The effects of phylogenetic relatedness on invasion success and impact: deconstructing Darwin's naturalisation conundrum
Bibliographic record
Abstract
Darwin's naturalisation conundrum describes the paradox that the relatedness of exotic species to native residents could either promote or hinder their success through opposing mechanisms: niche pre-adaptation or competitive interactions. Previous studies focusing on single snapshots of invasion patterns have provided support to both sides of the conundrum. Here, by examining invasion dynamics of 480 plots over 40 years, we show that exotic species more closely related to native species were more likely to enter, establish and dominate the resident communities, and that native residents more closely related to these successful exotics were more likely to go locally extinct. Therefore, non-random displacement of natives during invasion could weaken or even reverse the negative effects of exotic-native phylogenetic distances on invasion success. The scenario that exotics more closely related to native residents are more successful, but tend to eliminate their closely related natives, may help to reconcile the 150-year-old conundrum.
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".