Herbage biomass and its relationship to soil carbon under long-term grazing in northern temperate grasslands
Bibliographic record
Abstract
While northern temperate grasslands are important for supporting beef production, it remains unclear how grassland above- and belowground biomass responds to long-term cattle grazing. Here, we use a comprehensive dataset from 73 grasslands distributed across a broad agro-climatic gradient to quantify grassland shoot, litter, and shallow (top 30 cm) root biomass in areas with and without grazing. Additionally, we relate biomass to soil carbon (C) concentrations. Forb biomass was greater (p < 0.05) in grazed areas, particularly those receiving more rainfall. In contrast, grass and total aboveground herbage biomass did not differ with grazing (total: 2320 kg ha−1 for grazed vs. 2210 kg ha−1 for non-grazed; p > 0.05). Forb crude protein concentrations were lower (p < 0.05) in grazed communities compared with those that were non-grazed. Grasslands subjected to grazing had 56% less litter mass. Root biomass down to 30 cm remained similar between areas with (9090 kg ha−1) and without (7130 kg ha−1) grazing (p > 0.05). Surface mineral soil C concentrations were positively related to peak grassland biomass, particularly total (above + belowground) biomass, and with increasing forb biomass in grazed areas. Finally, total aboveground shoot biomass and soil C concentrations in the top 15 cm of soil were both positively related to the proportion of introduced plant diversity in grazed and non-grazed grasslands. Overall, cattle grazing at moderate stocking rates had minimal impact on peak grassland biomass, including above- and belowground, and a positive contribution exists from introduced plant species to maintaining herbage productivity and soil C.
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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) | 0.001 | 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".