Flood flow attenuation diminishes cottonwood colonization sites: an experimental test along the Boise River, USA
Bibliographic record
Abstract
Abstract The Boise River in southwest Idaho, USA, flows from forested mountain headwaters to the sagebrush steppe where the river was first regulated in 1909 for irrigated agriculture. Large upstream dams constructed in 1915, 1950, and 1955 are now operated to manage water for both irrigation and the attenuation of flood flows. This, in combination with bank armoring and channelization, has produced a narrowed river channel with simplified morphology. After damming, the native black cottonwood forest, Populus trichocarpa, expanded onto positions previously within the active channel. Since then, sexual reproduction of these cottonwoods appears to have become limited, apparently because of the lack of colonization sites devoid of competing vegetation. We investigated this hypothesis by constructing a channel that simulated recruitment sites previously formed by flood flow events. We observed extensive black cottonwood seedling recruitment along this channel in contrast to nearby reference sites where there were no seedlings, only saplings that originated as clonal root suckers. We conclude that the attenuation of flood flows has removed the geomorphic disturbance that previously created sites for colonization. As a consequence, the forest currently propagates primarily by clonal suckering that fails to introduce genetic diversity essential for adapting to change in the environment. To compensate for this loss, we recommend selective clearing and regrading of the floodplain according to an engineered design as one method to create cottonwood colonization sites. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".