Land cover change in eastern Kansas: litter dynamics of closed-canopy eastern redcedar forests in tallgrass prairie
Bibliographic record
Abstract
In the Great Plains region, eastern redcedar (Juniperus virginiana L.) abundance has increased dramatically in areas historically occupied by tallgrass prairie. This shift in dominant vegetation is likely to be accompanied by changes in ecosystem structure and function, including quantity, quality, and location (above- vs. below-ground) of litter inputs and subsequent effects on decomposition dynamics. The purpose of this study was to quantify and compare patterns of litterfall and decomposition in mature redcedar forests and adjacent prairie. Annual redcedar litterfall was 500 g·m-2·year-1, a large increase in foliar litter inputs compared with annually burned grassland (52 g·m-2·year-1). Using a reciprocal transplant decomposition study with four substrates, redcedar leaves and roots, and big bluestem (Andropogon gerardii Vitman) foliage and roots, we found marginal habitat effects, but greater differences between species, presumably owing to litter quality (including both C:N and lignin content). Decay rates were significantly higher in the prairie relative to the forest for each substrate. Additionally, within any particular habitat, grass litter had significantly faster decay rates than forest litter. These results suggest a shift in patterns of litter input and decomposition processes with afforestation of tallgrass prairie, which may result in long-term changes in C sequestration and storage.Key words: litter dynamics, eastern redcedar (Juniperus virginiana), big bluestem (Andropogon gerardii), decomposition, tallgrass prairie, nitrogen immobilization.
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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 | 0.000 |
| 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 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".