Effect of flood regime on tree growth in the floodplain and surrounding uplands of the Wisconsin River
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Flood regime and vegetation flood tolerance interact to influence tree growth in riverine landscapes. We studied tree growth in floodplain and upland forests of the Wisconsin River. About a century ago, levees set back from the river were constructed on this floodplain. The levee restricts some floodplain area from overbank flood events, but leaves a portion of active floodplain still inundated by floods. We addressed two questions: (1) how do growth rates of flood‐tolerant and flood‐intolerant tree species in the floodplain differ with flood regime? (2) At the stand level, how does growth rate differ with flood regime and between floodplain and upland areas? Annual tree growth rates from 1991 to 2000 were determined from tree increment cores for both individual species and stands. Tree growth rates of individual species varied between flood regimes. The most flood‐tolerant species ( Betula nigra and Fraxinus pennsylvanica ) grew faster in areas with active flooding, while the growth of less flood‐tolerant species ( Quercus velutina and Q. ellipsoidalis ) was depressed in swales and active floodplain. However, stand‐level tree growth did not differ between the floodplain and upland, or between flood regimes within the floodplain. Therefore, variation in the growth of individual species may not scale up to create differences in stand‐level tree growth because forest community composition varies spatially with flood regime. We suggest that growth rates are similar among sites because each community comprises of species adapted to their current flood regime. Copyright © 2008 John Wiley & Sons, Ltd.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.001 |
| 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 it