Data from: Individual size inequality links forest diversity and above-ground biomass
Bibliographic record
Abstract
1. Despite the mounting evidence for positive diversity–productivity relationships found in controlled experiments, diversity effects on productivity in natural systems remain hotly debated. Understanding the multivariate links between diversity and productivity in natural systems, in particular natural forests that host the majority of terrestrial biodiversity and provide essential services for humanity, remains a critical challenge for ecologists. 2. We analyzed data from 448 plots of varying tree species diversity, stand ages, and local nutrient availability in Canada's boreal forest (52°30’ – 55°24’ N latitude and 102°36’ – 108° W longitude). We used structural equation models to link multivariate relationships between above-ground biomass, tree species diversity, stand age, and soil nutrient availability. 3. Above-ground biomass increased with diversity indirectly via increasing tree size inequality, and increased with stand age and was higher on sites of medium soil nutrient regime directly as well as indirectly via increased tree size inequality. 4. Synthesis. Our results demonstrate positive diversity effects on above-ground biomass in natural forests of diverse forest ages and soil resource availability. Furthermore, we show that tree size inequality acts as a mechanism for the positive diversity effects on above-ground biomass, and as a mechanism in regulating above-ground biomass and species diversity simultaneously via interactions among individuals in natural forests.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.022 |
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".