Multitrophic diversity and biotic associations influence subalpine forest ecosystem multifunctionality
Bibliographic record
Abstract
Biodiversity across multiple trophic levels is required to maintain multiple ecosystem functions. Yet it remains unclear how multitrophic diversity and species interactions regulate ecosystem multifunctionality. Here, combining data from 9 different trophic groups (including trees, shrubs, herbs, leaf mites, small mammals, bacteria, pathogenic fungi, saprophytic fungi, and symbiotic fungi) and 13 ecosystem functions related to supporting, provisioning, and regulating services, we used a multitrophic perspective to evaluate the effects of elevation, diversity, and network complexity on scale-dependent subalpine forest multifunctionality. Our results demonstrated that elevation and soil pH significantly modified species composition and richness across multitrophic groups and influenced multiple functions simultaneously. We present evidence that species richness across multiple trophic groups had stronger effects on multifunctionality than species richness at any single trophic level. Moreover, biotic associations, indicating the complexity of trophic networks, were positively associated with multifunctionality. The relative effects of diversity on multifunctionality increased at the scale of the larger community compared to a scale accounting for neighboring interactions. Our results highlight the paramount importance of scale- and context-dependent multitrophic diversity and interactions for a better understanding of mountain ecosystem multifunctionality in a changing world.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".