Beyond propagule pressure: importance of selection during the transport stage of biological invasions
Bibliographic record
Abstract
Biological invasions are largely considered to be a "numbers game", wherein the larger the introduction effort, the greater the probability that an introduced population will become established. However, conditions during transport - an early stage of the invasion - can be particularly harsh, thereby greatly reducing the size of a population available to establish in a new region. Some successful non-indigenous species are more tolerant of environmental and anthropogenic stressors than related native species, possibly stemming from selection (ie survival of only pre-adapted individuals for particular environmental conditions) during the invasion process. By reviewing current literature concerning population genetics and consequences of selection on population fitness, we propose that selection acting on transported populations can facilitate local adaptation, which may result in a greater likelihood of invasion than predicted by propagule pressure alone. Specifically, we suggest that detailed surveys should be conducted to determine interactions between molecular mechanisms and demographic factors, given that current management strategies may underestimate invasion risk.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".