Economic analysis of mechanically disturbing rangeland to reduce clubmoss in Saskatchewan
Bibliographic record
Abstract
The objective of this study was to conduct an economic analysis of pitting or chisel plowing to reduce clubmoss (Selaginella densa Rydb.) on rangelands in Saskatchewan using secondary data. This analysis was undertaken for sandy and loamy range sites in the Dry and Moist Brown soil zones, and the Dark Brown soil zone of the province. The approach used involved valuation of post-treatment forage response in terms of increased livestock production. Under the best case scenarios, pitting and chisel plowing increase forage yields and stocking rates on fair condition rangeland to levels similar to those in excellent condition. However, economic efficiency of treatment varies and many factors affect the final results. This study shows that regardless of discount rate used, net present value of returns for chisel plowing were negative, indicating this treatment is not economic on any of the range sites. Results show that pitting was economically more efficient if the treatment benefits last 10 yr and the discount rate does not exceed 5%. Recovery of total costs of pitting on a loamy range site occurred in 9 yr after treatment in the Dark Brown soil zone, 9 and 10 yr in the Moist Brown soil zone, and 11 and 12 yr in the Dry Brown soil zone at discount rates of 3 and 5%, respectively. However, it is questionable whether beneficial effects of pitting or chisel plowing on herbage production exceed 10 yr. Range managers considering pitting or chisel plowing to reduce clubmoss on rangeland and improve forage productivity will find the net present value, and the predicted number of years to break even useful in making economically prudent decisions. Key words: Cultivation, mechanical treatments, Northern Mixed Prairie, range improvements, range management, Selaginella densa Rydb.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".