Variability in aboveground carbon driven by slope aspect and curvature in an eastern deciduous forest, USA
Bibliographic record
Abstract
In forested ecosystems, topography and tree species contribute to spatial variability in carbon (C) dynamics through differential rates of C uptake and storage; therefore, estimates of species-specific and spatial variability in C can strengthen ecosystem budgets. To produce such estimates, we deconstructed watershed-scale C and component pools (e.g., wood biomass, litter) and fluxes at a fine scale using a small mixed deciduous forest catchment to determine the variation due to topographic position and species. Factors affecting fluxes included aspect, slope curvature, tree species contributions, and litter production. Annual C uptake into wood varied across the catchment from 0 to 34 kg C·year −1 and was 20% greater on southern aspects than northern ones and 33% greater in swales than non-swale slopes. Of the more than 20 tree species found in the forest canopy of the catchment, highest C uptake in woody biomass was measured in Quercus rubra L. growing in swales, followed by Quercus prinus L. syn. growing on the southern aspect, with the lowest aboveground wood increment measured in Pinus at higher elevations on non-swale slopes. Quercus leaf litter moved from where it dropped into litter traps to where it settled on the forest floor, shifting the location of litter C inputs to the soil. Local variation in aboveground C rivals regional variation across regions and has the potential to introduce error when scaling C measures from points to landscapes.
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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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".