Eelgrass (Zostera marina) ecosystems in eastern Canada and their importance to migratory waterfowl
Notice bibliographique
Résumé
Seagrasses are marine flowering plants that create some of the most productive coastal habitats globally and play a key role in the functioning of nearshore ecosystems. The most common seagrass genus in Canada is Zostera and the species Zostera marina (eelgrass) is the predominant seagrass in intertidal and subtidal shoreline zones along the Atlantic, Pacific, and eastern James Bay coasts. Eelgrass has specific habitat requirements, with growth and productivity optimized within particular ranges of salinity, temperature, light availability, and nutrient concentrations. Large eelgrass meadows can impact nearshore environments by filtering the water column, stabilizing sediment, buffering shorelines, and providing habitat for various marine and coastal species, including commercially important species like Atlantic cod (Gadus morhua) and lobster (Homarus americanus). Eelgrass is also a vital food resource for migratory waterfowl, notably Canada Geese (Branta canadensis), Pacific Black Brant (Branta bernicla nigricans), and Atlantic Brant (Branta bernicla hrota). Despite their ecological importance, seagrasses are among the most vulnerable coastal ecosystems on the planet. The global loss of seagrass has been linked to a variety of human activities, including pollution, invasive species, and catchment modifications. There is an urgent need to improve monitoring of seagrass responses to environmental change, better document the importance of seagrass meadows to species reliant on them for food and habitat, and advance effective management and conservation of seagrass ecosystems. In this thesis, I investigated the spatiotemporal dynamics of eelgrass meadows in eastern Canada and the importance of eelgrass as a food source for migratory waterfowl, using remote sensing data, long-term monitoring data (biomass, density, and cover), and field observations. In Chapter 3, I used a novel cost-efficient approach for satellite imaging time-series to examine changes in eelgrass distribution and abundance from 1984 to 2017 in a wetland of international importance in northeastern New Brunswick. With minimal ground truth data, the novel time-series approach revealed a slow and steady decline in eelgrass abundance in some areas of the estuary. In contrast, other areas were characterized by highly dynamic shifts in eelgrass cover over time. I demonstrated how time-series analysis can be used to identify potential drivers of seagrass change and the benefits of including time-series analysis in seagrass monitoring programs. In Chapter 4, I contributed to advancing knowledge of migratory waterfowl stopover behaviour by examining the influence of eelgrass and human activities on Canada Geese habitat selection. Combining field observations of Canada Geese and the eelgrass distribution maps produced in Chapter 3, I found that Canada Geese selected areas with high eelgrass availability during periods of low human disturbance, which emphasized the importance of eelgrass as a food source during the fall migration. However, higher levels of human disturbance led to a redistribution of geese away from dense eelgrass meadows. In Chapter 5, I presented new insights into the recent and current state of eelgrass along the eastern coast of James Bay after a drastic and large-scale decline in the late 1990s. By aggregating, synthesizing, and analyzing long-term monitoring data and current surveys, spanning 1982 – 2020, I provided the first quantitative evidence that changes in eelgrass biomass in northeastern James Bay may reflect synergistic impacts of climate change and altered freshwater discharge regimes. Overall, this thesis advances understanding of how temperate and subarctic Zostera marina ecosystems and associated fauna respond to coastal development and climate change
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 | 0,000 |
| 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 | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».