ECONOMIC EVALUATION OF MANURE MANAGEMENT AND FARM GATE APPLICATIONS: A LITERATURE REVIEW OF ENVIRONMENTAL AND ECONOMIC ASPECTS OF MANURE MANAGEMENT IN ALBERTA'S LIVESTOCK SECTORS
Bibliographic record
Abstract
Livestock operations in Alberta have a significant impact on the economy. Manure is a by-product of livestock production. The review of the science on manure examined the environmental impacts of manure. These impacts include water pollution, air pollution, climatic change, and soil degradation. There are several technologies that may be used to manage manure on-farm and off-farm. These include nutrient recycling through soil application and composting. Composting reduces the volume of manure, but increases the nitrogen losses from the manure This review, using a very simplistic approach, estimated that more than 6.3 million tonnes of manure were generated in Alberta in 1996. Other studies have estimated significantly higher annual manure production. On a province-wide basis, there is adequate cropland area to make use of all the nutrients available in the manure produced. However, manure production tends to be concentrated on smaller land areas. Benefits of manure are constrained by both hauling costs and the costs of managing the manure itself. The on-farm economic costs or benefits are not well documented. Four general approaches have been used to analyze the on-farm economics of manure management. - Opportunity Cost: Value the nutrient content of manure using commercial fertilizer values and consider the manure or manure product as a commercial fertilizer substitute or supplement. - Crop Benefit: Value the direct crop benefit through a comparison of production in soil with manure applied versus a control with no manure applied. - Cost of Business: View the manure exclusively as a by-product of livestock production and evaluate methods for minimizing the cost of disposal. - Business Enterprise: View manure production as a value-added business and evaluate as a separate business enterprise using an appropriate approach. Any detailed economic analysis should incorporate the dynamic nature of manure production, and the management of manure through recycling through soil. Only one study was identified that was based on Alberta conditions and utilized a systems approach. At best, only one of the published studies explicitly incorporated the dynamic interactions of the livestock operation with a cropping enterprise, to analyze the on-farm economics of manure. This may be, in part, related to the complexities of modeling the key components in the system, while including the dynamic time-related interactions between soil, manure, and the environment. Those studies that attempted a systems approach or, at the very least, a more complete investment analysis, generally showed manure to be a net cost to the farm business. Little farm gate economic research applicable to Alberta on cost and benefits of manure systems for commercial farms for feedlots, dairy, pork or poultry was found. Future research could focus on a) economic case studies of selected farms to value manure management systems and b) working towards a systems analysis of manure management for Alberta livestock farms.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".