Factors Influencing the Resilience of Created Tidal Marshes in the Fraser River Estuary, British Columbia
Bibliographic record
Abstract
Abstract More than 100 tidal marsh creation projects were constructed throughout the Fraser River Estuary, British Columbia, Canada from the 1980s to present. Past studies described and evaluated many of these projects and found varied success, but the underlying factors that determine project outcomes remain uncertain. Combining field sampling, spatial analysis, and statistical modeling of plant communities, we aim to address this knowledge gap by asking what factors influence the resilience of created marshes, as measured by (1) persistence of marsh vegetation, (2) native species dominance, and (3) species richness. We observed marsh recession in 40 of the 78 projects visited, representing 23,666 m2 (9.3%) of the 254,357 m2 of created marsh surveyed. Increases in mean site elevation had a negative effect on percent recessed area, while sites in the north branch of the river and sites further upriver were more prone to recession. From field observations and data interpretation we suggest that wake erosion and Canada Goose (Branta canadensis) herbivory may be drivers behind these losses and warrant further investigation. Dominance of native species declined with distance upriver, though invasive cattail (Typha angustifolia, T. × glauca) defied this trend, dominating outer estuary sites, particularly closed embayments, when present. Native and non-native richness shared similar patterns and were comparable between reference and created marshes, increasing on average with elevation and distance upriver. These findings offer insight into how site design and location influence the outcome of marsh creation projects, and the challenges presented by stressors and environmental change in estuaries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".