Exceptions and exemptions under the ballast water management convention – Sustainable alternatives for ballast water management?
Bibliographic record
Abstract
The International Convention for the Control and Management of Ships' Ballast Water and Sediments (BWM Convention) aims to mitigate the introduction risk of harmful aquatic organisms and pathogens (HAOP) via ships' ballast water and sediments. The BWM Convention has set regulations for ships to utilise exceptions and exemptions from ballast water management under specific circumstances. This study evaluated local and regional case studies to provide clarity for situations, where ships could be excepted or exempted from ballast water management without risking recipient locations to new introductions of HAOP. Ships may be excepted from ballast water management if all ballasting operations are conducted in the same location (Regulation A-3.5 of the BWM Convention). The same location case study determined whether the entire Vuosaari harbour (Helsinki, Finland) should be considered as the same location based on salinity and composition of HAOP between the two harbour terminals. The Vuosaari harbour case study revealed mismatching occurrences of HAOP between the harbour terminals, supporting the recommendation that exceptions based on the same location concept should be limited to the smallest feasible areas within a harbour. The other case studies evaluated whether ballast water exemptions could be granted for ships using two existing risk assessment (RA) methods (Joint Harmonised Procedure [JHP] and Same Risk Area [SRA]), consistent with Regulation A-4 of the BWM Convention. The JHP method compares salinity and presence of target species (TS) between donor and recipient ports to indicate the introduction risk (high or low) attributed to transferring unmanaged ballast water. The SRA method uses a biophysical model to determine whether HAOP could naturally disperse between ports, regardless of their transportation in ballast water. The results of the JHP case study for the Baltic Sea and North-East Atlantic Ocean determined that over 97% of shipping routes within these regions resulted in a high-risk indication. The one route assessed in the Gulf of Maine, North America also resulted in a high-risk outcome. The SRA assessment resulted in an overall weak connectivity between all ports assessed within the Gulf of the St. Lawrence, indicating that a SRA-based exemption would not be appropriate for the entire study area. In summary, exceptions and exemptions should not be considered as common alternatives for ballast water management. The availability of recent and detailed species occurrence data was considered the most important factor to conduct a successful and reliable RA. SRA models should include biological factors that influence larval dispersal and recruitment potential (e.g., pelagic larval duration, settlement period) to provide a more realistic estimation of natural dispersal.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 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".