The Demographic Basis of Population Growth: A 32‐Year Transient Life Table Response Experiment
Bibliographic record
Abstract
It has recently been recognised that populations are rarely in demographic equilibrium, but rather in a 'transient' state. To examine how transient dynamics influence our empirical understanding of the links between changes in demographic rates and population growth, we conducted a 32-year study of Columbian ground squirrels. The population increased rapidly for 10 years, followed by a 2-year crash, and a gradual 19-year recovery. Transient life table response experiment (LTRE) analysis showed that demographic stochasticity accounted for approximately one-fourth of the variation in population growth, leaving the majority to be explained by environmental influences. These relatively small rodents appeared to have a slow pace of life. But unlike the general pattern for large mammals with slow life histories, ground squirrel survival did not exhibit low variation associated with environmental 'buffering'; instead, survival varied substantially over time and contributed substantially (78%) to changes in abundance over the long-term study, with minor contributions from reproduction and unstable stage structure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".