Controls on ecosystem and root respiration across a permafrost and wetland gradient in interior Alaska
Bibliographic record
Abstract
Permafrost is common to many northern wetlands given the insulation of thick organic soil layers, although soil saturation in wetlands can lead to warmer soils and increased thaw depth. We analyzed five years of soil CO 2 fluxes along a wetland gradient that varied in permafrost and soil moisture conditions. We predicted that communities with permafrost would have reduced ecosystem respiration (ER) but greater temperature sensitivity than communities without permafrost. These predictions were partially supported. The colder communities underlain by shallow permafrost had lower ecosystem respiration (ER) than communities with greater active layer thickness. However, the apparent Q 10 of monthly averaged ER was similar in most of the vegetation communities except the rich fen, which had smaller Q 10 values. Across the gradient there was a negative relationship between water table position and apparent Q 10 , showing that ER was more temperature sensitive under drier soil conditions. We explored whether root respiration could account for differences in ER between two adjacent communities (sedge marsh and rich fen), which corresponded to the highest and lowest ER, respectively. Despite differences in root respiration rates, roots contributed equally (∼40%) to ER in both communities. Also, despite similar plant biomass, ER in the rich fen was positively related to root biomass, while ER in the sedge marsh appeared to be related more to vascular green area. Our results suggest that ER across this wetland gradient was temperature-limited, until conditions became so wet that respiration became oxygen-limited and influenced less by temperature. But even in sites with similar hydrology and thaw depth, ER varied significantly likely based on factors such as soil redox status and vegetation composition.
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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 | 0.001 | 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".