RESEARCH ARTICLE Phosphorus Cycling in Montreal’s Food and Urban Agriculture Systems
Bibliographic record
Abstract
Cities are a key system in anthropogenic phosphorus (P) cycling because they concentrate both P demand and waste production. Urban agriculture (UA) has been proposed as a means to improve P management by recycling cities ’ P-rich waste back into local food pro-duction. However, we have a limited understanding of the role UA currently plays in the P cycle of cities or its potential to recycle local P waste. Using existing data combined with sur-veys of local UA practitioners, we quantified the role of UA in the P cycle of Montreal, Cana-da to explore the potential for UA to recycle local P waste. We also used existing data to complete a substance flow analysis of P flows in the overall food system of Montreal. In 2012, Montreal imported 3.5 Gg of P in food, of which 2.63 Gg ultimately accumulated in landfills, 0.36 Gg were discharged to local waters, and only 0.09 Gg were recycled through composting. We found that UA is only a small sub-system in the overall P cycle of the city, contributing just 0.44 % of the P consumed as food in the city. However, within the UA sys-tem, the rate of recycling is high: 73 % of inputs applied to soil were from recycled sources. While a Quebec mandate to recycle 100 % of all organic waste by 2020 might increase the role of UA in P recycling, the area of land in UA is too small to accommodate all P waste pro-duced on the island. UA may, however, be a valuable pathway to improve urban P sustain-ability by acting as an activity that changes residents ’ relationship to, and understanding of, the food system and increases their acceptance of composting.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".