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Demographic Consequences of Phenological Shifts in Response to Climate Change

2021· article· en· W3194746440 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

VenueAnnual Review of Ecology Evolution and Systematics · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPhenologyVital ratesClimate changePopulationEcologyBiologyLife history theoryReproductionPopulation growthDemographyLife history

Abstract

fetched live from OpenAlex

When a phenological shift affects a demographic vital rate such as survival or reproduction, the altered vital rate may or may not have population-level consequences. We review the evidence that climate change affects populations by shifting species’ phenologies, emphasizing the importance of demographic life-history theory. We find many examples of phenological shifts having both positive and negative consequences for vital rates. Yet, few studies link phenological shifts to changes in vital rates known to drive population dynamics, especially in plants. When this link is made, results are largely consistent with life-history theory: Phenological shifts have population-level consequences when they affect survival in longer-lived organisms and reproduction in shorter-lived organisms. However, there are just as many cases in which demographic mechanisms buffer population growth from phenologically induced changes in vital rates. We provide recommendations for future research aiming to understand the complex relationships among climate, phenology, and demography, which will help to elucidate the extent to which phenological shifts actually alter population persistence.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.166
Threshold uncertainty score0.133

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.065
GPT teacher head0.280
Teacher spread0.214 · 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