Effects of age and time of first calving on greenhouse gas emissions from simulated beef farms grazing four stockpiled forage treatments in late fall/early winter
Bibliographic record
Abstract
The impacts of age (2 vs 3 yrs), time (March vs June) of first calving and stockpiled forage quality (TDN) for late fall/early winter grazing on whole-system greenhouse gas (GHG) emissions and net revenues from cow-calf production systems were examined in this study. Farm simulations were conducted using the Holos model to estimate whole-farm GHG emissions from 16 systems in Brandon, Manitoba, Canada. Each simulation began with 118 newborn, female calves and ended upon weaning of their 6th calf with GHG emissions measured annually over 8-10 yrs. The steady-state herd consisted of 75 mature cows and 22 heifers, or 85 mature cows and 12 heifers, 4 bulls and their progeny. Four stockpiled forages/forage mixtures were evaluated: i) standing corn (COR), ii) tall fescue/meadow bromegrass (TFM); iii) orchard grass/alfalfa (OGA), and iv) tall fescue/alfalfa/cicer milkvetch (TAC). An economic analysis was conducted to estimate annual net revenues from the steady-state herd. Enteric methane (CH4) was the largest GHG emission source accounting for 57 to 65% of emissions across all systems. Cumulative GHG emissions (over the 8-10 yr period) were 5-14% lower with heifers calving at 2 vs 3 yrs of age, and 2-9% lower for March vs June calving within the 2-yr calving systems. Cumulative GHG emissions ranged from 4205-4765, 4329-4982, 4593-5460, and 4470-5029 Mg CO2e for systems grazing COR, TFM, OGA, and TAC, respectively. Emissions were highest from OGA, the lowest-TDN treatment, in all systems. Greenhouse gas intensity estimates ranged from 15.6 to 21.0 kg CO2e kg liveweight-1. Estimated net revenues were 5-7% higher with heifers calving at 2 vs 3 yrs of age and 9-14% higher for June- vs March-calving systems. Using 2021 market prices, net revenues averaged -$57,776, -$59,685, -$59,999, and -$70,179 yr-1, for OGA, TFM, TAC, and COR systems, respectively. This study suggests that (i) a reduction in the age at first calving (2 vs 3 yrs) should reduce GHG emissions and increase annual revenues; (ii) calving in March vs June should reduce GHG emissions but decrease annual revenues; and (iii) grazing stockpiled forages with higher TDN should reduce GHG emissions and annual revenues from cow-calf systems.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".