Relationship between propagule pressure and colonization pressure in invasion ecology: a test with ships' ballast
Bibliographic record
Abstract
Increasing empirical evidence indicates the number of released individuals (i.e. propagule pressure) and number of released species (i.e. colonization pressure) are key determinants of the number of species that successfully invade new habitats. In view of these relationships, and the possibility that ships transport whole communities of organisms, we collected 333 ballast water and sediment samples to investigate the relationship between propagule and colonization pressure for a variety of diverse taxonomic groups (diatoms, dinoflagellates and invertebrates). We also reviewed the scientific literature to compare the number of species transported by ships to those reported in nature. Here, we show that even though ships transport nearly entire local communities, a strong relationship between propagule and colonization pressure exists only for dinoflagellates. Our study provides evidence that colonization pressure of invertebrates and diatoms may fluctuate widely irrespective of propagule pressure. We suggest that the lack of correspondence is explained by reduced uptake of invertebrates into the transport vector and the sensitivity of invertebrates and diatoms to selective pressures during transportation. Selection during transportation is initially evident through decreases in propagule pressure, followed by decreased colonization pressure in the most sensitive taxa.
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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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".