Tracing carbon and nitrogen reserve remobilization during spring leaf flush and growth following defoliation
Bibliographic record
Abstract
Woody plants rely on the remobilization of carbon (C) and nitrogen (N) reserves to support growth and survival when resource demand exceeds supply at seasonally predictable times like spring leaf flush and following unpredictable disturbances like defoliation. However, we have a poor understanding of how reserves are regulated and whether distance between source and sink tissues affects remobilization. This leads to uncertainty about which reserves-and how much-are available to support plant functions like leaf growth. To better understand the source of remobilized reserves and constraints on their allocation, we created aspen saplings with organ-specific labeled reserves by using stable isotopes (13C,15N) and grafting unlabeled or labeled stems to labeled or unlabeled root stocks. We first determined which organs had imported root or stem-derived C and N reserves after spring leaf flush. We then further tested spatial and temporal variation in reserve remobilization and import by comparing (i) upper and lower canopy leaves, (ii) early and late leaves, and (iii) early flush and re-flush leaves after defoliation. During spring flush, remobilized root C and N reserves were preferentially allocated to sinks closer to the reserve source (i.e., lower vs upper canopy leaves). However, the reduced import of 13C in late versus early leaves indicates reliance on C reserves declined over time. Following defoliation, re-flush leaves imported the same proportion of root N as spring flush leaves, but they imported a lower proportion of root C. This lower import of reserve C suggests that, after defoliation, leaf re-flush rely more heavily on current photosynthate, which may explain the reduced leaf mass recovery of re-flush canopies (31% of initial leaf mass). The reduced reliance on reserves occurred even though roots retained significant starch concentrations (~5% dry wt), suggesting that aspen prioritizes the maintenance of root reserves at the expense of fast canopy recovery.
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".