Bibliographic record
Abstract
Abstract Role of Livestock in a Circular Bioeconomy T. A. McAllister1 Barbara Renate Amon2 and Philippe Becquet,3 1Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, Alberta, Canada T1J 4B1 2 Leibniz Institute for Agricultural Engineering and Bioeconomy, Max-Eyth-Allee 100, 14469 Potsdam, Germany 3 Regulatory Strategy Adviser, EI, 8, Place des Tonneliers, 68100 Mulhouse, France ABSTRACT Redesigning livestock systems that integrate circularity principles into livestock production is a critical step toward a more resilient and sustainable food system. The UN Food & Agriculture Organization’s Livestock Environmental Assessment & Performance (LEAP) Partnership have published a new guideline that provides insights into the measurements and products used to strengthen circularity within the livestock sector. It explores the synergies, trade-offs, and interactions of livestock within a circular bioeconomy framework. Livestock play a fundamental role within a circular bioeconomy by converting non-edible biomass, such as pastures and forages, agricultural residues, and food industry by-products into high-value animal-sourced foods (ASF), organic fertilizers, and renewable energy. By recycling nutrients and utilizing low-opportunity-cost biomass, livestock contribute to reducing food-feed competition, enhancing soil health, and closing nutrient cycles, improving the sustainability of agricultural systems and strengthening global food security. Beyond food production, livestock systems support bio-based industries by valorizing animal by-products (ABP) such as hides, bones, and fats into materials for pharmaceuticals, cosmetics, and bioenergy. Additionally, manure-based biogas production provides renewable energy while mitigating greenhouse gas emissions. The guideline presents an overview of widely used metrics and indicators for assessing the environmental impact of livestock production in a circular bioeconomy. The use of plant-based and animal-based by-products as feed, as well as the valorization of residuals such as manure within circular bioeconomy systems are outlined. Additionally, the document analyzes political and regulatory implications, discusses policies that promote the circular economy and bioeconomy, and outlines the strengths and challenges in supporting the use of by-products and residuals. The document is relevant to livestock producers, supply chain partners (e.g., feed producers), farming organizations, processors, and retailers seeking to enhance the environmental performance of livestock production systems. Non-livestock stakeholders can also benefit from insights into creating synergies within this sector through recycling and upcycling of residuals and waste. The guidelines will serve as a valuable tool for policymakers interested in fostering circular bioeconomy strategies for livestock supply chains.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
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".