Influence of dam regulation on 55-year canopy shifts in riparian forests
Bibliographic record
Abstract
Floodplain and swamp forests are undergoing extensive changes due to altered flow regimes, invasive species, logging, and various land use changes. These changes often go unnoticed due to the absence of adequate baseline data and monitoring. Using a data set from 55 years ago, we resampled 50 lowland forest stands in southern Wisconsin to assess changes in forest overstory composition, structure, diversity, and dominant species abundances. We also applied univariate and multivariate analyses to determine whether these changes varied between dam-regulated and unregulated rivers, tree species with different flooding tolerances, the presence of logging, and variations in edaphic and hydrologic variables. Although these forests display various types of resilience, their forest canopies are substantially different from 55 years ago, reflecting shifts in hydrology and the impacts of disease. On average, these forests have retained the same local (alpha) diversity but have converged in species composition (declined in beta diversity). They are now composed of more and smaller trees. Along the unregulated rivers, colonizing species have declined while later successional flood-tolerant species have increased. In the aftermath of Dutch elm disease, Ulmus spp. have greatly declined in abundance and size. Species with less flooding tolerance have generally increased across sites, especially along dam-regulated rivers. Because they are subject to chronic disturbances that reset succession, floodplain forests may respond more readily to shifts in disturbances regimes. Such forests may therefore serve as sentinels for forecasting the types of change that we can expect to unfold more gradually in upland forests.
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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 | 0.001 | 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) | 0.001 | 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".