Tomorrow Never Dies: biodegradation and subsequent viability of invasive macrophytes following exposure to aquatic disinfectants
Bibliographic record
Abstract
Aquatic invasive alien species (IAS) negatively impact freshwater ecosystems worldwide. As suppression and eradication of established invader populations are often complex, costly and resource-intensive, the prevention of further invader spread is considered a key aspect of proactive management measures. Although broad spectrum aquatic disinfectants have been suggested as a suitable decontamination mechanism to enhance invader spread-prevention strategies, inconsistencies concerning their effectiveness are reported within the literature. Here, we examine the use of two aquatic disinfectants, which were developed to kill damaging microbes, to induce substantial degradation of the apical fragmentary propagules of five invasivemacrophytes: Crassula helmsii (Kirk) Cockayne; Egeria densa Planchon; Elodeacanadensis Michx; Hydrocotyle ranunculoides Linnaeus; Lagarosiphon major(Ridley) Moss. Apical fragments were exposed to 0% (0 g L-1), 2% (20 g L-1) or 4%(40 g L-1) solutions of Virkon® Aquatic and Virasure® Aquatic, for submergencetreatments of five, fifteen, thirty or sixty minutes. After 28 days, degradation of treated fragments was significantly greater than that of control groups, particularlyfor 4% solutions and longer exposure times. Despite this, sustained viability in relation to shoot and/or root regrowth was exhibited by almost all plant species.However, new shoot growth rates were significantly reduced following exposure toall treatments. At matched concentrations, there was no significant difference between the two disinfectants. Overall, it appears that the examined aquatic disinfectants will not curtail the spread of these invasive macrophytes. Yet, longer submergence times, multiple applications and synergistic effects of different biosecurity treatments may enhance preventative measures against further spread and this requires investigation.
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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 | 0.000 | 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 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".