Long-term vegetation dynamics following water level stabilization in a prairie marsh
Bibliographic record
Abstract
The objective of this study is to examine the long-term vegetation dynamics of a prairie marsh following water level stabilization. We hypothesize that disruption of the natural disturbance regime (flood-drought cycles) in prairie marshes increases the influence of competition among macrophyte species. An increase in competitive interactions results in elimination of subordinate species, while consolidating the abundance of competitive dominants. We used colour infrared aerial photography, GPS and GIS, microtopographic maps, and ground-truthing surveys to examine the role of interspecific competition in structuring wetland communities in the Marsh Ecology Research Program (MERP) experimental marshes at Delta Marsh, Manitoba, Canada. The MERP complex consists of ten sand-diked and two "control" marshes, each between ca. 5-7 ha in area. Water level fluctuations in Delta Marsh were artificially stabilized in 1961, disrupting the natural flood-drought cycle. Since 1989, water levels in the twelve marshes have been left to equilibrate with the surrounding marsh. At present, six emergent plant zones characterize the twelve marshes: salt-tolerant species, annuals, reed grass, whitetop, cattail and bulrush. (Abstract shortened by UMI.)
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".