THE ROLE OF PLANT HYDRODYNAMICS AND PHENOLOGY IN PLANT WATER SOURCE APPORTIONMENT
Bibliographic record
Abstract
Understanding plant water sources, their apportionment in time, and the age distribution of transpired water remains \na major challenge in ecohydrology. While we know that transpiration is a dominant flux in the terrestrial water \ncycle, and that precipitation has been increasingly partitioned into evapotranspiration rather than runoff, the understanding \nof where trees get their water remains a major research gap. Basic questions of what sources of water are \nbeing taken up by roots, how that water travels through the xylem, how long takes for water to reach the stomata and \nthen diffuse back to the atmosphere are key to identify mechanisms that control the partitioning of soil water storage \ninto streamflow and transpiration. Trees use and store significant amounts of water. Their roots can create preferential \nflow paths in the soil, redistribute water within the soil profile, and reach far-deep water storages. Yet, the role of \ntree hydrodynamics and phenological processes have not been explored in the context of source apportionment age \ndistribution of transpiration. This challenges our ability to fully understand how forests use, store, and cycle water. \nI undertook a high-resolution weighing lysimeter experiment located in Switzerland, and a large field-based investigation \nat two long-term studies sites in Canada. In these studies, tree water transport, stem radius change, tree water \nstatus, and phenological transition phases were monitored along with high-temporal resolution measurements of stable \nisotopes in trees, soil and precipitation. The goal was to determine the mechanisms that control tree water use in space \nand in time and factors that may influence observations of stable isotopes within trees. The major findings of this \nresearch were firstly that xylem water analysis using direct vapor equilibration on laser spectroscopy, results in spectral \ncontamination introduced by organic compounds. But 17O-excess can be used as a tool to flag and quantify the degree \nof spectral contamination in direct vapor analysis and overcome the lack of flagging software or tools to detect contamination \nin vapor mode. Second, tree water status drives source water apportionment. Soil drying triggers changes \nin water status and results in shift in water uptake. Thus, measurements of tree water status in high-temporal resolution \ncan improve ours understanding of short-term shifts in tree water sources. High-temporal resolution measurements of \ntree water deficit offer new opportunities to understand patterns in tree water use when combined with stable isotopes. \nThird, phloem water is more depleted in heavy isotopes than xylem water. The difference between phloem and xylem \nwater is larger during phloem water refilling and in periods of tree water deficit. These observations led to proposing \na phloem refilling hypothesis and illustrated the need to better understand water transport within trees and potential \nisotope fractionation associations, as well as how this can affect tree water use observations. Fourth, this dissertation \nproposes a simple method to identify transpiration phenological phases in the boreal forest. This approach shows \ngood alignment and agreement with timing of phenological changes also observed with ecosystem evaporation fluxes, \nand canopy phenological processes. Lastly, the onset of stem rehydration and transpiration overlap with snowmelt, \nthe largest hydrological event in northern ecosystems. Trees seem to rely on snowmelt water to start transpiring and \nsnowmelt isotopic signatures dominate the transpiration stream in subsequent weeks. This investigation also showed \nthat source water signatures in the xylem are controlled by tree water transit times. The high-temporal resolution observations \nof tree water use along with the understanding of tree hydrodynamics suggests that ecohydrological separation \nillustrates the different velocities of flow paths, influenced by dynamic tree water use in space. Overall, through the coupled tree hydrodynamic measurements of tree water transport and water status, transpiration phenology, and stable \nisotope dynamics of trees, this research has advanced the understanding of tree water use in space and time.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".