Combining ballast water treatment and ballast water exchange: Reducing colonization pressure and propagule pressure of phytoplankton organisms
Bibliographic record
Abstract
Species richness and species abundance (colonization pressure and propagule pressure, respectively) are commonly used to characterize invasion risk for ballast-water-mediated introductions, which can be high if either parameter is high. For practical reasons, the adopted IMO-D2 standard for organisms in discharged ballast water only considers total abundance of biological indicators, without consideration of species richness or source community. Here we explore the effect of ballast-water source, ballast water exchange, chlorination, or a combination of both (hybrid treatment) on both colonization pressure and propagule pressure for one IMO-D2 size class (≥10 µm and <50 µm; phytoplankton). A strong reduction of propagule pressure was observed in all experimental trials and taxonomic groups, probably owing to environment conditions inside ballast tanks and treatment effects. However, only the hybrid treatment met the IMO-D2 standard for propagule pressure, while also significantly reducing colonization pressure, from 25 initial groups to 16 final groups. In this treatment, dinoflagellates and diatoms dominated final composition. The impact of different treatments on colonization pressure and propagule pressure was always lower when the vessel was ballasted in a brackish than freshwater port. Our study demonstrates that even treated ballast water compliant with the IMO-D2 standard may still harbor a diverse phytoplankton community, albeit with low individual species abundances. These results might be similar even using a type approved ballast water management systems which usually includes a filter for >50 µm organisms as a pre-treatment.
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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 | 0.001 | 0.000 |
| 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 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".