An initial intercomparison of micrometeorological and ecological inventory estimates of carbon exchange in a mid‐latitude deciduous forest
Bibliographic record
Abstract
Abstract The role of mid‐latitude forests in the sequestration of carbon (C) is of interest to an increasing number of scientists and policy‐makers alike. Net CO2exchange can be estimated on an annual basis, using eddy‐covariance techniques or from ecological inventories of C fluxes to and from a forest. Here we present an intercomparison of annual estimates of C exchange in a mixed hardwood forest in the Morgan‐Monroe State Forest, Indiana, USA for two years, 1998 and 1999. Based on eddy‐covariance measurements made at 1.8 times canopy height from a tower, C uptake by the forest was 237 and 287 g C m−2 y−1for 1998 and 1999, respectively. For the same time period, biometric and ecophysiological measures and modelled estimates of all significant carbon fluxes within deciduous forests were made, including: change in living biomass, aboveground and belowground detritus production, foliage consumption, and forest floor and soil respiration. Using this ecological inventory method for these same two time periods, C uptake was estimated to be 271 and 377 g C m−2 y−1, which are 14.3% and 31.4% larger, respectively, than the tower‐based values. The relative change between this method's annual estimates is consistent with that of the eddy‐covariance based values. Our results indicate that the difference in annual C exchange rates was due to reduced heterotrophic soil respiration in 1999.
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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 | 0.002 | 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 | 0.001 | 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".