Recovery of ecosystem carbon pools 35 years after whole-tree and stem-only clearcutting a red spruce – balsam fir forest in north-central Maine, USA
Bibliographic record
Abstract
Long-term field studies are critical to obtain credible knowledge on the effects of forest management. We tested the effect of whole-tree (WTH), stem-only (SOH) and no harvest (REF) on carbon (C) pools of a spruce-fir forest in Maine, USA in the long-term Weymouth Point Study Area, consisting of two adjacent watersheds with similar site conditions, species composition, and disturbance history. Harvest was conducted on one watershed in 1981. The other was left as an uncut late-successional reference. Fieldwork took place on various occasions from 1979 to 2016, on 22–31 plots. Thirty-five years after harvest, the average living biomass C-pool was significantly smaller for WTH than SOH on poorly drained (PD) soils, with no significant difference on somewhat poorly to moderately well-drained (SP-MW) soils, and no significant differences for deadwood, forest floor and mineral soil C. When including pre-harvest above-stump living biomass and forest floor C as co-variates for plots with available estimates, the deadwood C-pool was significantly smaller after WTH compared to SOH, as was forest floor C on PD but not on SP-MW soils. In 2016, living biomass, deadwood, and forest floor C-pools on the harvested watershed recovered to 62–67 %, 38–39 %, and 55–64 % of the corresponding C-pools for REF, while the mineral soil C-pool was 115–124 % of that of REF. Interpretation of C recovery is sensitive to the reference. Harvest left a long-term legacy on the landscape, with living biomass C on a trajectory towards fast recovery, while dead organic matter C pools recover at a slower pace.
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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) | 0.000 | 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".