Belowground and aboveground biomass in young postfire lodgepole pine forests of contrasting tree density
Bibliographic record
Abstract
As much as 40% of live biomass in coniferous forests is located belowground, yet the effect of tree density on biomass allocation is poorly understood. We developed allometric equations using traditional harvesting techniques to estimate coarse root biomass for [Formula: see text]13-year-old postfire lodgepole pine trees (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.). We then used these equations, plus estimates of fine root and aboveground biomass, to estimate total tree biomass and belowground to aboveground biomass ratios in young postfire lodgepole pine stands with a wide range of tree densities. Belowground biomass allocation increased with tree density, but the increase was largely determined by inherent differences associated with tree size, not competition. Stand biomass in trees ranged from 46 to 5529 kg·ha1 belowground, from 176 to 9400 kg·ha1 aboveground, and from 222 to 13 685 kg·ha1 for total biomass. For individual trees, the ratio of belowground to total biomass declined with tree size from 0.44 at a basal diameter of 0.5 cm to 0.11 at a basal diameter of 8 cm. This shift in individual tree allocation caused the proportion of total stand biomass in belowground tissues to increase from 19% in low-density stands with larger trees to 31% in high-density stands with small trees.
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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 | 0.000 | 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".