Effects of forest harvesting on soil methane fluxes in Florida slash pine plantations
Bibliographic record
Abstract
We examined the effects of forest harvesting on the net exchange of methane (CH4) between the atmosphere and sandy soils in two mature slash pine (Pinus elliottii Engelm. var. elliottii) plantations in northern Florida. Before each of the stem-only harvests, soils in these plantations were net sinks for CH4 (-0.03 to -2.6 mg CH4·m-2·d-1) on all but one sampling date. On this one pre-harvest sampling date, soils in one plantation were net sources of CH4. This emission coincided with an average soil moisture content of 83% water filled pore space (WFPS), which was significantly greater than the average soil moisture contents (25-66% WFPS) for all pre-harvest sampling dates. After harvesting, soils in both plantations became net sources of CH4. Average emission rates from harvested soils ranged from 3 to 11 mg CH4·m-2·d-1. Harvested soils were net sources of CH4 for at least 1 year after the harvest. However, the duration of the post-harvest CH4 emission period was reduced by bedding the plantation soils, a typical post-harvest site preparation treatment. Bedded soils in harvested stands were either relatively small net CH4 sources (0.2 mg CH4·m-2·d-1) or net CH4 sinks (-0.4 mg CH4·m-2·d-1). Soil CH4 fluxes were highly correlated with soil moisture contents (r2 = 0.66 and 0.71; significant at p < 0.05), which were strongly influenced by climate and forest management practices. For example, soil moisture contents for one of our sites, averaged over the pre-harvest, post-harvest, and post-harvest-plus-bedding periods were 46, 68, and 38% WFPS, respectively. Our results suggest that increased soil moisture in southern pine plantations induced by either precipitation events or forest management changes the direction of the soil CH4 flux from sink to source.
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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".