From tree to stand: Scaling relationships of water uptake and climate in a reclaimed boreal mixedwood stand.
Bibliographic record
Abstract
Soil water availability is a key factor in determining tree’s transpiration and sap flow rates, and varies with topography and soil depth. Reclaimed landscapes provide us with the unique opportunity to address the effects of those two variables independently on trees’ water uptake, and their relationship to climatic variation. We explored the relationship between individual tree water uptake and atmospheric variables for trembling aspen (Populus tremuloides) and white spruce (Picea glauca), and assessed how this relationship changed across different hillslope positions and rooting space. Growing season (May to September) sap and transpiration fluxes were monitored using heat ratio method sap flow sensors on trembling aspen and white spruce trees in 2014 and 2015 on a reclaimed hillslope in northern Alberta, Canada, with two different soil cover depths providing different rooting spaces. Both species’ sap flow rates and transpiration rates were strongly correlated to climatic variables such as vapor pressure deficit, precipitation events, air temperature, with slight differences in the relationship between topographical positions and soil depths. Site-level atmospheric water fluxes were obtained through eddy covariance measurements at the top of the hillslope. This allowed for a direct linkage of individual tree water uptake measurement to water flux measurements taken at the landscape-level. Understanding how distinct rooting and physiological characteristics of tree species and their growing conditions can be extrapolated to different scales, is crucial to our understanding of both atmospheric and edaphic water fluxes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".