Efficacy of ‘saltwater flushing’ in protecting the Great Lakes from biological invasions by invertebrate eggs in ships’ ballast sediment
Bibliographic record
Abstract
Summary 1. Mid‐ocean exchange and saltwater flushing were implemented as management practices to reduce the likelihood of new biological invasions in the Laurentian Great Lakes associated with ships’ ballast water and sediments. Despite this, there has been no formal assessment of the efficacy of these procedures. Here, we conduct a comparative analysis of community composition of dormant taxa transported by ballast sediment before and after regulations came into effect in 2006. 2. Ballast sediment samples were collected from 17 ships during the post‐regulation interval of 2007 and 2008. Invertebrate eggs were counted, hatched and species identified in the laboratory. Results were compared to similar samples collected from 39 ships between 2000 and 2002, prior to implementation of saltwater flushing regulations. 3. The estimated amount of residual ballast sediment transported by vessels was significantly lower during the post‐regulation period, ranging from <1 to 45 tonnes per ship, with an average of 5 tonnes. Mean density and number of dormant viable eggs per ship declined 91 and 81%, respectively. 4. Community composition also changed through time, with Rotifera accounting for 78% of taxa transported prior to regulation, whereas Cladocera and Copepoda each accounted for 38% of abundance post‐regulation. Although the number of non‐indigenous species (NIS) declined 73% per ship after 2006, the reduction was not statistically significant; however, the number of freshwater NIS – which pose the greatest risk of invasion for the Great Lakes – was significantly lowered. 5. Our comparative analysis suggests that ballast management regulations enacted in 2006 markedly reduced the probability of introduction of NIS via dormant eggs carried in ballast sediments.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".