Atmospheric Composition under Impermeable Winter Golf Green Protections
Bibliographic record
Abstract
The utilization of impermeable winter covers on annual bluegrass [Poa annua var. reptans (Hauskn.) Timm.] golf greens as a protection against excess water and ice is increasing rapidly in Canada and elsewhere in northern climates. A study was conducted to examine the impact of these covers on the atmospheric composition over golf green turfgrass during the 1997–1998 and 1998–1999 winters in Québec City and in Montréal, Canada. Winter protective covers tested included a commercial impermeable cover on top of either curled wood shavings mat (CW‐CC), 15 cm of straw mulch (SM‐CC) or a felt material (FM‐CC), a clear polyethylene cover on top of a curled wood shavings mat (CW‐PC), and an unprotected control. Oxygen was consumed at variable rates under impermeable winter protective covers. As a result, anoxic conditions were not reached during winter at the Québec City site but high respiration rates at the Montréal site resulted in anoxic conditions that lasted for periods as long as 50 d, without apparent damage to the annual bluegrass plants. Further tests were conducted on greens experiencing recurrent damages that could not be explained by freezing temperatures, snow mold pathogens, excess water, or ice. We showed that these problem greens had higher soil respiration rates than nonproblem greens indicating that the differences in O2 consumption amongst golf greens are likely due to differences in soil biological activity rather than in plant respiration. We also established that the higher activity in soils of recurrently damaged greens was related to higher levels of soil organic C. Accordingly, sand‐based golf greens built according to the USGA specifications had lower soil organic matter and lower respiration rates than greens built on native soils. We conclude that high rates of O2 consumption by golf greens with high soil organic matter content results in potentially harmful anoxic conditions under impermeable covers during winter.
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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 | 0.001 | 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) | 0.001 | 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".