Greater than the sum of the parts: how the species composition in different forest strata influence ecosystem function
Bibliographic record
Abstract
The mechanisms underpinning forest biodiversity-ecosystem function relationships remain unresolved. Yet, in heterogeneous forests, ecosystem function of different strata could be associated with traits or evolutionary relationships differently. Here, we integrate phylogenies and traits to evaluate the effects of elevational diversity on above-ground biomass across forest strata and spatial scales. Community-weighted means of height and leaf phosphorous concentration and functional diversity in specific leaf area exhibited positive correlations with tree biomass, suggesting that both positive selection effects and complementarity occur. However, high shrub biomass is associated with greater dissimilarity in seed mass and multidimensional trait space, while species richness or phylogenetic diversity is the most important predictor for herbaceous biomass, indicating that species complementarity is especially important for understory function. The strength of diversity-biomass relationships increases at larger spatial scales. We conclude that strata- and scale- dependent assessments of community structure and function are needed to fully understand how biodiversity influences ecosystem function.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".