Revealing intra-annual carbon sequestration patterns through xylem anatomy and eddy covariance fluxes in eastern white pine
Bibliographic record
Abstract
Forests are major terrestrial carbon sinks, playing a crucial role in climate change mitigation. Nonetheless, the long-term seasonal carbon sequestration dynamics are scarcely understood. Here, we investigated the relationships between climate variability, carbon fluxes, and the xylem biomass in an 80-year-old plantation of Pinus strobus in Ontario, Canada. From Eddy Covariance tower, we obtained daily Gross Primary Production (GPP), precipitation, VPD and air temperature for the period 2003-2018. To estimate inter-and intra-annual xylem biomass accumulation we selected 12 trees and built wood anatomical chronologies of cell number (CN), cell wall area (CWA) and overall wall area per ring (RWA). We used moving windows correlations of daily climate data and GPP with anatomical chronologies to analyse their associations at intra-annual scale. Temperature in early spring and precipitation in mid-spring and summer strongly positively affected GPP, while summer VPD had a negative effect. For the first time, we observed strong positive correlations between GPP in the growing season and CWA (proxy for carbon quantity in each xylem cell) both in earlywood (May 10 – Aug 1, r = 0.652) and latewood (Jul 3 – Sep 3, r = 0.885). Strong positive correlations were also found between GPP and CN and RWA (r ≥ 0.724). Our results suggest a direct influence of CO2 fluxes on the accumulation of carbon in woody biomass. This work will help to reduce uncertainties in woody carbon accumulation dynamics, opening new perspectives in the study of forest carbon cycle.
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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 | 0.001 | 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 | 0.001 |
| 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".