells, Nathaniel T. Wheelwright, Stéphanie Jenouvrier, Bernt‐Erik Sæther

Bibliographic record

VenueEcology Letters · 2022
Typeletter
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversité de SherbrookeUniversité Laval
Fundersnot available
KeywordsEcologyBiologyJuvenilePopulationExtinction (optical mineralogy)Density dependencePopulation ecologyDemography

Abstract

fetched live from OpenAlex

Temporal correlations among demographic parameters can strongly influence population dynamics. Our empirical knowledge, however, is very limited regarding the direction and the magnitude of these correlations and how they vary among demographic parameters and species' life histories. Here, we use long-term demographic data from 15 bird and mammal species with contrasting pace of life to quantify correlation patterns among five key demographic parameters: juvenile and adult survival, reproductive probability, reproductive success and productivity. Correlations among demographic parameters were ubiquitous, more frequently positive than negative, but strongly differed across species. Correlations did not markedly change along the slow-fast continuum of life histories, suggesting that they were more strongly driven by ecological than evolutionary factors. As positive temporal demographic correlations decrease the mean of the long-run population growth rate, the common practice of ignoring temporal correlations in population models could lead to the underestimation of extinction risks in most species.

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)0.003
metaresearch head score (Gemma)0.016
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 score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.013
GPT teacher head0.213
Teacher spread0.200 · 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

Citations56
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueEcology LettersSame topicAvian ecology and behaviorFrench-language works237,207