A Field Bioassay of Nitrogen and Phosphorus Phytoextraction from Biosolids in a Seasonally Frozen End‐of‐Life Municipal Lagoon Vegetated with Cattail
Bibliographic record
Abstract
Managing biosolids from end‐of‐life municipal lagoons is a major challenge for many small communities where landfilling or spreading of biosolids on farmland is restricted. Contaminant removal via phytoextraction may be a viable remediation option for end‐of‐life lagoons in such communities. This study examined the effect of harvest frequency (once or twice per season) on cattail ( Typha latifolia L.) biomass yield and N and P removal under a terrestrial phytoremediation system designed to treat the dewatered secondary cell of a municipal lagoon in Manitoba, Canada. Cattail was harvested once or twice per season from eight vegetation transects, each divided into two plots (2.5 × 2.5 m) to accommodate the two harvest frequencies. Biomass yields were greater for the single harvest (5.7 t ha −1 yr −1 ) than for two harvests per season (4.8 t ha −1 yr −1 ). This was mirrored by N phytoextraction, which was also greater for the single harvest (71 kg ha −1 yr −1 ) than the two‐harvest frequency (58 kg ha −1 yr −1 ). Phosphorus phytoextraction varied with year of harvest and ranged from 8 to 14 kg ha −1 yr −1 . Cumulative N and P phytoextraction amounts during the 5 yr were 330 kg N ha −1 and 57 kg P ha −1 . A greater fraction of N (51–91 kg ha −1 yr −1 ) and P (23–40 kg ha −1 yr −1 ) was sequestered in the belowground biomass (11–17 t ha −1 yr −1 ) and therefore was not removed by harvesting. These results show that phytoremediation using cattail is a viable option for managing N and P in end‐life lagoons. Core Ideas Seasonally frozen end‐of‐life municipal lagoon was amenable to terrestrial phytoremediation. We effectively phytoextracted N and P from municipal biosolids. Cattail biomass yields were greater with one than two annual harvests. Cumulative N and P phytoextraction was greater with one than two annual harvests. Greater fractions of N and P were sequestered in the belowground biomass.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".