Implications of female body-size variation for the reproductive ecology of an anuran amphibian
Bibliographic record
Abstract
Animal body size has profound ecological and evolutionary implications for lifespan, access to resources and reproduction. Body size, though, is phenotypically plastic and may be strongly correlated with both fecundity and mate choice. Therefore, temporal variation in body size within populations may correspondingly alter a population’s reproductive ecology over time and, if not taken into account, bias our perception of it. Male Fowler’s Toads (Anaxyrus fowleri) at Long Point, Ontario, have previously been shown to vary in average body size by as much as 18% over a period of 23 years. Here I demonstrate that the females also fluctuate in body size in correlation with their abundance and in synchrony with the males. Clutch size, which averaged 4443 eggs per clutch among 34 females, varied with individual female body size irrespective of temporal variation in average body size or abundance. Body size measurements of females and males in 75 mating pairs over 24 years were, overall, significantly correlated. However, when year-to-year variations in mean body size were accounted for statistically, this apparent evidence of size-assortative mating was negated. These results indicate that abundance, body size and fecundity likely are interrelated aspects of population regulation and that many purported observations of size-assortative mating in animals may need to be re-evaluated.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".