Diurnal and seasonal changes in stem increment and water use by yellow poplar trees in response to environmental stress
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To evaluate indicators of whole-tree physiological responses to climate stress, we determined seasonal, daily and diurnal patterns of growth and water use in 10 yellow poplar (Liriodendron tulipifera L.) trees in a stand recently released from competition. Precise measurements of stem increment and sap flow made with automated electronic dendrometers and thermal dissipation probes, respectively, indicated close temporal linkages between water use and patterns of stem shrinkage and swelling during daily cycles of water depletion and recharge of extensible outer-stem tissues. These cycles also determined net daily basal area increment. Multivariate regression models based on a 123-day data series showed that daily diameter increments were related negatively to vapor pressure deficit (VPD), but positively to precipitation and temperature. The same model form with slight changes in coefficients yielded coefficients of determination of about 0.62 (0.57-0.66) across data subsets that included widely variable growth rates and VPDs. Model R2 was improved to 0.75 by using 3-day running mean daily growth data. Rapid recovery of stem diameter growth following short-term, diurnal reductions in VPD indicated that water stored in extensible stem tissues was part of a fast recharge system that limited hydration changes in the cambial zone during periods of water stress. There were substantial differences in the seasonal dynamics of growth among individual trees, and analyses indicated that faster-growing trees were more positively affected by precipitation, solar irradiance and temperature and more negatively affected by high VPD than slower-growing trees. There were no negative effects of ozone on daily growth rates in a year of low ozone concentrations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it