Liming suppresses fine root production and turnover in a northern hardwood forest
Bibliographic record
Abstract
Fine roots and root-associated carbon (C) inputs contribute disproportionally to soil C stocks. Here, we quantified fine root dynamics in a mixed northern hardwood forest at the Woods Lake Watershed in the Adirondack Park, NY, USA, where an experimental lime application in 1989 led to the near-doubling of forest floor organic matter stocks two decades later. Prior work linked this organic matter accumulation with lower heterotrophic respiration and decreased abundances of major fungal saprotrophs and ectomycorrhizal fungi. We investigated whether liming-driven shifts in fine root dynamics and depth distribution also contributed to forest floor accumulation. Forest floor mass in limed plots again roughly doubled that in unlimed plots 32 years after liming, with persistently large accumulations in the Oa horizon. Liming decreased fine root production across all horizons measured (Oe, Oa, 0–10 cm mineral soil) and by 40% overall, with largest effects in the Oa horizon (−45%) where root turnover was also reduced (−59%). Thus, liming decreased, rather than increased, root detrital C inputs to the forest floor. These results suggest that liming must have suppressed decomposition even more than shown previously or increased some other C input to the forest floor to explain its substantial C accumulation.
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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 | 0.001 | 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".