EVALUATION OF THE EFFECTS OF CLIMATE CHANGE ON FORAGE AND LIVESTOCK PRODUCTION AND ASSESSMENT OF ADAPTATION STRATEGIES ON THE CANADIAN PRAIRIES A report to the Prairie Adaptation Research Collaborative Canadian Climate Change Action Fund
Bibliographic record
Abstract
An understanding of adaptation of plant and animal systems in response to changes in climate will help to reduce the risk involved in livestock production. Climate change will affect a large array of systems. Forage and livestock production will not be excluded from the impact of climate change. The purpose of this study was to understand the concept of adaptation and to integrate adaptive management strategies within the beef industry. A case study was undertaken at three locations to determine the impact of climate change as predicted by the CGCM1 model on livestock production. Three adaptation strategies were devised namely an early turnout date, intensive early season grazing and an extended grazing season. These were applied to simulation for the years 2051-2090. The results should only be considered as only an example of the possible responses to climate change. A climate change scenario was created using the Canadian Climate Change model (GCM1) and integrated into the GrassGro Decision Support System (DSS). Three adaptation strategies were tested in comparison to a baseline simulation (1961-1990) for 2 pasture associations, Russian wildrye/alfalfa (RWR/ALF) and Crested Wheatgrass (CWG) at three locations Melfort, Saskatoon, Swift Current, Saskatchewan. Climate change predictions were simulated for the years 2051-2080. The effects of climate change on livestock production were complex and results were variable for each site. The effects were more prominent at Saskatoon than Melfort and Swift Current, reflecting strong regional specificity and variability. The adaptation strategies were more successful for RWR/ALF than for CWG pasture at Melfort and Swift Current while CWG appeared to be more successful at Saskatoon. Indeed, the results suggest that productivity of beef cattle grazing RWR/ALF pastures at Melfort and Swift Current could be enhanced with climate change. However, Russian wild ryegrass is slow and difficult to establish. Therefore one of the recommendations from this report calls for a greater research effort into the establishment problems of this grass.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".