Factors controlling the interannual variability in the carbon balance of a southern boreal black spruce forest
Bibliographic record
Abstract
Factors controlling the seasonal and interannual variability of net ecosystem productivity ( F NEP ), gross ecosystem photosynthesis ( P g ), ecosystem respiration ( R e ) and evapotranspiration ( E ) of a mature boreal black spruce forest in central Saskatchewan, Canada were investigated using eight years (1999–2006) of continuous eddy covariance measurements. During 2000–2006, which included a three‐year drought, the forest was a weak sink for CO 2 with annual F NEP ranging from 27 to 80 g C m ‐2 (56 ± 21 g C m −2 a −1 ). The beginning of the growing season occurred when daily mean air temperature exceeded 4°C and the near surface soil temperature equaled or exceeded 0°C. The length of the growing season varied from 186 to 232 days. During the extreme drought year (2003), the smaller reduction in annual P g than in R e resulted in highest F NEP of the record. Annual F NEP decreased slightly with increasing soil water content; however, there was evidence of increased F NEP due to high water table conditions in 2004 because of the slightly higher decrease in R e than P g . Although bulk surface conductance ( g s ) decreased significantly during the dry conditions in 2003, the associated increase in D prevented a significant drop in E , which resulted in only a slight decline in evaporative fraction and almost no change in water use efficiency. Interannual variation in P g , R e and F NEP in the early growing season (April–June) and late growing season (July–September) was controlled by air temperature and soil water content, respectively. However, spring (April–May) mean air temperature was the main factor determining the interannual variation in annual F NEP . The effect of late growing season soil water content on annual P g and R e was greater than its effect on annual F NEP . The results emphasize the need to consider soil moisture conditions as well as temperature when simulating the response of the carbon balance components of this ecosystems to 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".