Understanding the effects of forest management on streams and rivers: A synthesis of research conducted in New Brunswick (Canada) 2014–2018
Notice bibliographique
Résumé
Forests play a major role in maintaining healthy streams and in providing ecosystem services such as clean drinking water, flood/drought protection and biodiversity, but studies have shown that some forestry operations can compromise these benefits. To assess whether current forest management practices impact stream ecosystems, a five-year study was conducted in J.D. Irving, Limited’s Black Brook Forestry District (New Brunswick, Canada) and in other watersheds with varying forest management intensity. This study was divided into two phases, with each addressing one main research question: 1) how different intensities of forest management affect the ecological health of headwater streams and, 2) whether the changes observed in headwater streams accumulate or dissipate in larger downstream rivers. A comprehensive approach to examining these research questions was taken by measuring multiple abiotic and biotic indicators to assess the integrity of stream ecosystems (sediments, water chemistry, insect communities, leaf decomposition, fish condition, mercury concentrations). The purpose of this paper is: 1) to synthesize the results of numerous scientific articles, and 2) to present the science and management implications in terms that regulatory and industrial forest managers can use to incorporate the lessons learned into their decision making. Results in Phase I show that streams in the most intensively managed catchments had greater inputs of terrestrial materials such as sediments, and these were incorporated into food webs, resulting in more terrestrial diets of aquatic consumers. The important stream function of leaf litter breakdown was negatively influenced by increased management intensity. Management practices related to roads warrant special attention, as roads tended to be more related to changes in stream indicators than tree removal. Additionally, results suggest that wet riparian areas were more sensitive to disturbance than drier riparian areas, which has implications for riparian buffer zone configurations. Regarding Phase II, some of the effects of forest management on small streams accumulated in larger downstream rivers (e.g., sediments, use of terrestrial resources by aquatic organisms), while others dissipated (e.g., water temperature, mercury contents). Interestingly, the impacts of forest management on streams were greater in the basin with tree removal but less silviculture than in the basin with more of both, suggesting that greater overall intensity of forest practices does not necessarily translate into greater environmental impacts, for example when considering partial versus clearcut harvesting. Overall, the study suggests that while current best management practices do not eliminate all effects, they do still offer good protection of biological integrity downstream.
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 | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,020 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,004 | 0,001 |
| 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 ».