Multivariate analysis of economic performance and environmental impacts of multispecies pastured livestock farms using direct marketing
Bibliographic record
Abstract
CONTEXT Worldwide, the livestock sector was found to be an important contributor to climate change , resource use, health, and pollution issues. In the Global North, the growing interest in alternative food networks and short supply chains has reached the livestock sector, within which we find an increasing number of farms raising multi-species herds on pasture and marketing their products directly to the end consumer. OBJECTIVE The objective of this study was to assess the economic performance and environmental impacts of multispecies pastured livestock farms using direct marketing, a farm model that can be considered novel and alternative when compared to large-scale specialized livestock operations. METHOD From a sample of 15 multispecies pastured livestock farms using direct marketing in Québec, we conducted a principal component analysis according to farm structure, economic and environmental indicators. We subsequently divided the farms in three groups using hierarchical clustering and compared them through an analysis of variance. RESULTS AND CONCLUSIONS Farms grouped in the Intensive cluster had a high animal load and high proportion of monogastric animals to which they fed purchased grain feed . This reliance on imported feed had negative economic and environmental impacts. Farms in the Extensive cluster supplemented a traditional cow-calf farming model with purchased weaners for seasonal finishing, thus presenting low animal densities and low environmental impacts. Other animal species were added to the herd to serve their direct-marketing clients, making for overall strong economic performances. Some farms in the Thrifty cluster produced crops, which helped lower their environmental impacts through manure cycling and economically diversify their activities. These farms had better resource optimization strategies and added value to their products though some level of processing on the farm. SIGNIFICANCE While all farms dedicated a certain amount of land to pasture or forage production , multispecies pastured livestock systems using direct marketing in Québec are not fully integrated crop-livestock systems. Farms with crop production activities, even when unrelated to their livestock operation, appeared to benefit from some level of integration between their crop and livestock productions in the form of a reduction of their environmental impacts through nutrient cycling by manure disposal on pasture. Farms with a higher animal density and higher proportion of monogastric animals fed purchased grain feed ran the risk of both causing negative environmental impacts and reducing their economic performances.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".