Colonization during early succession of restored freshwater marshes
Bibliographic record
Abstract
Little is known about the importance of initial colonization in the successional development of restored wetlands. We compared plant communities of two lightly planted restorations (water levels restored + planted and seeded), three hydrologic restorations (water levels restored), and two undrained sites. Measurements typically used in monitoring (richness, diversity, aboveground biomass) indicated that 23 years after restoration, restored wetlands showed only small differences from the plant community structure of undrained wetlands in the saturated zone. In contrast, analysis of vegetation based on species composition indicated differences in vegetation communities among all wetland types. Plant communities of planted restorations and reference sites were dominated by emergent species, while hydrologic restorations had a more variable plant community. These results indicate a small effect of initial planting and seeding at low densities and show that colonization is rapid during early succession of restored marshes. It was not clear whether either restoration method would eventually result in vegetation communities similar to reference sites. These results indicate that current monitoring periods of 35 years are insufficient to allow time for an accurate assessment of the successional development in each wetland.Key words: dispersal, germination, monitoring, plant biomass, plant community, wetland.
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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".