Species coexistence: macroevolutionary relationships and the contingency of historical interactions
Bibliographic record
Abstract
Evolutionary biologists since Darwin have hypothesized that closely related species compete more intensely and are therefore less likely to coexist. However, recent theory posits that species diverge in two ways: either through the evolution of 'stabilizing differences' that promote coexistence by causing individuals to compete more strongly with conspecifics than individuals of other species, or through the evolution of 'fitness differences' that cause species to differ in competitive ability and lead to exclusion of the weaker competitor. We tested macroevolutionary patterns of divergence by competing pairs of annual plant species that differ in their phylogenetic relationships, and in whether they have historically occurred in the same region or different regions (sympatric versus allopatric occurrence). For sympatrically occurring species pairs, stabilizing differences rapidly increased with phylogenetic distance. However, fitness differences also increased with phylogenetic distance, resulting in coexistence outcomes that were unpredictable based on phylogenetic relationships. For allopatric species, stabilizing differences showed no trend with phylogenetic distance, whereas fitness differences increased, causing coexistence to become less likely among distant relatives. Our results illustrate the role of species' historical interactions in shaping how phylogenetic relationships structure competitive dynamics, and offer an explanation for the evolution of invasion potential of non-native species.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".