Xylem adjustment and growth response of early- and late-successional tree species to rapid warming
Bibliographic record
Abstract
Abstract Climate changes have dramatically affected forest succession. However, how trees at different successional stages respond to climate warming is unclear in the subtropics. Here, we compared the radial growth (RW) and xylem features of the early-successional stage Castanea mollissima and late-successional stage Quercus fabri in subtropical forests and assessed their response to climate changes. All parameters, including RW, number of vessels (VN), vessel density (VD), mean (MVA) and total (TVA) vessel area, percentage of conductive area within xylem (RCTA), theoretical (Kh) and xylem-specific (Ks) hydraulic conductivity, except for MVA of C. mollissima were significantly higher than those of Q. fabri. During the drought period, a notable adverse correlation between two cluster parameters of Q. fabri, associated with hydraulic safety and efficiency, suggested a pronounced hydraulic trade-off in Q. fabri under drought conditions. Castanea mollissima was more sensitive to climate and more prone to hydraulic failure than Q. fabri. Temperatures and moisture conditions positively and negatively affected the hydraulic efficiency-related parameters of C. mollissima. Moisture conditions in the previous summer and winter were significantly negatively and positively related to the radial growth of both species. The impact of generalized warming was not evident due to variations in hydraulic strategies and species characteristics, trade-offs between non-growing and growing season climates, and specific competition. If climate warming continues, C. mollissima growth will probably significantly decline due to the increasing risk of hydraulic failure. Warming may accelerate species replacement and forest succession in the study area by changing their lifespans and competitive relationships.
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 | 0.000 | 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) | 0.001 | 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 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".