INUNDATION TOLERANCES OF RIPARIAN WILLOWS AND COTTONWOODS<sup>1</sup>
Bibliographic record
Abstract
ABSTRACT: Throughout western North America, willows and cottonwoods are dominant woody plants in riparian zones, streamside areas that are periodically flooded. This study compared tolerances of willows‐Salix discolor, S. exigua, and S. lutea‐and cottonwoods‐Populus angustifolia, P balsamifera, and P deltoides‐to water inundation, one component of stream flooding. Rooted cuttings were grown for 152 days in 10 cm tall pots in water depths from 2.5 to 10 cm (inundated). Shoot and root elongation growth of the inundated cottonwoods were reduced 23 and 45 percent, while S. lutea was relatively unaffected and the inundated sandbar willow, S. exigua, displayed 72 and 43 percent increases in shoot and root elongation. The inundation reduced transpiration in P deltoides and for mature P balsamifera trees that were flooded by a small reservoir on Willow Creek, Alberta. Those flooded trees died in their second year of inundation. The greater inundation tolerance of willows versus cottonwoods is consistent with observations along Midvale Creek, Montana, where beaver dams created a pond in which P trichocarpa died while willows thrived after five years. These patterns of inundation tolerance are consistent with elevational zones of occurrence as willows‐and particularly the sandbar willow—occur at low elevations close to the stream. The understanding of inundation tolerances should assist in the provision of hydrologic patterns that will conserve and restore these shrubs and trees along streams and could permit their establishment along artificial reservoirs.
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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 | 0.000 | 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".