Timing, Magnitude, and Isotopic Composition of Nitrate Leached Under Red Raspberries Over an Unconfined Aquifer With High Annual Recharge
Bibliographic record
Abstract
The highly conductive, trans-boundary Abbotsford-Sumas Aquifer (ASA) has a decadal scale history of nitrate contamination linked to high groundwater recharge and intensive agricultural land use including livestock and perennial berry (particularly raspberries) production. This thesis aimed to better understand the controls on nitrate leaching under raspberries over the ASA. To achieve this, the temporal and spatial variability of nitrate leaching under experimental and commercially managed stands were examined using Passive Capillary wick Samplers below the root zone and high-resolution passive diffusion samplers in the shallow groundwater. High seasonal variation was observed when comparing the δ15NNO3 values of leachate nitrate collected under experimental plots receiving either fertilizer (-2.4 to +8.7 ‰) or manure (+1.6 to +9.6 ‰), which, in many cases, precluded a clear distinction between the two treatment nitrate sources. Some of this seasonal variation was attributed to the application of growing season irrigation. Likewise, the unexpectedly high proportion of annual nitrate leaching under commercially managed raspberries during spring and summer (29 and 39%) was attributed to growing season irrigation. Although the irrigation water and fertilizer were placed only along the raspberry rows, approximately 60 % of nitrate leaching occurred under the alley areas between the rows, indicating that improved alley management may be important for managing nitrate leaching losses. Raspberry stand renovation (canes chopped, soil fumigated and tilled, and manure applied before replanting), which typically occurs every 6-10 years in response to decreased crop vigour, resulted in 246 kg-N-ha-1 leached under the commercial stand during the year following manure application and replanting compared to an average of 72 kg-N-ha-1 during later years. Results from this study site suggests that for a 10-year renovation cycle, approximately 23 % of the nitrate loading to groundwater could be attributed to renovation practices. The magnitude and isotopic composition of nitrate leaching were highly spatially and temporally (seasonally and inter-annually) variable. Characterizing this variation is key to targeting and assessing improved management practices for mitigating groundwater nitrate-N. Improved irrigation and alley management, reducing manure applications, and increasing the time between renovations can potentially decrease groundwater nitrate-N concentrations over the long-term.
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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) | 0.000 | 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 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".