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Record W7161957794 · doi:10.82308/40359

Eelgrass (Zostera marina) ecosystems in eastern Canada and their importance to migratory waterfowl

2022· dissertation· en· W7161957794 on OpenAlexaboutno aff
Mélanie‐Louise Leblanc

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
Fundersnot available
KeywordsSeagrassZostera marinaHabitatZosteraWaterfowlEcosystemBayProductivity

Abstract

fetched live from OpenAlex

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

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.179
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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