Characterizing flow regimes for floodplain forest conservation: an assessment of factors affecting sapling growth and survivorship on three cold desert rivers
Bibliographic record
Abstract
I analyzed annual height growth and survivorship of Fremont cottonwood (Populus fremontii S. Watson) saplings on three floodplains in Colorado and Utah to assess responses to interannual variation in flow regime and summer precipitation. Mammal exclosures, supplemented with an insecticide treatment at one site, were used to assess flow regime herbivore interactions. Multiple regression analyses on data collected over 711 years indicated that growth of continuously injury-free saplings was positively related to either peak discharge or the maximum 30-day discharge but was not related to interannual decline in the late-summer river stage (ΔWMIN) or precipitation. Growth was fastest where ΔWMIN was smallest and depth to the late-summer water table moderate (≤1.5 m). Survivorship increased with ΔWMIN where the water table was at shallow depths. Herbivory reduced long-term height growth and survivorship by up to 60% and 50%, respectively. The results support the concept that flow history and environmental context determine whether a particular flow will have a net positive or negative influence on growth and survivorship and suggest that the flow regime that best promotes sapling growth and survival along managed rivers features a short spring flood pulse and constant base flow, with no interannual variation in the hydrograph. Because environmental contexts vary, interannual variation may be necessary for best overall stand performance.
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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) | 0.000 | 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".