Planting techniques and abiotic variation at two salt marsh restoration sites in the Bay of Fundy
Bibliographic record
Abstract
Salt marshes provide many important ecosystem services, and interest in their restoration is growing in response to climate change. In Maritime Canada, salt marsh restoration projects have focused on restoring tidal flow without planting. Over time, these sites can show persistent deficits in vegetation diversity. We evaluated six techniques for encouraging revegetation (plugs, field transplants, seed, wrack, tilling, and no planting) with eight native species (Carex paleacea, Juncus gerardii, Limonium carolinianum, Plantago maritima, Poa palustris, Solidago sempervirens, Sporobolus alterniflorus, and Sporobolus michauxianus) at two Bay of Fundy salt marsh restoration sites. Community recovery and plant performance (growth rate, summer and winter survival, and health) were monitored over 2 years. Planting plugs produced the highest abundance of perennial halophytes over both years with high survival rates (76.4% ± 0.02 SE), whereas plants transplanted from adjacent sites had higher mortality and slightly lower cover. All planted species survived and grew. Growth rate, health, and winter survival were all more strongly related to site than planting technique, indicating that location was more important to success than technique. We found evidence that differences in elevation, inundation, soil salinity, and soil nutrients at each site may explain these differences in performance. Plugs and field transplants may both be useful for restoration in the future and mixing methods to capitalize on respective strengths may produce best results when planting. Our results also highlight the need to tailor planting plans to individual sites as plants may respond uniquely in different situations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".