Shoot water relations of mature black spruce families displaying a genotype x environment interaction in growth rate. III. Diurnal patterns as influenced by vapor pressure deficit and internal water status
Bibliographic record
Abstract
Pressure-volume curves were constructed and shoot water potentials measured for +20-year-old black spruce (Picea mariana (Mill.) BSP) trees from four full-sib families growing on a moist site and a dry site at the Petawawa Research Forest, Ontario, to determine whether differences in diurnal water relations traits were related to productivity. To assess the basis for the observed diurnal patterns, we analyzed effects of environmental and internal water stress variables on diurnal water relations traits. Among the water relations traits examined, turgor pressure was the most sensitive, responding to site, family and environmental variables and displaying the strongest diurnal responses to varying soil water availability and atmospheric vapor pressure deficit (VPD). Overall, there was an 84% drop in turgor pressure with increasing VPD: turgor pressure fell 46% in response to the first 0.75 kPa increase in VPD, and 9.7% in response to a second 0.75 kPa increase in VPD. The families differed in water relations responses to moderate water stress, but not in responses to minor or more extreme water stresses. Thus, at a VPD of 0.5 kPa, there was an estimated 83% greater family difference in turgor pressure on the dry site compared with the moist site. Soil and atmospheric water stress appeared to exert effects in tandem to elicit these responses (r(2) = 0.728). A comparison of the mechanisms of response to water deficit indicated that osmotic adjustment was more important than change in cell wall elasticity. We used a conceptual water relations model to illustrate the differences between tolerant and intolerant families in their mechanisms of water stress response. We conclude that, because genetic responses to site factors are dynamic, the integrated response over time contributes to the observed genetic x environmental interaction in growth.
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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".