Revisiting Darwin's naturalization conundrum: explaining invasion success of non‐native trees and shrubs in southern Africa
Bibliographic record
Abstract
Summary Invasive species are detrimental ecologically and economically. Their negative impacts in Africa are extensive and call for a renewed commitment to better understand the correlates of invasion success. Here, we explored several putative drivers of species invasion among woody non‐native trees and shrubs in southern Africa, a region of high floristic diversity. We tested for differences in functional traits between plant categories using a combination of phylogenetic independent contrasts and a simulation‐based phylogenetic anova . We found that non‐native species generally have longer flowering duration compared with native species and are generally hermaphroditic, and their dispersal is mostly abiotically mediated. We also revealed that non‐native trees and shrubs that have become invasive are less closely related to native trees and shrubs than their non‐invasive non‐native counterparts. Non‐natives that are more closely related to the native species pool may be more likely to possess traits suited to the new environment in which they find themselves and thus have greater chance of establishment. However, successful invaders are less closely related to the native pool, indicating evidence for competitive release or support for the vacant niche theory. Synthesis . Non‐native trees and shrubs in southern Africa are characterized by a suite of traits, including long flowering times, a hermaphroditic sexual system and abiotic dispersal, which may represent important adaptations promoting establishment. We suggest that differences in the evolutionary distances separating the native species pool from invasive and non‐invasive species might help resolve Darwin's naturalization conundrum.
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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 | 0.001 | 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".