Regional analysis of litter quality in the central grassland region of North America
Bibliographic record
Abstract
Abstract. The central grassland region of North America is characterized by large gradients of temperature and precipitation. These climatic variables are important determinants of the distribution of plant species, and strongly influence plant morphology and tissue chemistry. We analysed regional patterns of plant litter quality as they vary with climate in grassland ecosystems throughout central North America including tall‐grass prairie, mixed grass prairie, shortgrass steppe, and hot desert grasslands. An extensive database from the International Biological Program and the Long‐Term Ecological Research Program allowed us to isolate the effects of climate from those of plant functional types on litter quality. Our analysis of grass species confirms a previously recognized positive correlation between C/N ratios and precipitation. Precipitation exhibited a similar positive relationship with lignin/N and percent lignin. Although there was no significant correlation between temperature and C/N, there was a significant positive relationship between temperature and both percent lignin and lignin/N. Among functional types, C 3 grasses had a slightly lower C/N ratio than C 4 grasses. Tall grass species exhibited higher C/N, lignin/N, and percent lignin than short grass species. This understanding of the regional patterns of litter quality and the factors controlling them provides us with a greater knowledge of the effect that global change and the accompanying feedbacks may have on ecosystem processes.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".