Hierarchical Reproductive Allocation and Allometry within a Perennial Bunchgrass after 11 Years of Nutrient Addition
Bibliographic record
Abstract
Bunchgrasses are one of the most important plant functional groups in grassland ecosystems. Reproductive allocation (RA) for a bunchgrass is a hierarchical process; however, how bunchgrasses adjust their RAs along hierarchical levels in response to nutrient addition has never been addressed. Here, utilizing an 11-year nutrient addition experiment, we examined the patterns and variations in RA of Agropyron cristatum at the individual, tiller and spike levels. We evaluated the reproductive allometric relationship at each level by type II regression analysis to determine size-dependent and size-independent effects on plant RA variations. Our results indicate that the proportion of reproductive individuals in A. cristatum increased significantly after 11 years of nutrient addition. Adjustments in RA in A. cristatum were mainly occurred at the individual and tiller levels but not at the spike level. A size-dependent effect was a dominant mechanism underlying the changes in plant RA at both individual and tiller levels. Likewise, the distribution of plant size was markedly changed with large individuals increasing after nutrient addition. Tiller-level RA may be a limiting factor for the adjustment of RA in A. cristatum. To the best of our knowledge, this study is the first to examine plant responses in terms of reproductive allocation and allometry to nutrient enrichment within a bunchgrass population from a hierarchical view. Our findings have important implications for understanding the mechanisms underlying bunchgrass responses in RA to future eutrophication due to human activities. In addition, we developed a hierarchical analysis method for disentangling the mechanisms that lead to variation in RA for perennial bunchgrasses.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".