Dynamics of stem water uptake among isohydric and anisohydric species experiencing a severe drought
Bibliographic record
Abstract
Predicting the impact of drought on forest ecosystem processes requires an understanding of trees' species-specific responses to drought, especially in the Eastern USA, where species composition is highly dynamic due to historical changes in land use and fire regime. Here, we adapted a framework that classifies trees' water-use strategy along the spectrum of isohydric to anisohydric behavior to determine the responses of three canopy-dominant species to drought. We used a collection of leaf-level gas exchange, tree-level sap flux and stand-level eddy covariance data collected in south-central Indiana from 2011 to 2013, which included an unusually severe drought in the summer of 2012. Our goal was to assess how patterns in the radial profile of sap flux and reliance on hydraulic capacitance differed among species of contrasting water-use strategies. In isohydric species, which included sugar maple (Acer saccharum Marsh.) and tulip poplar (Liriodendron tulipifera L.), we found that the sap flux in the outer xylem experienced dramatic declines during drought, but sap flux at inner xylem was buffered from reductions in water availability. In contrast, for anisohydric oak species (Quercus alba L. and Quercus rubra L.), we observed relatively smaller variations in sap flux during drought in both inner and outer xylem, and higher nighttime refilling when compared with isohydric species. This reliance on nocturnal refilling, which occurred coincident with a decoupling between leaf- and tree-level water-use dynamics, suggests that anisohydric species may benefit from a reliance on hydraulic capacitance to mitigate the risk of hydraulic failure associated with maintaining high transpiration rates during drought. In the case of both isohydric and anisohydric species, our work demonstrates that failure to account for shifts in the radial profile of sap flux during drought could introduce substantial bias in estimates of tree water use during both drought and non-drought periods.
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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".