Plant functional traits affect biomass responses to global change: A meta‐analysis
Bibliographic record
Abstract
Abstract Whether and how the responses of above‐ (AGB) and below‐ground biomass (BGB) and above‐ground net primary production (ANPP) to global changes are linked to plant functional traits is unclear. We conducted a global meta‐analysis based on 2561 observations from 318 manipulative studies (primarily forest, grassland and cropland monocultures) to examine the effect of plant functional traits (i.e. morphological and chemical traits, mycorrhizal association type and symbiotic nitrogen (N) fixation) of dominant species on the responses of plant biomass production to global change drivers, that is, elevated CO 2 (eCO 2 ), elevated nutrient (eNutrient), elevated water (eWater), warming and drought. Across all terrestrial ecosystems studied, eCO 2 , eNutrient and eWater increased, while drought reduced biomass production. Warming had no overall effect on any of the biomass production metrics. Importantly, the positive effects of eNutrient on BGB were more pronounced for communities dominated by ‘fast’ species (with high specific leaf area and leaf N content). Plant communities dominated by plants with low resource uptake rates by roots exhibited stronger effects of eCO 2 on ANPP and weaker effects of eNutrient on AGB, BGB and ANPP. In communities dominated by arbuscular mycorrhizal fungi‐associated plants, eNutrient increased AGB and ANPP, and drought reduced AGB. In contrast, eNutrient and drought increased BGB in communities dominated by ectomycorrhizal fungi‐associated plants. eCO 2 increased ANPP in communities dominated by non‐N‐fixing species but not in communities dominated by N‐fixing species. Synthesis . Accounting for functional traits of dominant plants improves the predictability of ecosystem responses to global change, and can guide ecological management practices to safeguard key ecosystem functions in a rapidly changing world.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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 teacher head, 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".