Interactions between reactive nitrogen and the Canadian landscape: A budget approach
Bibliographic record
Abstract
Abstract The movement of excess reactive nitrogen (N r ) from anthropogenic activities to natural ecosystems has been described as one of the most serious environmental threats facing modern society. One of the approaches for tracking this movement is the use of budgets that quantify fluxes. We constructed an N r budget for Canada using measured and modeled values from the scientific literature, government databases, and data from new agri‐environmental indicators, in order to produce information for policy makers and scientists to understand the major flows of nitrogen to allow a better assessment of risks to the Canadian environment. We divided the Canadian territory south of 60°N into areas dominated by natural ecosystems, as well as by agricultural and urban/industrial activities to evaluate N r flows within, between, and out of these units. We show that Canada is a major exporter of N r due to the availability of inexpensive commercial fertilizers. The large land area suitable for agriculture makes Canada a significant agricultural N r exporter of both grain crops and livestock. Finally, Canada exports petroleum N mainly to the United States. Because of its location and prevailing atmospheric transport patterns, Canada is a net receptor of N r air pollution from the United States, receiving approximately 20% of the N r leaving the U.S. airshed. We found that overall, terrestrial natural ecosystems as well as the atmosphere are in balance between N r inputs and outputs when all N reactive and nonreactive fluxes are included. However, when only reactive forms are considered, almost 50% of N entering the Canadian atmosphere cannot be accounted for and is assumed to be lost to the Atlantic and Arctic oceans or to unmeasured dry deposition. However, agricultural and freshwater landscapes are showing large differences between measured inputs and outputs of N as our data suggest that denitrification in soils and aquatic systems is larger than what models predict. Our work also shows that Canada is a major contributor to the global flow of nitrogen through commercial exports.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".