Contrasting effects of phylogenetic relatedness on plant invader success in experimental grassland communities
Bibliographic record
Abstract
Summary Identifying the factors determining the success of invasive species is critical for management of biological invasions. Darwin's naturalization conundrum states that exotic species closely related to natives should be successful because of a shared affinity for local environmental conditions, but at the same time close relatives often compete more intensively, limiting ‘niche’ opportunities for the invaders. Previous studies have generally considered these two ‘opposing’ hypotheses as mutually exclusive, yet evidence for both of them abounds, indicating a practical dilemma for management of biological invasions. In this study, we sowed the seeds of the invasive exotic Ambrosia artemisiifolia L. into 369 experimental plant communities to mimic an introduction of the exotics into a series of new habitats. We further linked the establishment and growth performance of the invader in these experimental communities to the phylogenetic relatedness between the invader and the community residents where it was introduced. We found that the probability of invader establishment declined with increasing phylogenetic distance between the invader and residents, whereas the average size of surviving invader individuals increased with the phylogenetic distance. These results can be at least partly explained by the observations that close relatives tend to create similar soil microhabitat through harbouring similar soil enzymes (e.g. alkaline and acid phosphatases) benefiting invader establishment and that intense competitive interactions between the invader and its close relatives suppressed exotic growth. Synthesis and applications. This study presents the first experimental evidence that phylogenetic relatedness has contrasting effects on different aspects of invader success, thus shedding light on the long‐standing Darwin's naturalization conundrum. Moreover, our findings also have important implications for management of plant invasions: for controlling invasive species characterized by high establishment probability, native species distantly related to the invasive species can be planted in sites surrounding the invasion foci, whereas the opposite seems to be true for controlling those characterized by large individual size.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".