Long-term recovery of ecosystem services following forest harvest in coastal temperate rainforests of Vancouver Island, British Columbia, Canada
Notice bibliographique
Résumé
All ecosystems, and the ecosystem services (ES) they provide, are susceptible to potentially lasting impacts of resource extraction. For example, in forests, timber harvesting provides near-term services (such as wood products), but can be responsible for declines in other services such as carbon storage or wild edible foods, which may take decades or even centuries to recover. Some ES may recover quickly with forest regrowth, while others recover either slowly or not at all. However, the long-term recovery of multiple forest ES has rarely been quantified. My fundamental goal in this thesis is to build an improved understanding of how multiple ES recover following forest harvest, using the heavily harvested coastal temperate forests of western Vancouver Island, British Columbia, Canada, as my study system. First, I used a forest chronosequence to estimate the recovery trajectories for eight ES over a 212-year period. I used changes in key forest structures to estimate the provision of the following services: wood volume, carbon storage, potential nesting platforms used by an emblematic old-growth associate bird species the marbled murrelet (Brachyramphus marmoratus), habitat services provided by coarse woody debris, habitat services provided by dead trees, large heritage trees, wild edible berries, and large redcedar (Thuja plicata) used in traditional First Nations carving. ES recovered along varying non-linear trajectories and within markedly different timeframes. Wood volume stocks, dead tree biomass, and carbon storage recovered the fastest, reaching their maximum rates of recovery at around 65 years. In contrast, recovery of wild edible berries, heritage large trees, and habitat for marbled murrelet did not even commence until 70-100 years. Large heritage trees and large redcedar did not recover to old-growth baseline (forests >250 years old) during the 212-year period of my chronosequence. Second, I examined how ES recovery differed in two forest types: riparian and upland forests. With field assistance from a local First Nations crew, I estimated ten ES in old-growth (late seral stands >250 years in age) and second-growth stands (~35 years age) within each forest type. In addition to those services sampled in Chapter 1, I also estimated cedar bark for use in traditional First Nations weaving, salal (Gualtheria shallon) merchantable greenery, and fish habitat provided by instream woody debris. The abundance of ES differed significantly by forest type and forest age. For example, large cedar and potential nesting platforms for marbled murrelets were absent in second-growth stands, and significantly higher in riparian sites relative to their presence in upland forests. Old-growth riparian forests were hotspots of many ES, providing the highest levels of all services except salal merchantable greenery. The long timeframes and varying trajectories of recovery highlight the need to avoid ES declines proactively, for example by preserving sites with high levels of ES or working with First Nations to identify key areas with high levels of desired ES. Forest age and forest type have significant and major effects on multiple ES, and are thus two key variables for managing multiple ES in forested landscapes. Overall, this thesis provides insights into the effects of forest harvesting on multiple ES of ecological, cultural and economic importance. By applying forest ecological understanding to track changes in a bundle of ES, I identify influences of site conditions, long timeframes of successional recovery, and impacts from management to gain a broader understanding of the factors shaping forest ES. By building an improved empirical and conceptual understanding of multiple ES and their change through time, I have provided novel insights as well as practical solutions towards the challenge of long-term forest planning to sustain multiple ES.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».