Fen restoration: defining a reference ecosystem using paleoecological stratigraphy and present-day inventories
Bibliographic record
Abstract
Choosing past and present-day indicators could strengthen the reference ecosystem used for ecological restoration projects. Based on the paleoecological analysis of four peat cores and the characterization of 13 contemporary natural sites, the reference ecosystem for minerotrophic peatlands in southeastern Canada is composed of two broad categories of plant assemblages described as tall-sedge and Sphagnum–Thuja/brown moss. In paleoecological peat profiles, tall-sedge communities were found at the transition between aquatic and terrestrial, and were associated with high graminoid production, riverine peatlands, and elevated water table in the present-day analyses. Sphagnum–Thuja communities resemble the present-day vegetation found in natural basin type peatlands. Except for Sphagnum warnstorfii Russ., these communities, with high taxonomical diversity, contain more generalist species from boreal peatland vegetation, such as Rhododendron groenlandicum (Oeder) Kron & Judd, Thuja occidentalis L., Linnaea borealis L., and Maianthemum trifolium L. They grow in dryer or shady habitats such as hummocks or forest understory. The importance of brown mosses was revealed by paleoecological analysis. Overall, findings from both approaches are complementary: paleoecological stratigraphy informs us about past ecosystem dynamics, while present-day inventories allow us to define current plant communities and their major environmental characteristics. The range of variability of vegetation and environmental variables found in these studies are essential tools for fen restoration projects.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".