Factors influencing progress toward sympatric speciation
Bibliographic record
Abstract
Many factors could influence progress towards sympatric speciation. Some of the potentially important ones include competition, mate choice and the degree to which alternative sympatric environments (resources) are discrete. What is not well understood is the relative importance of these different factors, as well as interactions among them. We use an individual-based numerical model to investigate the possibilities. Mate choice was modelled as the degree to which male foraging traits influence female mate choice. Competition was modelled as the degree to which individuals with different phenotypes compete for portions of the resource distribution. Discreteness of the environment was modelled as the degree of bimodality of the underlying resource distribution. We find that strong mate choice was necessary, but not sufficient, to cause sympatric speciation. In addition, sympatric speciation was most likely when the resource distribution was strongly bimodal and when competition among different phenotypes was intermediate. Even under these ideal conditions, however, sympatric speciation occurred only a fraction of the time. Sympatric speciation owing to competition on unimodal resource distributions was also possible, but much less common. In all cases, stochasticity played an important role in determining progress towards sympatric speciation, as evidenced by variation in outcomes among replicate simulations for a given set of parameter values. Overall, we conclude that the nature of competition is much less important for sympatric speciation than is the nature of mate choice and the underlying resource distribution. We argue that an increased understanding of the promoters and inhibitors of sympatric speciation is best achieved through models that simultaneously evaluate multiple potential factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".