Forest ecosystem respiration estimated from eddy covariance and chamber measurements under high turbulence and substantial tree mortality from bark beetles
Bibliographic record
Abstract
Eddy covariance nighttime fluxes are uncertain due to potential measurement biases. Many studies report eddy covariance nighttime flux lower than flux from extrapolated chamber measurements, despite corrections for low turbulence. We compared eddy covariance and chamber estimates of ecosystem respiration at the GLEES Ameriflux site over seven growing seasons under high turbulence [summer night mean friction velocity (u*) = 0.7 m s(-1)], during which bark beetles killed or infested 85% of the aboveground respiring biomass. Chamber-based estimates of ecosystem respiration during the growth season, developed from foliage, wood, and soil CO2 efflux measurements, declined 35% after 85% of the forest basal area had been killed or impaired by bark beetles (from 7.1 ± 0.22 μmol m(-2) s(-1) in 2005 to 4.6 ± 0.16 μmol m(-2) s(-1) in 2011). Soil efflux remained at ~3.3 μmol m(-2) s(-1) throughout the mortality, while the loss of live wood and foliage and their respiration drove the decline of the chamber estimate. Eddy covariance estimates of fluxes at night remained constant over the same period, ~3.0 μmol m(-2) s(-1) for both 2005 (intact forest) and 2011 (85% basal area killed or impaired). Eddy covariance fluxes were lower than chamber estimates of ecosystem respiration (60% lower in 2005, and 32% in 2011), but the mean night estimates from the two techniques were correlated within a year (r(2) from 0.18 to 0.60). The difference between the two techniques was not the result of inadequate turbulence, because the results were robust to a u* filter of >0.7 m s(-1). The decline in the average seasonal difference between the two techniques was strongly correlated with overstory leaf area (r(2) = 0.92). The discrepancy between methods of respiration estimation should be resolved to have confidence in ecosystem carbon flux estimates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".