Coordinating old-growth conservation across scales of space, time, and biodiversity: lessons from the US policy debate
Notice bibliographique
Résumé
Conservation of old-growth forests and their biodiversity and climate benefits requires coordinated actions across spatiotemporal scales, including restrictions on harvest of old and mature trees and longer-term landscape planning for old-growth recovery. In 2024, the US government drafted a National Old-Growth Amendment (NOGA) to enhance consideration of old growth in planning. The amendment was never finalized due to a change in administrations. However, the debate associated with the proposed NOGA remains relevant for several reasons. The key points of debate also underpin discussion regarding ongoing US regional policy initiatives such as amendments to the Northwest Forest Plan (NWFP). The NOGA policy debate illustrates questions that should inform US national old-growth initiatives under future administrations. Lastly, the debate highlights challenges common to such initiatives globally as nations implement the Kunming-Montreal Global Biodiversity Framework. Although the proposed NOGA provides a useful foundation for future initiatives, more attention must be paid to the policy implications of variation in the context in which old growth occurs across ecosystems. New initiatives must learn from regional efforts, including the NWFP’s insights that landscape design including reserves is essential for conservation of species, services, and processes associated with old-growth ecosystems. Reserves, conceived as places where extractive uses are restricted but beneficial human activities are supported, are compatible with strategies for ecosystem restoration and Indigenous-led conservation. An approach that builds on the NOGA’s adaptive strategies can form a foundation for long-term conservation of forest ecosystems by protecting climate refugia, addressing barriers to connectivity, and enhancing monitoring capacity. Ecosystem-based standards are needed to ensure protection of mature forest so recruitment into the old-growth stage shifts ecosystems towards historic proportions of old growth. In addition to clarifying goals regarding ecological integrity, comprehensive policy must incorporate goals for recovering at-risk species based on relationships across scales of biodiversity between forest habitat and species viability. Land management agencies need to articulate a long-term vision for recovery of depleted ecosystem elements (including both old growth and naturally disturbed younger stands) via designation of large areas anchored by remaining old-growth stands, surrounded by areas managed for recovery of ecological integrity, native biodiversity, and ecosystem services.
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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 | 0,000 | 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 | 0,000 | 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 ».