Variation in Peak Growing Season Net Ecosystem Production Across the Canadian Arctic
Bibliographic record
Abstract
Tundra ecosystems store vast amounts of soil organic carbon, which may be sensitive to climatic change. Net ecosystem production, NEP, is the net exchange of carbon dioxide (CO(2)) between landscapes and the atmosphere, and represents the balance between CO(2) uptake by photosynthesis and release by decomposition and autotrophic respiration. Here we examine CO(2) exchange across seven sites in the Canadian low and high Arctic during the peak growing season (July) in summer 2008. All sites were net sinks for atmospheric CO(2) (NEP ranged from 5 to 67 g C m(-2)), with low Arctic sites being substantially larger CO(2) sinks. The spatial difference in NEP between low and high Arctic sites was determined more by CO(2) uptake via gross ecosystem production than by CO(2) release via ecosystem respiration. Maximum gross ecosystem production at the low Arctic sites (average 8.6 μmol m(-2) s(-1)) was about 4 times larger than for high Arctic sites (average 2.4 μmol m(-2) s(-1)). NEP decreased with increasing temperature at all low Arctic sites, driven largely by the ecosystem respiration response. No consistent temperature response was found for the high Arctic sites. The results of this study clearly indicate there are large differences in tundra CO(2) exchange between high and low Arctic environments and this difference should be a central consideration in studies of Arctic carbon balance and climate change.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".