A meta-analysis of the sources of variation in the environmental impacts of different broiler production systems
Bibliographic record
Abstract
1. Shifting to higher welfare systems is expected to increase their environmental impact and mitigation strategies need to be identified. The environmental impacts associated with various broiler production systems (BPS: conventional, higher welfare indoors, free-range or organic) and the characteristics of BPS which contribute to these impacts were investigated via a literature review and meta-analysis.2. The impact metrics considered were global warming (GWP), acidification and eutrophication potentials, NH3 emissions, land use, water use, energy use (EU) and biodiversity. Due to the paucity of data, analysis was limited to the impacts of the characteristics of the BPS: stocking density (STD), slaughter weight (SW), feed conversion ratio (FCR), on GWP, NH3 emissions and EU.3. After correction for system boundaries and functional units, no statistical effects of BPS on GWP were found, while higher welfare systems were associated with higher EU. Reduced STD was associated with reductions in GWP and EU. The SW was positively associated with GWP and NH3 emissions, while higher FCR was associated with increased NH3 emissions and EU.4. Environmental impacts arose from feed-associated activities (>75%). Most of the GWP impacts were associated with land use change (LUC), especially when associated with ‘unsustainable’ soya. High variation in values for different environmental metrics within BPS indicated a lack of standardisation in the assessment of environmental impact across the industry.5. The results suggested that practices within a system contributed greatly to the environmental impact of the system. Rather than comparing systems, it may be more productive to focus on improving practices that have the potential to reduce environmental impacts within a system, without compromising animal welfare.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.022 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.046 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".