Temporal change in body mass of two sympatric hamster species and implications for population dynamics
Bibliographic record
Abstract
Shifting of body size distributions of animals has been a long-time focus in population ecology, but the underlying mechanism of density-dependent changes in body size and its implications for population dynamics of animals are largely unknown. In this 26-year study, we investigated intrinsic and extrinsic factors affecting body mass of the Chinese striped hamster (Cricetulus barabensis Pallas, 1773) and the greater long-tailed hamster (Tscherskia triton de Winton, 1899) in the Northern China Plain. We proposed three hypotheses to explain body mass shifts in the two hamster species: growth, survival, and reproduction hypotheses. Our results showed that mean and maximum body masses of both hamster species were positively correlated with population density, and that this density-dependent change in body mass is more likely to be caused by a change in mortality rates, not by a change in growth rates or reproduction rates. The sustained decline of body mass during the study period was probably caused by increased mortality owing to an increase in the area of agricultural irrigation. Our results suggest that, under the condition of lacking survival and growth data, the maximum body mass (which represents survival rate), minimum body mass (which represents growth rate), and mean body mass are very useful criteria in revealing intrinsic and extrinsic effects on population dynamics and the underlying mechanisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".