Globally limited individual and combined effects of multiple global change factors on allometric biomass partitioning
Bibliographic record
Abstract
Abstract Aim Plant biomass allocation reflects the distribution of photosynthates among different organs in response to changing environmental conditions. Global change influences plant growth across terrestrial ecosystems, but impacts of individual and combined multiple global change factors (GCFs) on plant biomass allocation at the global scale are unclear. Location Global. Time period Contemporary. Major taxa studied Plants in terrestrial ecosystems. Methods We conducted a meta‐analysis of data comprising 4,180 pairwise observations to assess individual and combined effects of nitrogen addition (N), warming (W), elevated CO2(C), irrigation (I), and drought (D) on plant biomass allocation based on the ‘ratio‐based optimal partitioning’ and ‘isometric allocation’ hypotheses. Results We found that (a) ratio‐based plant biomass fractions of different organs were only minimally affected by individual and combined effects of the studied GCFs; (b) combined effects of two‐factor pairs of GCFs on plant biomass allocation were commonly additive, rather than synergistic or antagonistic; (c) moderator variables influenced, but seldom changed the direction of individual and combined effects of GCFs on plant biomass allocation; and (d) neither individual nor combined effects of the studied GCFs altered allometric relationships among different organs, indicating that patterns of plant biomass allocation under the environmental stress conditions exerted by the multiple GCFs were better explained by the isometric allocation rather than the ratio‐based optimal partitioning hypothesis. Main conclusions Our results show consistent patterns of allometric plant biomass partitioning under effects of multiple GCFs and provide evidence of an isometric plant biomass allocation trajectory in response to global change perturbations. These findings improve our understanding and prediction of terrestrial vegetation responses to future global change scenarios.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".