Species and sex ratio differences in mixed populations of hybridogenetic water frogs: The influence of pond features
Bibliographic record
Abstract
Among closely related species with overlapping fundamental niches, usually one species excludes the other(s) unless they differ in their realized niches. In some instances, however, niche overlap is inevitable. One example is European water frogs of the Rana lessonae / R. ridibunda / R. esculenta-complex, where the hybrid R. esculenta is reproductively dependent on one or the other of the two parental species. Hence, it has to live in close sympatry with them, but species and sex ratios in such mixed populations vary widely among ponds. In this paper we investigate the spatial and temporal distribution of the three species by comparing nine ponds with different ecological conditions and frog proportions. All three species occurred in all ponds, but in significantly different absolute and relative numbers. R. lessonae proportions are higher in smaller, more structured ponds with rich vegetation under water while R. ridibunda dominates in larger, less structured ponds with little vegetation under water. The hybrid R. esculenta is intermediate in its distribution; it occurs in larger ponds than R. lessonae, but in more vegetated ones than R. ridibunda. The sex ratios of the three species differ also within the ponds. In R. esculenta, the proportion of females decreased with increasing fluctuation in water temperature. The observed spatial distribution of adults is best explained through species differences in the habitat-related development and survival of their progeny, which is known from several experiments. Temporal changes in species proportions were not related to pond characteristics. This, however, is not surprising, as year-to-year changes in pond features were small, and strong site fidelity, combined with high annual survival, creates substantial temporal autocorrelation between population compositions of successive years.
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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) | 0.002 | 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".