Mowing management favors primary productivity and carbon sequestration without changing species diversity in a temperate hayfield in Central Interior British Columbia, Canada
Bibliographic record
Abstract
We examined the effects of different mowing heights on the plant and soil characteristics of an irrigated and fertilized perennial cropping system in the central interior of British Columbia, Canada primarily composed of Medicago sativa, Phleum pratense, and Trifolium pratense. Mowing treatments included cutting heights of 0 cm, 5 cm, 10 cm, 15 cm, 20 cm, 25 cm, 30 cm, and an unmowed control treatment. Mowing treatments were applied three times throughout the study duration, followed by a final harvest. Data were collected on aboveground plant productivity, plant community diversity, and levels of soil carbon, nitrogen, and organic matter. Results showed plant productivity to be greatest at lower cutting heights, decreasing as cutting height increased. M0, M5, and M10 treatments produced over 300% more cumulative biomass than the control treatment. There were no differences across mowing treatments for measures of species diversity. The ten-centimetre treatment produced highest values of soil carbon, nitrogen, and organic matter than many other mowing treatments after three treatment applications (p < 0.05). Results indicate that lower cutting heights produced higher levels of aboveground biomass, did not alter crop species composition throughout the course of the study, and have potential to contribute towards the carbon pool. These results provide insight on the use of mowing within perennial cropping systems, and the effects on aboveground productivity and levels of soil carbon. The implications of this study allow agricultural producers to make informed decisions on how to manage their land for optimum productivity and environmental sustainability.
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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 | 0.001 | 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".