Are the factors recommended by UNEP-SETAC for evaluating biodiversity in LCA achieving their promises: a case study of corrugated boxes produced in the US
Notice bibliographique
Résumé
Abstract Purpose We tested the effectiveness of the global and ecoregion-based average characterization factors (CFs) for “Potential Species Loss” recommended by the UNEP-SETAC Life Cycle Initiative to identify hotspots and improvement opportunities compared to using a land competition indicator for a product for which the predominant life cycle use of land is forest management. Methods For a case study of average corrugated boxes produced in the US, system boundaries were defined to encompass all life cycle stages from forest management to disposal. Fiber procurement was regionalized to US ecoregions, and (Chaudhary et al. Environ Sci Technol 49:9987–9995, 2015) ecoregion-specific CFs were applied. US-average CFs were applied to other background processes. Hotspots were identified using contribution analyses, and improvement opportunities were evaluated using scenarios. We compared the results with those from applying a land competition indicator, often used as a proxy for biodiversity in LCA. Results and discussion Forest management was identified as the activity within the life cycle of corrugated boxes that uses the greatest amount of land, allowing the definition of two potential improvement opportunities: reducing fiber consumption and intensifying forest management. By applying the recommended CFs, fiber procurement was also identified as the main contributor to “Potential Species Loss.” The CFs also allowed to identify ecoregions in which species were potentially the most affected by forest management and related potential improvement opportunities. Tradeoffs between taxonomic groups were discussed. In some cases, the results contradicted those from applying a land competition indicator, and in many cases, we were unable to reconcile the results obtained with existing scientific knowledge on species diversity and forest management. Conclusions and recommendations The results obtained by applying the recommended CFs could not always be reconciled with existing scientific knowledge on the effect of forest management on species diversity, significantly impairing the usefulness of these factors for assessing improvement opportunities and increasing the risk of counterproductive decisions. The local effect on species of forest management is likely to be misrepresented by the average number of species in a given ecoregion. Successful consideration of biodiversity response in the context of forest management would require the integration of other approaches, such as site-specific studies. Potential improvements to the proposed method include further spatialization of the CFs, defining a range of forest management practices for which CFs would be defined, considering forest productivity, and defining CFs using a baseline that would encourage better practices even within a given existing management regime.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».