Carbon balance of a southern taiga spruce stand in European Russia
Bibliographic record
Abstract
We present results from nearly three years of net ecosystem flux measurements above a boreal spruce stand growing in European Russia. Fluxes were measured by eddy covariance using conventional techniques. In all years examined (1998–2000), the forest was a significant source of carbon to the atmosphere. However, the magnitude of this inferred source depended upon assumptions regarding the degree of “flux” loss under conditions of low turbulence, such as typically occur at night. When corrections were not made, the forest was calculated to be only a modest source of C to the atmosphere (3–5 mol C m−2 yr−1). However, when the corrections were included, the apparent source was much larger (20–30 mol C m−2 yr−1). Using a simple model to describe the temperature dependencies of ecosystem respiration on air and soil temperatures, about 80% of the night-time flux was inferred to be from soil respiration, with the remainder being attributable to foliage, branches and boles. We used reasonable assumptions to estimate the rate of ecosystem respiration during the day, allowing an estimation of canopy photosynthetic rates and hence the annual Gross Primary Productivity of the ecosystem. For the two full years examined (1999 and 2000), this was estimated at 122 and 130 mol C m−2 yr−1, respectively. This value is similar to estimates for boreal forests in Scandinavia, but substantially higher than has been reported for Canadian or Siberian boreal forests. There was a clear tendency for canopy photosynthetic rates to increase with both light and temperature, but the slope of the temperature response of photosynthesis was less steep that that of ecosystem respiration. Thus, on most warm days in summer the forest was a substantial source of carbon to the atmosphere; with the forest usually being a net sink only on high insolation days where the average daily air temperatures were below about 18 °C. These data, along with other studies on the current balance of boreal ecosystems, suggests that at the current time many boreal forests might be releasing substantial amounts of carbon dioxide to the atmosphere. This observed temperature sensitivity of this ecosystem suggests that this might be a consequence of substantially higher than average temperatures over recent years.xs
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".