Bald Cypress (Taxodium distichum) Knees Are Methane Sources Controlled by Geomorphology, Climate, and Hydrologic Extremes
Bibliographic record
Abstract
While there is evidence to suggest woody root structures, such as bald cypress (Taxodium distichum) “knees”, can act as conduits of methane (CH4) emissions, flux rates can be highly variable, and little has been done to explain variation from this emissions pathway. We captured spatial (i.e., across knee surface, within sites, between sites) and temporal dynamics of CH4 from knees with the goal of building empirical models that may be used to improve predictions of the contribution of these woody root structures to net CH4 emissions. Knee and soil CH4 emissions were measured across seasons within the lower Mississippi Alluvial Valley in a main channel, side channel, and a reservoir edge. Knees were a net source of CH4 across all seasons, even during periods of soil CH4 uptake. During periods of high methane flux, knee emissions varied across the knee surface, decreasing with height from ground, suggesting a possible soil-derived CH4 source. Knee CH4emissions at the main and side channels decreased during a severe drought and increased ~ ten-fold in summer and two-fold in winter following flooding events. At the reservoir edge, knee emissions were highest during summer pool (i.e., increased water levels). Knee CH4 emissions were positively correlated with water level and temperature, the degree to which differed across geomorphic positions. Our findings show that cypress knees appear to be an important contributor to wetland CH4 emissions. Future work should account for the density of knees and accurately upscale their emissions to better understand their ecosystem contribution.
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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 | 0.001 |
| 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) | 0.001 | 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".