Estimation of enteric methane emissions trends (1990-2008) from Manitoba beef cattle using empirical and mechanistic models
Bibliographic record
Abstract
Alemu, A. W., Ominski, K. H. and Kebreab, E. 2011. Estimation of enteric methane emissions trends (1990-2008) from Manitoba beef cattle using empirical and mechanistic models. Can. J. Anim. Sci. 91: 305-321. The objective of this study was to estimate and assess trends in enteric methane (CH4) emissions from the Manitoba beef cattle population from the base year of 1990 to 2008 using mathematical models. Two empirical (statistical) models: Intergovernmental Panel on Climate Change (IPCC) Tier 2 and a nonlinear equation (Ellis), and two dynamic mechanistic models: MOLLY (v3) and COWPOLL were used. Beef cattle in Manitoba were categorized in to 29 distinct subcategories based on management practice, physiological status, gender, age and production environment. Data on animal performance, feeding and management practices and feed composition were collected from the literature as well as from provincial and national sources. Estimates of total enteric CH4 production from the Manitoba beef cattle population varied between 0.9 and 2.4 Mt CO2 eq. from 1990 to 2008. Regardless of the type of models used, average CH4 emissions for 2008 were estimated to be 45.2% higher than 1990 levels. More specifically, CH4 emissions tended to increase between 1990 and 1996. Emissions were relatively stable between 1996 and 2002, increased between 2003 and 2005, but declined by 13.2% between 2005 and 2008, following the same trend as that observed in the beef cattle population. Models varied in their estimates of CH4 conversion rate (Ym, percent gross energy intake), emission factor (kg CH4 head-1 yr-1) and CH4 production. Total CH4 production estimates ranged from 1.2 to 2.0 Mt CO2 eq. for IPCC Tier 2, from 0.9 to 1.5 Mt CO2 eq. for Ellis, from 1.3 to 2.1 Mt CO2 eq. for COWPOLL and from 1.5 to 2.4 Mt CO2 eq. for MOLLY. The results indicate that enteric CH4 estimates and emission trends in Manitoba were influenced by the type of model and beef cattle population. As such, it is necessary to use appropriate models for reliable estimates for enteric CH4 inventory. A more robust approach may be to integrate different models by using mechanistic models to estimate regional Ym values, which may then be used as input for the IPCC Tier 2 model.
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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 | 0.000 | 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) | 0.002 | 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 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".