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Record W2470903542 · doi:10.2527/jas.2015-0141

Forage use to improve environmental sustainability of ruminant production12

2016· review· en· W2470903542 on OpenAlexaff
Jessie Guyader, H. H. Janzen, R. Kroebel, K. A. Beauchemin

Bibliographic record

VenueJournal of Animal Science · 2016
Typereview
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsGreenhouse gasEnvironmental scienceForageSustainabilityLivestockManureArable landPopulationAgronomyAgroforestryBiologyAgricultureEcology

Abstract

fetched live from OpenAlex

Ruminants raised for meat and milk are important sources of protein in human diets worldwide. Their unique digestive system allows them to derive energy and nourishment from forages, making use of vast areas of grazing lands not suitable for arable cropping or biofuel production and avoiding direct competition for grain that can be used as human food. However, sustaining an ever-growing population of ruminants consuming forages poses a dilemma: while exploiting their ecological niche, forage-fed ruminants produce large amount of enteric methane, a potent greenhouse gas. Resolving this quandary would allow ruminants an expanded role in meeting growing global demands for livestock products. One way around the dilemma is to devise forage-based diets and feeding systems that reduce methane emissions per unit of milk or meat produced. Ongoing research has made significant strides toward this objective. A wider opportunity is to look beyond methane emissions alone and consider all greenhouse gas emissions from the entire livestock-producing system. For example, by raising ruminants in systems using forages, some of the methane emissions can be offset by preserving or enhancing soil carbon reserves, thereby withholding carbon dioxide from the air. Similarly, well-managed systems based on forages may reduce synthetic fertilizer use by more effective use of manure and nitrogen-fixing plants, thereby curtailing nitrous oxide emissions. The potential environmental benefits of forage-based systems may be expanded even further by considering their other ecological benefits, such as conserving biodiversity, improving soil health, enhancing water quality, and providing wildlife habitat. The quandary, then, can be alleviated by managing ruminants within a holistic land-livestock synchrony that considers not only methane emissions but also suppression of other greenhouse gases as well as other ecological benefits. Given the complexity of such systems, there likely are no singular "best-management" practices that can be recommended everywhere. Using systems-based approaches such as life cycle analysis, ruminant production can be tuned for local lands to achieve greatest net benefits overall. In many instances, such systems, based on forages, may maintain high output of milk and meat while also furnishing other ecosystem benefits, such as reduced overall greenhouse gas emissions.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.014
GPT teacher head0.288
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations73
Published2016
Admission routes1
Has abstractyes

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