Productivity, resource use, and competitive interactions of <i>Fraxinus uhdei</i> in Hawaii uplands
Bibliographic record
Abstract
We examined stand growth, canopy development, and resource use of Fraxinus uhdei (Wenzig) Lingelsh, a nonindigenous tree grown in Hawaii, and its interactions with the native, N-fixing tree Acacia koa Gray. Along a gradient of decreasing rainfall with elevation, on Histosols, F. uhdei had decreased stand basal area, productivity, and canopy development. At high-elevation sites, productivity of F. uhdei was limited by N, and F. uhdei benefitted from association with A. koa, as (i) foliar N content of F. uhdei was positively related to aboveground net primary productivity (ANPP), (ii) leaf area index, biomass increment, and ANPP of F. uhdei increased in a single-species stand after N additions, but there was no response by either F. uhdei or A. koa in a mixed stand, and (iii) productivity of F. uhdei in mixed stands with A. koa at high-elevation sites was greater than in single-species stands, and F. uhdei foliage was enriched with N in proportion to the fraction of stand basal area in A. koa. Seemingly, growth of F. uhdei on Histosols was also limited by water availability, as an index of carbon isotope composition of leaves (δ13C), and, therefore, intrinsic water-use efficiency (WUE) increased with elevation. Biomass production of F. uhdei stands per unit leaf area and per unit intercepted radiation (ε) decreased with increasing elevation on Histosols. Decreased nitrogen-use efficiency and ε of F. uhdei on Histosols were both traded off against increased WUE.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".