Sexual dimorphism, temporal niche differentiation, and evidence for the Jack Sprat effect in an annual dioecious plant
Bibliographic record
Abstract
Abstract Sexual dimorphism in dioecious plants often occurs as a consequence of the different resource requirements of females and males, especially during reproduction. The contrasting reproductive roles of the sexes can influence the phenology of growth, plant size, and flowering time, with implications for the intensity of competitive interactions within and between the sexes. Here, we investigate the influence of contrasting nutrient regimes and intra‐sexual and inter‐sexual competition on the expression of sexual dimorphism in life‐history traits and biomass allocation throughout the life cycle of the dioecious annual Rumex hastatulus Baldw. (Polygonaceae). Development of a sex‐specific marker enabled us to quantify the influence of competition on sex‐specific differences in mortality and vegetative traits. We were particularly interested in determining whether the overall performance of the sexes might differ between the two forms of intra‐specific competition, potentially providing evidence for sexual specialization in resource acquisition and niche differentiation. Our results indicated that although patterns of sexual dimorphism were dynamic, they were largely insensitive to nutrient conditions. We found that intra‐sexual competition was more severe than inter‐sexual competition, differentially affecting mortality and most traits during the vegetative and particularly the reproductive stage of the life history. Female trait values generally increased more under inter‐sexual than intra‐sexual competition in comparison to males. Our findings are consistent with temporal niche differentiation resulting from sexual specialization for different resource requirements and provide evidence for the “Jack Sprat effect.”
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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 | 0.001 | 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".