The nature of interspecific interactions and co‐diversification patterns, as illustrated by the fig microcosm
Bibliographic record
Abstract
Interactions between mutualists, competitors, and antagonists have contrasting ecological effects that, sustained over generations, can influence micro- and macroevolution. Dissimilar benefits and costs for these interactions should cause contrasting co-diversification patterns between interacting clades, with prevalent co-speciation by mutualists, association loss by competitors, and host switching by antagonists. We assessed these expectations for a local assemblage of 26 fig species (Moraceae: Ficus), 26 species of mutualistic (pollinating), and 33 species of parasitic (galling) wasps (Chalcidoidea). Using newly acquired gene sequences, we inferred the phylogenies for all three clades. We then compared the three possible pairs of phylogenies to assess phylogenetic congruence and the relative frequencies of co-speciation, association duplication, switching, and loss. The paired phylogenies of pollinators with their mutualists and competitors were significantly congruent, unlike that of figs and their parasites. The distributions of macroevolutionary events largely agreed with expectations for mutualists and antagonists. By contrast, that for competitors involved relatively frequent association switching, as expected, but also unexpectedly frequent co-speciation. The latter result likely reflects the heterogeneous nature of competition among fig wasps. These results illustrate the influence of different interspecific interactions on co-diversification, while also revealing its dependence on specific characteristics of those interactions.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".