Restoration of a Lake <scp>Ontario‐connected</scp> fen through invasive <i>Typha</i> removal
Bibliographic record
Abstract
Lake‐level regulation that began in 1960 eliminated large fluctuations of Lake Ontario water levels, altering coastal wetland plant communities. More than a half century later, the altered hydroperiod supports dense, monotypic stands of invasive cattail (Typha angustifolia and Typha × glauca), which have diminished overall plant community diversity. As a result, Lake Ontario coastal wetlands are less capable of providing many of their traditional ecological functions. One such wetland is Buttonwood Fen, a floating, lake‐connected peatland on Lake Ontario's southern shore near Rochester, NY. We implemented cattail‐control measures from 2016 to 2018 with the goal of decreasing live and dead cattail biomass and increasing cover of native fen taxa. Site manipulation included removal of dead cattail biomass, cutting new cattail growth when rhizome carbohydrate reserves were at their lowest, and hand‐wicking regrowth with herbicide in early fall. Results showed a decrease in live cattail stem density and cover and dead biomass cover, as well as an increase in cover of fen taxa. Although not a replicated study, our results suggest that removing dead cattail biomass and targeted treatment of live cattail stems via cutting and hand‐wicking with glyphosate can reduce cattail and improve site quality.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".