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Record W4399445928 · doi:10.1111/ele.14453

Climate change fluctuations can increase population abundance and range size

2024· article· en· W4399445928 on OpenAlexafffund
Jane Shaw MacDonald, Frithjof Lutscher, Yves Bourgault

Bibliographic record

VenueEcology Letters · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNicheClimate changeExtinction (optical mineralogy)Abundance (ecology)EcologyPopulation sizeRange (aeronautics)PopulationEcological nicheEnvironmental scienceBiologyHabitatDemography

Abstract

fetched live from OpenAlex

Climate change threatens many species by a poleward/upward movement of their thermal niche. While we know that faster movement has stronger impacts, little is known on how fluctuations of niche movement affect population outcomes. Environmental fluctuations often affect populations negatively, but theory and experiments have revealed some positive effects. We study how fluctuations around the average speed of the niche impact a species' persistence, abundance and realized niche width under climate change. We find that the outcome depends on how fluctuations manifest and what the relative time scale of population growth and climate fluctuations are. When populations are close to extinction with the average speed, fluctuations around this average accelerate population decline. However, populations not yet close to extinction can increase in abundance and/or realized niche width from such fluctuations. Long-lived species increase more when their niche size remains constant, short-lived species increase more when their niche size varies.

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 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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score1.000

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)0.0200.001

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 head0.014
GPT teacher head0.237
Teacher spread0.224 · 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; both teacher heads agree on what is shown here.

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

Citations13
Published2024
Admission routes2
Has abstractyes

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