Costs and benefits of shelterbelts: A review of producers' perception and min map analysis for Saskatchewan, Canada
Bibliographic record
Abstract
The role of shelterbelts within prairie agriculture is changing. In the past, shelterbelts have been promoted and adopted to reduce soil erosion and to protect farmsteads and livestock from harsh prairie climates. Production techniques used today have been changed from when shelterbelts were first introduced as a management practice to reduce erosion. Advances in production technology accompanied with increase in farm size and changes to policy have all contributed to a shift in how shelterbelts are considered within management plans. The objective of this research is to identify the private costs and benefits from adoption and retention of shelterbelts. In the summer of 2013, a survey was conducted of producers and land owners chiefly from Saskatchewan, Canada. It was found that many of the benefits of shelterbelts can be classified as noneconomic and, therefore, are more difficult for producers and land owners to recognize or include within their operations management decisions. Conversely, the costs to producers were easily identified and heavily influenced management decisions. As greenhouse gas management and policy become more of a focus, shelterbelts have the potential to play a major role in climate change mitigation by sequestering significant amounts of atmospheric carbon dioxide (CO2) into the soil and as biomass carbon in above- and belowground parts of planted shelterbelt trees or shrubs. However, most producers do not recognize such benefits within their management decisions, as they are not currently compensated for the benefits that they provide to society.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.031 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".