Edge of Field Vegetated Buffers as a Potential Source of Dissolved Phosphorus over the Non-Growing Season in Cold Climates
Bibliographic record
Abstract
Phosphorus (P) rich runoff from agricultural landscapes are a major contributor to freshwater eutrophication issues. To intercept this runoff before it reaches waterways, vegetated buffer strips (VBS) are often employed at field edges. Over time, sediment and nutrients accumulate at these unmanaged field edges and can become legacy sources of P, representing a source of dissolved P to waterways. In addition, typical non-growing season (NGS) conditions experienced in cold climates favour the release of P from vegetation within VBS, further adding to the potential for these features to contribute to P loads of waterways. Although these sites represent potential sources of P to waterways, it is unclear if the risk of release differs across different regions, or with riparian zone shape/topography or vegetation type. Thus, the aim of this thesis is to measure the variability of P concentrations in VBS soil and vegetation samples across several sites to determine the effects that topography, freezing temperatures, period of inundation, and soil P level have on mechanisms of P retention, mobilization, and transport over the NGS in typical Canadian VBS. \nSoil and vegetation samples were collected at various topographic locations (up, mid, low slope) from 4 Ontario (moderate winter) and 4 Manitoba (severe winter) VBS sites at the beginning and end of the NGS (Fall of 2020 and Spring of 2021) to measure their water extractable P and plant-available P contents. This analysis was supplemented with in-field hydrologic and temperature data at most sites. Results demonstrate that topography can drive soil P levels but has no effect on vegetation P or on the change of soil or vegetation P concentrations over the NGS due to greater periods of inundation. While the severity of freezing impacted the extractability of vegetation P, it was found that the temperatures applied in the lab were more severe than those experienced in the field due to the presence of snow cover accumulating in ditches. Further analysis on the effects of vegetation management were conducted on frozen soil/vegetation columns extracted from one Ontario site. Those results indicate the efficacy of vegetation harvesting as a means of reducing P losses from runoff through VBS, with the potential to reduce SRP loads by 3 and 10 kg/ha (for lower and upper zones, respectively). To investigate the relationship between vegetation and soil P concentrations more thoroughly and determine if vegetation growing in P-rich soils exhibits greater risk for winter P loss, samples were collected from 2 additional sites with highly elevated soil P due to bunker silo runoff, as part of a pilot study. Results indicate that vegetation P concentrations are independent of soil P concentrations and do not exhibit evidence of luxury P uptake and storage, though further investigation is recommended. \nThis thesis provides an initial investigation into the importance of VBS vegetation to NGS P losses. Future work should design experiments based on the recommendations and lessons learned to further enhance the understanding of vegetation management as a potential VBS best practice for P loss reduction, and to better understand the complex biogeochemical relationships in these systems.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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 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".