Evaluating efficacy of a ballast water filtration system for reducing spread of aquatic species in freshwater ecosystems
Bibliographic record
Abstract
Biological invasions by non-indigenous species are considered a leading threat to biodiversity, with prevention being a key management strategy. Consequently, numerous commercial ballast water treatment systems have been, or are being, developed to prevent future aquatic invasions. However, most treatment systems are being designed for the many vessels undertaking long transoceanic voyages in marine waters rather than the relatively few vessels operating on short voyages in freshwater, such as those in the Laurentian Great Lakes. Here we conduct testing of the biological efficacy of a 40 µm ballast water filtration unit through shipboard trials. We test the hypotheses that i) filtration will significantly reduce abundance of zooplankton greater than 50 µm in size but not phytoplankton 10 to 50 µm in size; ii) filtration will reduce zooplankton abundances in ballast water below International Maritime Organization discharge standards, but not those of phytoplankton; and iii) filtration will alter the community composition of zooplankton, non-randomly reducing invasion risk of larger taxa. During the summer of 2012, three shipboard trials were conducted. Ballast water samples were collected using a before-after experimental design. Our study showed that filtration significantly reduced abundance of copepods and cladocerans, but not of juvenile dreissenid veligers and rotifers. Contrary to our expectation, phytoplankton densities were also significantly lower after the treatment. Overall, ballast water treated during our tests would not meet proposed international discharge standards. Filtration altered relative abundance of zooplankton, but did not reduce introduction risk of any taxonomic group due to the small juvenile stages and dormant eggs which passed through the treatment. While we do not rule out filtration as a ballast water treatment option for zooplankton in the future, our tests indicate further development is required for meaningful reduction of invasion risk.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".