Nitrogen pools and processes in agricultural systems of Coastal British Columbia — A review of published research
Bibliographic record
Abstract
A significant amount of research on nitrogen (N) dynamics has been conducted within the past 20 yr in south coastal British Columbia. This succinct set of data has practical and environmental information on N cycling particularly focusing on gains to and losses from agricultural fields, and transformations of soil N pools. Coastal British Columbia fields have received large annual additions by application of fertilizer and manure. Some of the manure N from animals using locally grown forages is recycled within the farm operation, but a large amount of N is imported as feed especially for intensive animal production. Budget calculations estimated that there may be substantial losses of N through volatilization from manure, particularly from housing and storage areas, and during application to fields. Some of the volatilized ammonia in holding areas may be recycled to fields via precipitation. Direct measurements of these losses and returns of N have not been made. Studies have shown that there is limited risk of leaching of nitrate beyond the root zone during the growing season because most of the annual rainfall occurs over the winter and because nitrate can be adsorbed to soil particles. However, any extractable inorganic N (nitrate directly and ammonium after nitrification) in the profile at the end of the growing season will be lost over the winter. Most of that loss is due to nitrate leaching, but conditions are also favorable for denitrification. There is considerable (> 200 mg N k−1 in some soils) ammonium-N fixed in Fraser Valley soils, but the impact of this phenomenon to crop growth is still poorly understood. Wetting and drying cycles have a great influence on the dynamics of this pool of soil N. The response of spring growth of grass to the time of N application was influenced by the relative competitiveness of microorganisms and plants for available soil N. A study comparing short-season (broccoli) and long-season (sweet corn) crop responses to N applications showed that the rate at which the plants require N influences their response to N amendments. Raspberries were found to require relatively small quantities of N on a land area basis because of the wide inter-row distances. An autumn soil nitrate test has been proposed for making fertilizer N recommendations for raspberries. Although knowledge gained from this research has provided a basis for interpreting studies for the development of N management practices and for making interim recommendations, a method to predict the amount of N mineralized from soil organic matter is key to the development of soil-analysis-based N rate recommendations. Key words: N cycling, nitrate, ammonium, fixed ammonium, soil organic N, mineralization
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".