Mismatch between primary and secondary growth and its consequences on wood formation in Qinghai spruce
Bibliographic record
Abstract
The connections between the primary and secondary growth of trees allows better understanding of the dynamics of carbon sequestration in forest ecosystems. The relationship between primary and secondary growth of trees could change due to the diverging responses of meristems to climate warming. In this study, the bud phenology and radial growth dynamics of Qinghai spruce (Picea crassifolia) in arid and semi-arid areas of China in 2019 and 2020 were weekly monitored to analyze their response to different weather conditions and their links with carbon sink. Xylem anatomical traits (i.e. lumen radial diameter and cell wall thickness) were quantified along cell radial files after the end of xylem lignification to calculate the early-to-latewood transition date. Winter and early spring (January-March) were warmer in 2020 with a colder April compared with 2019. Precipitation in April-June was lower in 2020 than in 2019. In 2019, bud phenology occurred earlier, while the onset of xylem formation and the early-to-latewood transition date were delayed. The duration from the beginning of split bud and exposed shoot to the early-to-latewood transition date was positively correlated with the radial width of earlywood (accounting for ~80% of xylem width) and total xylem width. The longer duration of xylem cell division did not increase xylem cell production and radial width. Moreover, the duration from bud burst to the early-to-latewood transition date in 2020 was negatively linked with early phloem cell production as compared with 2019. Our findings suggest that warm conditions in winter and early spring promote the xylogenesis of Qinghai spruce, but might delay bud burst. However, the xylem width increments largely depend on the duration from bud burst to the start of latewood cell division rather than on the earlier xylogenesis and longer duration of xylem cell differentiation induced by warm conditions.
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 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".