Water availability and forest growth in coarse-textured soils
Bibliographic record
Abstract
Huang, M., Barbour, S. L., Elshorbagy, A., Zettl, J. D. and Si, B. C. 2011. Water availability and forest growth in coarse-textured soils. Can. J. Soil Sci. 91: 199-210. A method of evaluating the influence of soil layering and climatic variability on plant available water for forest growth is presented. This method enables species-specific levels of maximum sustainable plant transpiration to be evaluated. A calibrated HYDRUS-1D model was used with a 60-yr meteorological record to simulate actual evapotransipration (ETa) of dominant tree species with different values of leaf area index (LAI) for three sites in northern Alberta. A probability distribution of ETa was developed for each case. The relationships between LAI, plant above-ground primary production (ANPP), and ETa were used to estimate the minimum water demand to support plant growth at specific sites. The developed frequency curves of ETa and the minimum water demand can be used to determine the maximum sustainable LAI and the risk associated with revegetating a particular site with a dominant tree species. The effect of different tree species on the minimum water demand and the maximum sustainable LAI was also illustrated. The results indicated that layering of coarse-textured soils can provide more plant available water and support a higher maximum sustainable LAI than homogeneous soils of a similar texture.
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 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) | 0.001 | 0.001 |
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".