Functional diversity dominates positive species mixture effects on ecosystem multifunctionality in subtropical plantations
Bibliographic record
Abstract
Mixed-species plantations generally exhibit higher ecosystem multifunctionality than monospecific plantations. However, it is unclear how tree species functional composition influences species mixture effects on ecosystem multifunctionality. We selected 171 monospecific and mixed-species plantations from nine regions across subtropical China, and quantified 13 key ecosystem functional properties to investigate how species mixture effects on ecosystem multifunctionality are modulated by functional diversity and identity. We found that ecosystem multifunctionality was significantly higher (p < 0.05) in mixed tree plantations than in monospecific plantations except the mixed-conifer species plantations. Across all regions, ecosystem multifunctionality was significantly higher (p < 0.05) in mixed conifer-broadleaf plantations than in monospecific plantations of the corresponding species, but not different between mixed and monospecific coniferous plantations. The magnitude of species mixture effects on ecosystem multifunctionality varied greatly with tree species compositions. Taking Cunninghamia lanceolata Lamb. as an example, the effects varied from a range of 2.0%–9.6% when mixed with a conifer species to 36%–87% when mixed with a broadleaf species. The functional diversity was the dominate driver shaping ecosystem multifunctionality, while functional identity, as expressed by community-weighted mean of specific leaf area, also had a positive effect on ecosystem multifunctionality through the increased below-ground nitrogen and phosphorus stocks regulated by specific leaf area of the mixing tree species. Our study highlights the important role of functional diversity in shaping ecosystem multifunctionality across region-wide environmental conditions. Mixed conifer-broadleaf tree plantations with distinct functional traits benefit the enhancement of ecosystem multifunctionality, and the magnitude of species mixture effects is modulated by the functional identity of tree species composition; those relationships deserve a special consideration in multifunctional management context of subtropical plantations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".