Water use by fast-growing Eucalyptus urophylla plantations in southern China
Bibliographic record
Abstract
Tree growth, water use, climate and soil water conditions were monitored over 12 months in two 3-4-year-old Eucalyptus urophylla S.T. Blake plantations on the Leizhou Peninsula of southern China. The Hetou plantation was established on a sandy soil of sedimentary origin with low water storage capacity, and the Jijia plantation was established on a clay soil formed on basalt. Sapwood area was approximately 50% higher at Jijia than at Hetou because of differences in plant spacing (1994 versus 1356 stems ha(-1)). Annual water use, assessed by heat pulse measurements, was 542 mm at Hetou and 559 mm at Jijia, with mean sap flux densities of 2772 and 1839 l m(-2) day(-1), respectively. Limitations to water use, imposed by climatic and soil factors, were quantified by analysis of daily canopy conductance in relation to daytime vapor pressure deficit (VPD) and soil water content. Similar annual water use at the two sites was a result of higher VPD and soil water availability at Hetou compensating for the greater sapwood area at Jijia. Potential annual water use in the absence of soil water limitation was estimated at 916 mm at Jijia and 815 mm at Hetou. Higher water availability during the dry season and early wet season at Hetou than at Jijia was the result of deep root systems. The results imply that water use by plantations on soils with high water availability and in areas of high VPD may be reduced by establishment at wider spacing. The environmental cost of water use by plantations must be weighed against their economic and environmental values to determine an appropriate mix of forestry, agriculture and other land uses in regions where water resources are limited.
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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".