Relative role of population density and climatic factors in shaping the body growth rate of Lilford’s Wall Lizard (<i>Podarcis</i> <i>lilfordi</i>)
Bibliographic record
Abstract
The body growth rate in small reptiles is modulated by per-capita food resources and recent evidences suggested that this constraint is the mechanism underlying differences between cohorts. Per-capita food resources depend on population size and climatic factors, but their relative role in explaining the variations in growth rate is unclear. We used morphological data collected over 6 years to model the body growth of an insular lizard (Lilford’s Wall Lizard, Podarcis lilfordi (Günther, 1874)). We used nonlinear equations to describe the appropriate length-at-age relationship. For each sex, seasonal growth was observed and the oscillatory von Bertalanffy curve was fitted to the data. Three age classes were recognized, and we investigated the relative role of density, spring rainfall, and temperature in explaining the variation of the growth rate in each sex-by-age class. Results showed that the relative role of density and climatic factors varied according to the age considered. While population size and temperature had a negative effect on the growth rate of juveniles, rainfall had a positive influence on the growth of subadults. Adult growth was near zero and constant over time. The different role of density-dependent and climatic factors in explaining age-dependent growth rate provides an important insight in understanding lizard population dynamics and life-history tactics.
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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 | 0.001 | 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".