Faster speciation of fig‐wasps than their host figs leads to decoupled speciation dynamics: Snapshots across the speciation continuum
Bibliographic record
Abstract
Even though speciation involving multiple interacting partners, such as plants and their pollinators, has attracted much research, most studies focus on isolated phases of the process. This currently precludes an integrated understanding of the mechanisms leading to cospeciation. Here, we examine population genetic structure across six species-pairs of figs and their pollinating wasps along an elevational gradient in New Guinea. Specifically, we test three hypotheses on the genetic structure within the examined species-pairs and find that the hypothesized genetic structures represent different phases of a single continuum, from incipient cospeciation to the full formation of new species. Our results also illuminate the mechanisms governing cospeciation, namely that fig wasps tend to accumulate population genetic differences faster than their figs, which initially decouples the speciation dynamics between the two interacting partners and breaks down their one-to-one matching. This intermediate phase is followed by genetic divergence of both partners, which may eventually restore the one-to-one matching among the fully formed species. Together, these findings integrate current knowledge on the mechanisms operating during different phases of the cospeciation process. They also reveal that the increasingly reported breakdowns in one-to-one matching may be an inherent part of the cospeciation process. Mechanistic understanding of this process is needed to explain how the extraordinary diversity of species, especially in the tropics, has emerged. Knowing which breakdowns in species interactions are a natural phase of cospeciation and which may endanger further generation of diversity seems critical in a constantly changing world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".