Taxon‐ and vector‐specific variation in species richness and abundance during the transport stage of biological invasions
Bibliographic record
Abstract
Recent empirical and statistical evidence suggest that propagule pressure (i.e., number of individuals introduced per event, and the number and frequency of events) and colonization pressure (i.e., number of species released per event, and the number and frequency of events) are of vital importance to invasion success. To explore possible changes in propagule and colonization pressure during the transport stage of the invasion process, we examine abundance and species richness of virus‐like particles, bacteria, diatoms, dinoflagellates, and invertebrates transported in commercial ships—a leading vector for global spread of aquatic nonindigenous species. We collected 154 ballast water samples from ships that had performed or were exempt from ballast water exchange (BWE) prior to arrival at Pacific and Atlantic ports in Canada and Laurentian Great Lakes ports. We found that abundance and species richness varied across taxa and regions, with ships arriving to the Atlantic region carrying the highest abundance of taxa. The highest species richness of invertebrates and diatoms was recorded from ships arriving to the Pacific, whereas the richest communities of dinoflagellates occurred in the Atlantic region. We also found that BWE had no effect on abundance or species richness of most taxa (dinoflagellates, diatoms, bacteria, and virus‐like particles), whereas the effect on abundance of invertebrates was not clear. Finally, longer voyages resulted in lower abundance of all taxa except dinoflagellates, and lower species richness of diatoms. Paradoxically, the elevated abundance and species richness of dinoflagellates following BWE suggest that this group could have enhanced invasion potential when ships manage ballast water by exchange.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".