Morphological data quantifying sexual dimorphism of Anolis carolinensis in presence and absence of congener
Bibliographic record
Abstract
Natural selection favors sexual dimorphism that reduces resource competition between the sexes of the same species. However, niche partitioning among interspecific competitors should counter such divergence, as partitioning the niche results in smaller total niche widths for each individual species, leaving less room for the sexes to diverge. A straightforward (and long-standing) hypothesis emerges: species in competitor-rich ecological communities should show less sexual dimorphism than species in competitor-poor ecological communities. Here, we test this prediction using a well-documented natural experiment generated by the recent arrival of Anolis sagrei to a set of small islands in Mosquito Lagoon, Florida, containing Anolis carolinensis. Despite known interspecific habitat partitioning and rapid evolution in habitat-use traits by A. carolinensis in this system, sexual dimorphism between male and female A. carolinensis was not reduced as predicted on two-species islands relative to islands with only A. carolinensis. This is consistent with a small but growing body of empirical tests of the dimorphism-richness hypothesis that have been ambiguous in their support at best. A rethinking of the validity of this intuitive hypothesis is needed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.022 |
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".