High‐level rather than low‐level warming destabilizes plant community biomass production
Bibliographic record
Abstract
Abstract Ecosystem stability is essential to its sustainable functions and services to humanity. Although climate warming is projected to vary from 1 to 5°C by the end of 21st century, how the temporal stability of plant community biomass production responds to different warming scenarios remains unclear. To fill this knowledge gap, we conducted a 6‐year field experiment with three levels of warming treatments (control, +1.5°C, +2.5°C) by using infrared radiators, in an alpine meadow on the Qinghai–Tibet Plateau. We found that low‐level warming (+1.5°C), compared to the control, did not significantly change the temporal stability of plant community biomass production and its underlying causes, including species diversity, compensatory dynamics, mean–variance scaling, biomass temporal stability of plant population (the average of temporal stability of species biomass production of all species in the community) or dominant species. However, high‐level warming (+2.5°C) significantly reduced them. Species diversity was not a significant predictor of temporal stability of plant community biomass production in this species‐rich ecosystem, regardless of the magnitude of warming, while co‐existing species compensatory dynamics and the biomass temporal stability of dominant species determined the response of temporal stability of plant community biomass production to warming. Synthesis . Our results suggest that the responses of plant community biomass temporal stability and its underlying mechanisms to climate warming depend on warming magnitudes. The findings highlight the various responses of ecosystem functions and services to different warming scenarios and imply that ecosystem will fail to maintain and provide stable biomass‐related services for humanity under high‐level climate warming.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".