Drought and flood stress tolerance of butternut (<i>Juglans cinerea</i>) and naturally occurring hybrids: implications for restoration
Bibliographic record
Abstract
Efforts to restore species threatened by introduced pathogens often include breeding resistance into susceptible native species from resistant exotics, but this is a lengthy and expensive process. Naturally occurring hybrids between susceptible and resistant species may accelerate this process if they fulfill the desired species’ ecological function. To explore this possibility, we exposed the following seedlings to drought and flood treatments in a controlled environment: Juglans cinerea L. (butternut), which has been devastated by an exotic pathogen; Juglans ailantifolia Carr. var. cordiformis (heartnut); Juglans × bixbyi Rehd. [ailanthifolia × cinerea] (buartnut), multigenerational hybrids between butternut and heartnut; and Juglans nigra L. (black walnut). There was a strong taxa × treatment interaction. Butternut had a negative response to flood treatments, expressed by reduced leaf area (LA), photosynthetic assimilation (A), and chlorophyll fluorescence (Fv/Fm). Heartnut had a negative response to drought, expressed by lower LA and A. Hybrid A and LA were reduced in response to both treatments. Results indicate that hybrid drought and flood tolerance may limit their overall ability to completely occupy the ecological niche formerly filled by butternut. However, the strong dichotomous response of progenitors to moisture stress suggests that hybrids could be efficiently screened for J. cinerea character in conjunction with disease resistance.
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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".