An Economic Evaluation of Shelterbelts on Saskatchewan Grain and Mixed Farms
Bibliographic record
Abstract
Shelterbelts have a long history in the Canadian Prairies. They were used for protecting crops, livestock, and buildings from extreme wind. However, removing shelterbelts in Saskatchewan has been observed in recent periods. Changes in farming technology (adoption of no-till method, reduction in summer-fallow area), inconvenience of large machinery movement, loss of land, and short-run economic goals of producers may contribute to this removal. Shelterbelts provide benefits to producers and offer several goods and services to society. The carbon sequestration ability of shelterbelts can play an essential role in achieving Canada's greenhouse gas (GHG) emission reduction target. Further removal of shelterbelts can create more challenges to achieving this target. Producers make decisions about maintaining or removal of shelterbelts. How such decisions are made is not clearly understood. Are such choices supported on economic grounds? Existing studies have supported the economic goals of the producers to be an essential factor in adopting new technology. Whether producers are better off with shelterbelts is unknown for Saskatchewan. From the producers' perspective, an economic evaluation of a farm with shelterbelts is needed. Moreover, one may hypothesize regional differences in shelterbelt's impact on farm returns. Therefore, this study aims to evaluate the economics of a farm with shelterbelts in Saskatchewan's Black, Brown, and Dark Brown soil zone. It considered field shelterbelts for a grain farm and a combination of field and livestock shelterbelts for a crop-beef mixed farm. Three scenarios were selected for the grain farm (Baseline Scenario – farm without shelterbelts, Scenario One – farm-maintained shelterbelts, and Scenario Two – farm removed shelterbelts). Two scenarios were selected for the crop-beef mixed farm (Baseline Scenario - farm without shelterbelts, Scenario One - farm maintained shelterbelts). Both farms were subjected to economic evaluation using financial analysis, which was incorporated in the form of a simulation model. This model resulted in estimates of the net present value (NPV) of farm returns from shelterbelts over 60 years. Results suggest that the economics of farms with shelterbelts differed across soil zones. For grain producers, neither field shelterbelts nor removing shelterbelts once planted was an economically preferred option in all three soil zones. On the other hand, shelterbelts were economically preferred for all mixed farm producers, particularly in the Black soil zone. Since previous studies have shown shelterbelts benefit society, a case could be made for government intervention. However, policies that would entice maintaining or not removing field shelterbelts need further investigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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 teacher head, 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".