Tree rings from a European beech forest chronosequence are useful for detecting growth trends and carbon sequestration
Bibliographic record
Abstract
Past carbon (C) storage trends were estimated using dendroecological methods in a beech chronosequence in central Germany. Raw-ring-width chronologies, sensitivity curves, and carbon uptake trends were developed for 70-, 110-, and 150-year-old (S70, S110, and S150), even-aged stands. Ecosystem C stock and net ecosystem productivity (NEP C ) were computed as the sum of the C stock and fluxes of the soil, the aboveground compartment, and the estimated belowground compartment. The ecosystem C stock ranged from 216 t C·ha 1 in S150, to 265 t C·ha 1 in S70, to 272 in S110. NEP C values followed ecosystem C stocks, ranging from 1.7, to 2.4, to 5.1 t C·ha 1 ·year 1 for S150, S70, and S110, respectively. Stem C-stock uptake rate in S110 showed an increase in growth rate over the first 110 years of S150. We estimate that this increase in stem C stock was 6.2%. Given the constancy of forest management among the stands of the chronosequence, we hypothesize that the increase in C stock shown by S110 is due to indirect human-induced effects. We conclude that managed young forests can take advantage of increased resources and counteract the C losses at harvest that are seen in the old forests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.003 | 0.001 |
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".