Establishing the value of a salt marsh as a potential benchmark: vegetation surveys and paleoecological analyses as assessment tools
Bibliographic record
Abstract
Identifying tidal salt marshes as priority sites for conservation or restoration remains a challenge, as several sites are so severely degraded that allocating financial resources for their protection would be questionable. The decision-making process could nevertheless be facilitated by comparing species assemblages and the dynamics and (or) ecological functions of a site with an ecological benchmark, i.e., a tidal marsh that remains free from anthropogenic disturbances. We used plant surveys and plant macrofossil and pollen analyses for evaluating the benchmark potential of the Pointe-aux-Épinettes marsh, a protected salt marsh of the St. Lawrence River estuary (Canada) and one of the last salt marshes that could potentially be a benchmark along the estuary. Historical evidence indicated that the forests surrounding the marsh were converted into agricultural lands circa 1850. Nevertheless, this land-use change had little impact on the marsh. The long-term impacts of trampling and grazing by livestock on the vegetation were negligible. Macrofossil analyses indicated that the plant assemblages were dynamic, but past and current vegetation assemblages are representative of those characterizing an undisturbed salt marsh, with a very high proportion of native wetland species. In a context where truly undisturbed salt marshes are extremely rare ecosystems, our study indicates that the Pointe-aux-Épinettes plant assemblages could be used as benchmarks against which the condition of the vegetation of other salt marshes in northeastern North America could be evaluated.
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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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| 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".