Aboveground interactions and productivity in mixed-species plantations of <i>Acacia mearnsii</i> and <i>Eucalyptus globulus</i>
Bibliographic record
Abstract
This study compared productivity in mixed-species plantations of Eucalyptus globulus ssp. pseudoglobulus (Naudin ex Maiden) Kirkpatr. and Acacia mearnsii de Wild with pure stands of each species and investigated how this might be explained by canopy stratification between species and changes in leaf characteristics of eucalypts. Investigations were carried out at a trial using the replacement series design, which consisted of the following combinations: 100% eucalypts (100%E), 75% eucalypts + 25% acacia (75%E:25%A), 50% eucalypts + 50% acacia (50%E:50%A), 25% eucalypts + 75% acacia (25%E:75%A), and 100% acacia (100%A). At 9.5 years, stem volume and biomass were highest in 50%E:50%A treatments. Canopy stratification occurred in all mixtures, with acacias in the lower and eucalypts in the upper canopy stratum. This and the increasing canopy light interception with increasing proportion of acacia in the mixture indicated that A. mearnsii is substantially more shade tolerant than E. globulus. Midcanopy foliage of E. globulus in the 50%E:50%A mixture had higher foliage nitrogen (N) but lower phosphorus (P) concentrations and lower light-saturated net photosynthesis rates (A max ) than those in the 100%E treatment. In addition, similar relationships between eucalypt crown volume and stem biomass across treatments indicated that eucalypt crowns were not more efficient in mixture. Our study indicates that the productivity gains in these mixtures may be partially attributable to aboveground niche separation between species.
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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) | 0.001 | 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".